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PaddleOCR
“03b7daa5be911c0394f6742b5087576c3795143a”上不存在“git@gitcode.net:s920243400/PaddleOCR.git”
提交 6fe01d43 编写于 作者: 文幕地方's avatar 文幕地方
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Merge branch 'dygraph' of https://github.com/PaddlePaddle/PaddleOCR into table_pr

上级 ddaa2c25 9e4ae9dc
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PPOCRLabel/PPOCRLabel.py
浏览文件 @ 6fe01d43
...@@ -28,7 +28,7 @@ from PyQt5.QtCore import QSize, Qt, QPoint, QByteArray, QTimer, QFileInfo, QPoin ...@@ -28,7 +28,7 @@ from PyQt5.QtCore import QSize, Qt, QPoint, QByteArray, QTimer, QFileInfo, QPoin
from PyQt5.QtGui import QImage, QCursor, QPixmap, QImageReader from PyQt5.QtGui import QImage, QCursor, QPixmap, QImageReader
from PyQt5.QtWidgets import QMainWindow, QListWidget, QVBoxLayout, QToolButton, QHBoxLayout, QDockWidget, QWidget, \ from PyQt5.QtWidgets import QMainWindow, QListWidget, QVBoxLayout, QToolButton, QHBoxLayout, QDockWidget, QWidget, \
QSlider, QGraphicsOpacityEffect, QMessageBox, QListView, QScrollArea, QWidgetAction, QApplication, QLabel, QGridLayout, \ QSlider, QGraphicsOpacityEffect, QMessageBox, QListView, QScrollArea, QWidgetAction, QApplication, QLabel, QGridLayout, \
QFileDialog, QListWidgetItem, QComboBox, QDialog, QAbstractItemView QFileDialog, QListWidgetItem, QComboBox, QDialog, QAbstractItemView, QSizePolicy
__dir__ = os.path.dirname(os.path.abspath(__file__)) __dir__ = os.path.dirname(os.path.abspath(__file__))
...@@ -227,6 +227,21 @@ class MainWindow(QMainWindow): ...@@ -227,6 +227,21 @@ class MainWindow(QMainWindow):
listLayout.addWidget(leftTopToolBoxContainer) listLayout.addWidget(leftTopToolBoxContainer)
# ================== Label List ================== # ================== Label List ==================
labelIndexListlBox = QHBoxLayout()
# Create and add a widget for showing current label item index
self.indexList = QListWidget()
self.indexList.setMaximumSize(30, 16777215) # limit max width
self.indexList.setEditTriggers(QAbstractItemView.NoEditTriggers) # no editable
self.indexList.itemSelectionChanged.connect(self.indexSelectionChanged)
self.indexList.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOff) # no scroll Bar
self.indexListDock = QDockWidget('No.', self)
self.indexListDock.setWidget(self.indexList)
self.indexListDock.setFeatures(QDockWidget.NoDockWidgetFeatures)
labelIndexListlBox.addWidget(self.indexListDock, 1)
# no margin between two boxes
labelIndexListlBox.setSpacing(0)
# Create and add a widget for showing current label items # Create and add a widget for showing current label items
self.labelList = EditInList() self.labelList = EditInList()
labelListContainer = QWidget() labelListContainer = QWidget()
...@@ -240,7 +255,7 @@ class MainWindow(QMainWindow): ...@@ -240,7 +255,7 @@ class MainWindow(QMainWindow):
self.labelListDock = QDockWidget(self.labelListDockName, self) self.labelListDock = QDockWidget(self.labelListDockName, self)
self.labelListDock.setWidget(self.labelList) self.labelListDock.setWidget(self.labelList)
self.labelListDock.setFeatures(QDockWidget.NoDockWidgetFeatures) self.labelListDock.setFeatures(QDockWidget.NoDockWidgetFeatures)
listLayout.addWidget(self.labelListDock) labelIndexListlBox.addWidget(self.labelListDock, 10) # label list is wider than index list
# enable labelList drag_drop to adjust bbox order # enable labelList drag_drop to adjust bbox order
# 设置选择模式为单选 # 设置选择模式为单选
...@@ -256,6 +271,17 @@ class MainWindow(QMainWindow): ...@@ -256,6 +271,17 @@ class MainWindow(QMainWindow):
# 触发放置 # 触发放置
self.labelList.model().rowsMoved.connect(self.drag_drop_happened) self.labelList.model().rowsMoved.connect(self.drag_drop_happened)
labelIndexListContainer = QWidget()
labelIndexListContainer.setLayout(labelIndexListlBox)
listLayout.addWidget(labelIndexListContainer)
# labelList indexList同步滚动
self.labelListBar = self.labelList.verticalScrollBar()
self.indexListBar = self.indexList.verticalScrollBar()
self.labelListBar.valueChanged.connect(self.move_scrollbar)
self.indexListBar.valueChanged.connect(self.move_scrollbar)
# ================== Detection Box ================== # ================== Detection Box ==================
self.BoxList = QListWidget() self.BoxList = QListWidget()
...@@ -766,6 +792,7 @@ class MainWindow(QMainWindow): ...@@ -766,6 +792,7 @@ class MainWindow(QMainWindow):
self.shapesToItemsbox.clear() self.shapesToItemsbox.clear()
self.labelList.clear() self.labelList.clear()
self.BoxList.clear() self.BoxList.clear()
self.indexList.clear()
self.filePath = None self.filePath = None
self.imageData = None self.imageData = None
self.labelFile = None self.labelFile = None
...@@ -1027,13 +1054,19 @@ class MainWindow(QMainWindow): ...@@ -1027,13 +1054,19 @@ class MainWindow(QMainWindow):
for shape in self.canvas.selectedShapes: for shape in self.canvas.selectedShapes:
shape.selected = False shape.selected = False
self.labelList.clearSelection() self.labelList.clearSelection()
self.indexList.clearSelection()
self.canvas.selectedShapes = selected_shapes self.canvas.selectedShapes = selected_shapes
for shape in self.canvas.selectedShapes: for shape in self.canvas.selectedShapes:
shape.selected = True shape.selected = True
self.shapesToItems[shape].setSelected(True) self.shapesToItems[shape].setSelected(True)
self.shapesToItemsbox[shape].setSelected(True) self.shapesToItemsbox[shape].setSelected(True)
index = self.labelList.indexFromItem(self.shapesToItems[shape]).row()
self.indexList.item(index).setSelected(True)
self.labelList.scrollToItem(self.currentItem()) # QAbstractItemView.EnsureVisible self.labelList.scrollToItem(self.currentItem()) # QAbstractItemView.EnsureVisible
# map current label item to index item and select it
index = self.labelList.indexFromItem(self.currentItem()).row()
self.indexList.scrollToItem(self.indexList.item(index))
self.BoxList.scrollToItem(self.currentBox()) self.BoxList.scrollToItem(self.currentBox())
if self.kie_mode: if self.kie_mode:
...@@ -1066,12 +1099,18 @@ class MainWindow(QMainWindow): ...@@ -1066,12 +1099,18 @@ class MainWindow(QMainWindow):
shape.paintIdx = self.displayIndexOption.isChecked() shape.paintIdx = self.displayIndexOption.isChecked()
item = HashableQListWidgetItem(shape.label) item = HashableQListWidgetItem(shape.label)
item.setFlags(item.flags() | Qt.ItemIsUserCheckable) # current difficult checkbox is disenble
item.setCheckState(Qt.Unchecked) if shape.difficult else item.setCheckState(Qt.Checked) # item.setFlags(item.flags() | Qt.ItemIsUserCheckable)
# item.setCheckState(Qt.Unchecked) if shape.difficult else item.setCheckState(Qt.Checked)
# Checked means difficult is False # Checked means difficult is False
# item.setBackground(generateColorByText(shape.label)) # item.setBackground(generateColorByText(shape.label))
self.itemsToShapes[item] = shape self.itemsToShapes[item] = shape
self.shapesToItems[shape] = item self.shapesToItems[shape] = item
# add current label item index before label string
current_index = QListWidgetItem(str(self.labelList.count()))
current_index.setTextAlignment(Qt.AlignHCenter)
self.indexList.addItem(current_index)
self.labelList.addItem(item) self.labelList.addItem(item)
# print('item in add label is ',[(p.x(), p.y()) for p in shape.points], shape.label) # print('item in add label is ',[(p.x(), p.y()) for p in shape.points], shape.label)
...@@ -1105,6 +1144,7 @@ class MainWindow(QMainWindow): ...@@ -1105,6 +1144,7 @@ class MainWindow(QMainWindow):
del self.shapesToItemsbox[shape] del self.shapesToItemsbox[shape]
del self.itemsToShapesbox[item] del self.itemsToShapesbox[item]
self.updateComboBox() self.updateComboBox()
self.updateIndexList()
def loadLabels(self, shapes): def loadLabels(self, shapes):
s = [] s = []
...@@ -1156,6 +1196,13 @@ class MainWindow(QMainWindow): ...@@ -1156,6 +1196,13 @@ class MainWindow(QMainWindow):
# self.comboBox.update_items(uniqueTextList) # self.comboBox.update_items(uniqueTextList)
def updateIndexList(self):
self.indexList.clear()
for i in range(self.labelList.count()):
string = QListWidgetItem(str(i))
string.setTextAlignment(Qt.AlignHCenter)
self.indexList.addItem(string)
def saveLabels(self, annotationFilePath, mode='Auto'): def saveLabels(self, annotationFilePath, mode='Auto'):
# Mode is Auto means that labels will be loaded from self.result_dic totally, which is the output of ocr model # Mode is Auto means that labels will be loaded from self.result_dic totally, which is the output of ocr model
annotationFilePath = ustr(annotationFilePath) annotationFilePath = ustr(annotationFilePath)
...@@ -1211,6 +1258,10 @@ class MainWindow(QMainWindow): ...@@ -1211,6 +1258,10 @@ class MainWindow(QMainWindow):
# fix copy and delete # fix copy and delete
# self.shapeSelectionChanged(True) # self.shapeSelectionChanged(True)
def move_scrollbar(self, value):
self.labelListBar.setValue(value)
self.indexListBar.setValue(value)
def labelSelectionChanged(self): def labelSelectionChanged(self):
if self._noSelectionSlot: if self._noSelectionSlot:
return return
...@@ -1223,6 +1274,21 @@ class MainWindow(QMainWindow): ...@@ -1223,6 +1274,21 @@ class MainWindow(QMainWindow):
else: else:
self.canvas.deSelectShape() self.canvas.deSelectShape()
def indexSelectionChanged(self):
if self._noSelectionSlot:
return
if self.canvas.editing():
selected_shapes = []
for item in self.indexList.selectedItems():
# map index item to label item
index = self.indexList.indexFromItem(item).row()
item = self.labelList.item(index)
selected_shapes.append(self.itemsToShapes[item])
if selected_shapes:
self.canvas.selectShapes(selected_shapes)
else:
self.canvas.deSelectShape()
def boxSelectionChanged(self): def boxSelectionChanged(self):
if self._noSelectionSlot: if self._noSelectionSlot:
# self.BoxList.scrollToItem(self.currentBox(), QAbstractItemView.PositionAtCenter) # self.BoxList.scrollToItem(self.currentBox(), QAbstractItemView.PositionAtCenter)
...@@ -1517,6 +1583,7 @@ class MainWindow(QMainWindow): ...@@ -1517,6 +1583,7 @@ class MainWindow(QMainWindow):
if self.labelList.count(): if self.labelList.count():
self.labelList.setCurrentItem(self.labelList.item(self.labelList.count() - 1)) self.labelList.setCurrentItem(self.labelList.item(self.labelList.count() - 1))
self.labelList.item(self.labelList.count() - 1).setSelected(True) self.labelList.item(self.labelList.count() - 1).setSelected(True)
self.indexList.item(self.labelList.count() - 1).setSelected(True)
# show file list image count # show file list image count
select_indexes = self.fileListWidget.selectedIndexes() select_indexes = self.fileListWidget.selectedIndexes()
...@@ -2015,12 +2082,14 @@ class MainWindow(QMainWindow): ...@@ -2015,12 +2082,14 @@ class MainWindow(QMainWindow):
for shape in self.canvas.shapes: for shape in self.canvas.shapes:
shape.paintLabel = self.displayLabelOption.isChecked() shape.paintLabel = self.displayLabelOption.isChecked()
shape.paintIdx = self.displayIndexOption.isChecked() shape.paintIdx = self.displayIndexOption.isChecked()
self.canvas.repaint()
def togglePaintIndexOption(self): def togglePaintIndexOption(self):
self.displayLabelOption.setChecked(False) self.displayLabelOption.setChecked(False)
for shape in self.canvas.shapes: for shape in self.canvas.shapes:
shape.paintLabel = self.displayLabelOption.isChecked() shape.paintLabel = self.displayLabelOption.isChecked()
shape.paintIdx = self.displayIndexOption.isChecked() shape.paintIdx = self.displayIndexOption.isChecked()
self.canvas.repaint()
def toogleDrawSquare(self): def toogleDrawSquare(self):
self.canvas.setDrawingShapeToSquare(self.drawSquaresOption.isChecked()) self.canvas.setDrawingShapeToSquare(self.drawSquaresOption.isChecked())
...@@ -2254,6 +2323,7 @@ class MainWindow(QMainWindow): ...@@ -2254,6 +2323,7 @@ class MainWindow(QMainWindow):
self.itemsToShapesbox.clear() # ADD self.itemsToShapesbox.clear() # ADD
self.shapesToItemsbox.clear() self.shapesToItemsbox.clear()
self.labelList.clear() self.labelList.clear()
self.indexList.clear()
self.BoxList.clear() self.BoxList.clear()
self.result_dic = [] self.result_dic = []
self.result_dic_locked = [] self.result_dic_locked = []
...@@ -2665,6 +2735,7 @@ class MainWindow(QMainWindow): ...@@ -2665,6 +2735,7 @@ class MainWindow(QMainWindow):
def undoShapeEdit(self): def undoShapeEdit(self):
self.canvas.restoreShape() self.canvas.restoreShape()
self.labelList.clear() self.labelList.clear()
self.indexList.clear()
self.BoxList.clear() self.BoxList.clear()
self.loadShapes(self.canvas.shapes) self.loadShapes(self.canvas.shapes)
self.actions.undo.setEnabled(self.canvas.isShapeRestorable) self.actions.undo.setEnabled(self.canvas.isShapeRestorable)
...@@ -2674,6 +2745,7 @@ class MainWindow(QMainWindow): ...@@ -2674,6 +2745,7 @@ class MainWindow(QMainWindow):
for shape in shapes: for shape in shapes:
self.addLabel(shape) self.addLabel(shape)
self.labelList.clearSelection() self.labelList.clearSelection()
self.indexList.clearSelection()
self._noSelectionSlot = False self._noSelectionSlot = False
self.canvas.loadShapes(shapes, replace=replace) self.canvas.loadShapes(shapes, replace=replace)
print("loadShapes") # 1 print("loadShapes") # 1
......
PPOCRLabel/README.md
浏览文件 @ 6fe01d43
...@@ -2,7 +2,7 @@ English | [简体中文](README_ch.md) ...@@ -2,7 +2,7 @@ English | [简体中文](README_ch.md)
# PPOCRLabel # PPOCRLabel
PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field, with built-in PPOCR model to automatically detect and re-recognize data. It is written in python3 and pyqt5, supporting rectangular box, table and multi-point annotation modes. Annotations can be directly used for the training of PPOCR detection and recognition models. PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field, with built-in PP-OCR model to automatically detect and re-recognize data. It is written in python3 and pyqt5, supporting rectangular box, table and multi-point annotation modes. Annotations can be directly used for the training of PP-OCR detection and recognition models.
<img src="./data/gif/steps_en.gif" width="100%"/> <img src="./data/gif/steps_en.gif" width="100%"/>
...@@ -142,14 +142,18 @@ In PPOCRLabel, complete the text information labeling (text and position), compl ...@@ -142,14 +142,18 @@ In PPOCRLabel, complete the text information labeling (text and position), compl
labeling in the Excel file, the recommended steps are: labeling in the Excel file, the recommended steps are:
1. Table annotation: After opening the table picture, click on the `Table Recognition` button in the upper right corner of PPOCRLabel, which will call the table recognition model in PP-Structure to automatically label 1. Table annotation: After opening the table picture, click on the `Table Recognition` button in the upper right corner of PPOCRLabel, which will call the table recognition model in PP-Structure to automatically label
the table and pop up Excel at the same time. the table and pop up Excel at the same time.
2. Change the recognition result: **label each cell** (i.e. the text in a cell is marked as a box). Right click on the box and click on `Cell Re-recognition`. 2. Change the recognition result: **label each cell** (i.e. the text in a cell is marked as a box). Right click on the box and click on `Cell Re-recognition`.
You can use the model to automatically recognise the text within a cell. You can use the model to automatically recognise the text within a cell.
3. Mark the table structure: for each cell contains the text, **mark as any identifier (such as `1`) in Excel**, to ensure that the merged cell structure is same as the original picture. 3. Mark the table structure: for each cell contains the text, **mark as any identifier (such as `1`) in Excel**, to ensure that the merged cell structure is same as the original picture.
4. Export JSON format annotation: close all Excel files corresponding to table images, click `File`-`Export table JSON annotation` to obtain JSON annotation results. > Note: If there are blank cells in the table, you also need to mark them with a bounding box so that the total number of cells is the same as in the image.
4. ***Adjust cell order:*** Click on the menu `View` - `Show Box Number` to show the box ordinal numbers, and drag all the results under the 'Recognition Results' column on the right side of the software interface to make the box numbers are arranged from left to right, top to bottom
5. Export JSON format annotation: close all Excel files corresponding to table images, click `File`-`Export table JSON annotation` to obtain JSON annotation results.
### 2.3 Note ### 2.3 Note
...@@ -219,14 +223,7 @@ PPOCRLabel supports three ways to export Label.txt ...@@ -219,14 +223,7 @@ PPOCRLabel supports three ways to export Label.txt
- Close application export - Close application export
### 3.4 Dataset division
### 3.4 Export Partial Recognition Results
For some data that are difficult to recognize, the recognition results will not be exported by **unchecking** the corresponding tags in the recognition results checkbox. The unchecked recognition result is saved as `True` in the `difficult` variable in the label file `label.txt`.
> *Note: The status of the checkboxes in the recognition results still needs to be saved manually by clicking Save Button.*
### 3.5 Dataset division
- Enter the following command in the terminal to execute the dataset division script: - Enter the following command in the terminal to execute the dataset division script:
...@@ -255,7 +252,7 @@ For some data that are difficult to recognize, the recognition results will not ...@@ -255,7 +252,7 @@ For some data that are difficult to recognize, the recognition results will not
| ... | ...
``` ```
### 3.6 Error message ### 3.5 Error message
- If paddleocr is installed with whl, it has a higher priority than calling PaddleOCR class with paddleocr.py, which may cause an exception if whl package is not updated. - If paddleocr is installed with whl, it has a higher priority than calling PaddleOCR class with paddleocr.py, which may cause an exception if whl package is not updated.
......
PPOCRLabel/README_ch.md
浏览文件 @ 6fe01d43
...@@ -7,8 +7,8 @@ PPOCRLabel是一款适用于OCR领域的半自动化图形标注工具，内置P ...@@ -7,8 +7,8 @@ PPOCRLabel是一款适用于OCR领域的半自动化图形标注工具，内置P
<img src="./data/gif/steps.gif" width="100%"/> <img src="./data/gif/steps.gif" width="100%"/>
#### 近期更新 #### 近期更新
- 2022.05：新增表格标注，使用方法见下方`2.2 表格标注`（by [whjdark](https://github.com/peterh0323); [Evezerest](https://github.com/Evezerest)) - 2022.05：**新增表格标注**，使用方法见下方`2.2 表格标注`（by [whjdark](https://github.com/peterh0323); [Evezerest](https://github.com/Evezerest))
- 2022.02：新增关键信息标注、优化标注体验（by [PeterH0323](https://github.com/peterh0323) ） - 2022.02：**新增关键信息标注**、优化标注体验（by [PeterH0323](https://github.com/peterh0323) ）
- 新增：使用 `--kie` 进入 KIE 功能，用于打【检测+识别+关键字提取】的标签 - 新增：使用 `--kie` 进入 KIE 功能，用于打【检测+识别+关键字提取】的标签
- 提升用户体验：新增文件与标记数目提示、优化交互、修复gpu使用等问题。 - 提升用户体验：新增文件与标记数目提示、优化交互、修复gpu使用等问题。
- 新增功能：使用 `C` 和 `X` 对标记框进行旋转。 - 新增功能：使用 `C` 和 `X` 对标记框进行旋转。
...@@ -113,23 +113,29 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl -i https://mirror.baidu. ...@@ -113,23 +113,29 @@ pip3 install dist/PPOCRLabel-1.0.2-py2.py3-none-any.whl -i https://mirror.baidu.
1. 安装与运行：使用上述命令安装与运行程序。 1. 安装与运行：使用上述命令安装与运行程序。
2. 打开文件夹：在菜单栏点击 “文件” - "打开目录" 选择待标记图片的文件夹<sup>[1]</sup>. 2. 打开文件夹：在菜单栏点击 “文件” - "打开目录" 选择待标记图片的文件夹<sup>[1]</sup>.
3. 自动标注：点击 ”自动标注“，使用PPOCR超轻量模型对图片文件名前图片状态<sup>[2]</sup>为 “X” 的图片进行自动标注。 3. 自动标注：点击 ”自动标注“，使用PP-OCR超轻量模型对图片文件名前图片状态<sup>[2]</sup>为 “X” 的图片进行自动标注。
4. 手动标注：点击 “矩形标注”（推荐直接在英文模式下点击键盘中的 “W”)，用户可对当前图片中模型未检出的部分进行手动绘制标记框。点击键盘Q，则使用四点标注模式（或点击“编辑” - “四点标注”），用户依次点击4个点后，双击左键表示标注完成。 4. 手动标注：点击 “矩形标注”（推荐直接在英文模式下点击键盘中的 “W”)，用户可对当前图片中模型未检出的部分进行手动绘制标记框。点击键盘Q，则使用四点标注模式（或点击“编辑” - “四点标注”），用户依次点击4个点后，双击左键表示标注完成。
5. 标记框绘制完成后，用户点击 “确认”，检测框会先被预分配一个 “待识别” 标签。 5. 标记框绘制完成后，用户点击 “确认”，检测框会先被预分配一个 “待识别” 标签。
6. 重新识别：将图片中的所有检测画绘制/调整完成后，点击 “重新识别”，PPOCR模型会对当前图片中的**所有检测框**重新识别<sup>[3]</sup>。 6. 重新识别：将图片中的所有检测画绘制/调整完成后，点击 “重新识别”，PP-OCR模型会对当前图片中的**所有检测框**重新识别<sup>[3]</sup>。
7. 内容更改：单击识别结果，对不准确的识别结果进行手动更改。 7. 内容更改：单击识别结果，对不准确的识别结果进行手动更改。
8. **确认标记：点击 “确认”，图片状态切换为 “√”，跳转至下一张。** 8. **确认标记：点击 “确认”，图片状态切换为 “√”，跳转至下一张。**
9. 删除：点击 “删除图像”，图片将会被删除至回收站。 9. 删除：点击 “删除图像”，图片将会被删除至回收站。
10. 导出结果：用户可以通过菜单中“文件-导出标记结果”手动导出，同时也可以点击“文件 - 自动导出标记结果”开启自动导出。手动确认过的标记将会被存放在所打开图片文件夹下的*Label.txt*中。在菜单栏点击 “文件” - "导出识别结果"后，会将此类图片的识别训练数据保存在*crop_img*文件夹下，识别标签保存在*rec_gt.txt*中<sup>[4]</sup>。 10. 导出结果：用户可以通过菜单中“文件-导出标记结果”手动导出，同时也可以点击“文件 - 自动导出标记结果”开启自动导出。手动确认过的标记将会被存放在所打开图片文件夹下的*Label.txt*中。在菜单栏点击 “文件” - "导出识别结果"后，会将此类图片的识别训练数据保存在*crop_img*文件夹下，识别标签保存在*rec_gt.txt*中<sup>[4]</sup>。
### 2.2 表格标注 ### 2.2 表格标注
表格标注针对表格的结构化提取，将图片中的表格转换为Excel格式，因此标注时需要配合外部软件打开Excel同时完成。 表格标注针对表格的结构化提取，将图片中的表格转换为Excel格式，因此标注时需要配合外部软件打开Excel同时完成。在PPOCRLabel软件中完成表格中的文字信息标注（文字与位置）、在Excel文件中完成表格结构信息标注，推荐的步骤为：
在PPOCRLabel软件中完成表格中的文字信息标注（文字与位置）、在Excel文件中完成表格结构信息标注，推荐的步骤为：
1. 表格识别：打开表格图片后，点击软件右上角 `表格识别` 按钮，软件调用PP-Structure中的表格识别模型，自动为表格打标签，同时弹出Excel 1. 表格识别：打开表格图片后，点击软件右上角 `表格识别` 按钮，软件调用PP-Structure中的表格识别模型，自动为表格打标签，同时弹出Excel
2. 更改识别结果：**以表格中的单元格为单位增加标注框**（即一个单元格内的文字都标记为一个框）。标注框上鼠标右键后点击 `单元格重识别`
2. 更改标注结果：**以表格中的单元格为单位增加标注框**（即一个单元格内的文字都标记为一个框）。标注框上鼠标右键后点击 `单元格重识别`
可利用模型自动识别单元格内的文字。 可利用模型自动识别单元格内的文字。
3. 标注表格结构：将表格图像中有文字的单元格，**在Excel中标记为任意标识符（如`1`）**，保证Excel中的单元格合并情况与原图相同即可。
4. 导出JSON格式：关闭所有表格图像对应的Excel，点击 `文件`-`导出表格JSON标注` 获得JSON标注结果。 > 注意：如果表格中存在空白单元格，同样需要使用一个标注框将其标出，使得单元格总数与图像中保持一致。
3. **调整单元格顺序**：点击软件`视图-显示框编号` 打开标注框序号，在软件界面右侧拖动 `识别结果` 一栏下的所有结果，使得标注框编号按照从左到右，从上到下的顺序排列，按行依次标注。
4. 标注表格结构：**在外部Excel软件中，将存在文字的单元格标记为任意标识符（如 `1` ）**，保证Excel中的单元格合并情况与原图相同即可（即不需要Excel中的单元格文字与图片中的文字完全相同）
5. 导出JSON格式：关闭所有表格图像对应的Excel，点击 `文件`-`导出表格JSON标注` 获得JSON标注结果。
### 2.3 注意 ### 2.3 注意
...@@ -197,13 +203,7 @@ PPOCRLabel支持三种导出方式： ...@@ -197,13 +203,7 @@ PPOCRLabel支持三种导出方式：
- 关闭应用程序导出 - 关闭应用程序导出
### 3.4 导出部分识别结果 ### 3.4 数据集划分
针对部分难以识别的数据，通过在识别结果的复选框中**取消勾选**相应的标记，其识别结果不会被导出。被取消勾选的识别结果在标记文件 `label.txt` 中的 `difficult` 变量保存为 `True` 。
> *注意：识别结果中的复选框状态仍需用户手动点击确认后才能保留*
### 3.5 数据集划分
在终端中输入以下命令执行数据集划分脚本： 在终端中输入以下命令执行数据集划分脚本：
...@@ -232,7 +232,7 @@ python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ../ ...@@ -232,7 +232,7 @@ python gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ../
| ... | ...
``` ```
### 3.6 错误提示 ### 3.5 错误提示
- 如果同时使用whl包安装了paddleocr，其优先级大于通过paddleocr.py调用PaddleOCR类，whl包未更新时会导致程序异常。 - 如果同时使用whl包安装了paddleocr，其优先级大于通过paddleocr.py调用PaddleOCR类，whl包未更新时会导致程序异常。
......
PPOCRLabel/libs/canvas.py
浏览文件 @ 6fe01d43
...@@ -627,7 +627,7 @@ class Canvas(QWidget): ...@@ -627,7 +627,7 @@ class Canvas(QWidget):
# adaptive BBOX label & index font size # adaptive BBOX label & index font size
if self.pixmap: if self.pixmap:
h, w = self.pixmap.size().height(), self.pixmap.size().width() h, w = self.pixmap.size().height(), self.pixmap.size().width()
fontszie = int(max(h, w) / 48) fontszie = int(max(h, w) / 96)
for s in self.shapes: for s in self.shapes:
s.fontsize = fontszie s.fontsize = fontszie
......
PPOCRLabel/libs/shape.py
浏览文件 @ 6fe01d43
...@@ -126,7 +126,7 @@ class Shape(object): ...@@ -126,7 +126,7 @@ class Shape(object):
color = self.select_line_color if self.selected else self.line_color color = self.select_line_color if self.selected else self.line_color
pen = QPen(color) pen = QPen(color)
# Try using integer sizes for smoother drawing(?) # Try using integer sizes for smoother drawing(?)
pen.setWidth(max(1, int(round(2.0 / self.scale)))) # pen.setWidth(max(1, int(round(2.0 / self.scale))))
painter.setPen(pen) painter.setPen(pen)
line_path = QPainterPath() line_path = QPainterPath()
......
applications/README.md
浏览文件 @ 6fe01d43
[English](README_en.md) | 简体中文
# 场景应用 # 场景应用
PaddleOCR场景应用覆盖通用，制造、金融、交通行业的主要OCR垂类应用，在PP-OCR、PP-Structure的通用能力基础之上，以notebook的形式展示利用场景数据微调、模型优化方法、数据增广等内容，为开发者快速落地OCR应用提供示范与启发。 PaddleOCR场景应用覆盖通用，制造、金融、交通行业的主要OCR垂类应用，在PP-OCR、PP-Structure的通用能力基础之上，以notebook的形式展示利用场景数据微调、模型优化方法、数据增广等内容，为开发者快速落地OCR应用提供示范与启发。
> 如需下载全部垂类模型，可以扫描下方二维码，关注公众号填写问卷后，加入PaddleOCR官方交流群获取20G OCR学习大礼包（内含《动手学OCR》电子书、课程回放视频、前沿论文等重磅资料） - [教程文档](#1)
- [通用](#11)
- [制造](#12)
- [金融](#13)
- [交通](#14)
<div align="center"> - [模型下载](#2)
<img src="https://ai-studio-static-online.cdn.bcebos.com/dd721099bd50478f9d5fb13d8dd00fad69c22d6848244fd3a1d3980d7fefc63e" width = "150" height = "150" />
</div> <a name="1"></a>
## 教程文档
<a name="11"></a>
### 通用
| 类别 | 亮点 | 模型下载 | 教程 |
| ---------------------- | ------------ | -------------- | --------------------------------------- |
| 高精度中文识别模型SVTR | 比PP-OCRv3识别模型精度高3%，可用于数据挖掘或对预测效率要求不高的场景。| [模型下载](#2) | [中文](./高精度中文识别模型.md)/English |
| 手写体识别 | 新增字形支持 | | |
<a name="12"></a>
> 如果您是企业开发者且未在下述场景中找到合适的方案，可以填写[OCR应用合作调研问卷](https://paddle.wjx.cn/vj/QwF7GKw.aspx)，免费与官方团队展开不同层次的合作，包括但不限于问题抽象、确定技术方案、项目答疑、共同研发等。如果您已经使用PaddleOCR落地项目，也可以填写此问卷，与飞桨平台共同宣传推广，提升企业技术品宣。期待您的提交！ ### 制造
## 通用 | 类别 | 亮点 | 模型下载 | 教程 | 示例图 |
| -------------- | ------------------------------ | -------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
| 数码管识别 | 数码管数据合成、漏识别调优 | [模型下载](#2) | [中文](./光功率计数码管字符识别/光功率计数码管字符识别.md)/English | <img src="https://ai-studio-static-online.cdn.bcebos.com/7d5774a273f84efba5b9ce7fd3f86e9ef24b6473e046444db69fa3ca20ac0986" width = "200" height = "100" /> |
| 液晶屏读数识别 | 检测模型蒸馏、Serving部署 | [模型下载](#2) | [中文](./液晶屏读数识别.md)/English | <img src="https://ai-studio-static-online.cdn.bcebos.com/901ab741cb46441ebec510b37e63b9d8d1b7c95f63cc4e5e8757f35179ae6373" width = "200" height = "100" /> |
| 包装生产日期 | 点阵字符合成、过曝过暗文字识别 | [模型下载](#2) | [中文](./包装生产日期识别.md)/English | <img src="https://ai-studio-static-online.cdn.bcebos.com/d9e0533cc1df47ffa3bbe99de9e42639a3ebfa5bce834bafb1ca4574bf9db684" width = "200" height = "100" /> |
| PCB文字识别 | 小尺寸文本检测与识别 | [模型下载](#2) | [中文](./PCB字符识别/PCB字符识别.md)/English | <img src="https://ai-studio-static-online.cdn.bcebos.com/95d8e95bf1ab476987f2519c0f8f0c60a0cdc2c444804ed6ab08f2f7ab054880" width = "200" height = "100" /> |
| 电表识别 | 大分辨率图像检测调优 | [模型下载](#2) | | |
| 液晶屏缺陷检测 | 非文字字符识别 | | | |
| 类别 | 亮点 | 类别 | 亮点 | <a name="13"></a>
| ------------------------------------------------- | -------- | ---------- | ------------ |
| [高精度中文识别模型SVTR](./高精度中文识别模型.md) | 新增模型 | 手写体识别 | 新增字形支持 |
## 制造 ### 金融
| 类别 | 亮点 | 类别 | 亮点 | | 类别 | 亮点 | 模型下载 | 教程 | 示例图 |
| ------------------------------------------------------------ | ------------------------------ | ------------------------------------------- | -------------------- | | -------------- | ------------------------ | -------------- | ----------------------------------- | ------------------------------------------------------------ |
| [数码管识别](./光功率计数码管字符识别/光功率计数码管字符识别.md) | 数码管数据合成、漏识别调优 | 电表识别 | 大分辨率图像检测调优 | | 表单VQA | 多模态通用表单结构化提取 | [模型下载](#2) | [中文](./多模态表单识别.md)/English | <img src="https://ai-studio-static-online.cdn.bcebos.com/a3b25766f3074d2facdf88d4a60fc76612f51992fd124cf5bd846b213130665b" width = "200" height = "200" /> |
| [液晶屏读数识别](./液晶屏读数识别.md) | 检测模型蒸馏、Serving部署 | [PCB文字识别](./PCB字符识别/PCB字符识别.md) | 小尺寸文本检测与识别 | | 增值税发票 | 尽请期待 | | | |
| [包装生产日期](./包装生产日期识别.md) | 点阵字符合成、过曝过暗文字识别 | 液晶屏缺陷检测 | 非文字字符识别 | | 印章检测与识别 | 端到端弯曲文本识别 | | | |
| 通用卡证识别 | 通用结构化提取 | | | |
| 身份证识别 | 结构化提取、图像阴影 | | | |
| 合同比对 | 密集文本检测、NLP串联 | | | |
## 金融 <a name="14"></a>
| 类别 | 亮点 | 类别 | 亮点 | ### 交通
| ------------------------------ | ------------------------ | ------------ | --------------------- |
| [表单VQA](./多模态表单识别.md) | 多模态通用表单结构化提取 | 通用卡证识别 | 通用结构化提取 | | 类别 | 亮点 | 模型下载 | 教程 | 示例图 |
| 增值税发票 | 尽请期待 | 身份证识别 | 结构化提取、图像阴影 | | ----------------- | ------------------------------ | -------------- | ----------------------------------- | ------------------------------------------------------------ |
| 印章检测与识别 | 端到端弯曲文本识别 | 合同比对 | 密集文本检测、NLP串联 | | 车牌识别 | 多角度图像、轻量模型、端侧部署 | [模型下载](#2) | [中文](./轻量级车牌识别.md)/English | <img src="https://ai-studio-static-online.cdn.bcebos.com/76b6a0939c2c4cf49039b6563c4b28e241e11285d7464e799e81c58c0f7707a7" width = "200" height = "100" /> |
| 驾驶证/行驶证识别 | 尽请期待 | | | |
| 快递单识别 | 尽请期待 | | | |
<a name="2"></a>
## 模型下载
如需下载上述场景中已经训练好的垂类模型，可以扫描下方二维码，关注公众号填写问卷后，加入PaddleOCR官方交流群获取20G OCR学习大礼包（内含《动手学OCR》电子书、课程回放视频、前沿论文等重磅资料）
<div align="center">
<img src="https://ai-studio-static-online.cdn.bcebos.com/dd721099bd50478f9d5fb13d8dd00fad69c22d6848244fd3a1d3980d7fefc63e" width = "150" height = "150" />
</div>
## 交通 如果您是企业开发者且未在上述场景中找到合适的方案，可以填写[OCR应用合作调研问卷](https://paddle.wjx.cn/vj/QwF7GKw.aspx)，免费与官方团队展开不同层次的合作，包括但不限于问题抽象、确定技术方案、项目答疑、共同研发等。如果您已经使用PaddleOCR落地项目，也可以填写此问卷，与飞桨平台共同宣传推广，提升企业技术品宣。期待您的提交！
| 类别 | 亮点 | 类别 | 亮点 | <a href="https://trackgit.com">
| ------------------------------- | ------------------------------ | ---------- | -------- | <img src="https://us-central1-trackgit-analytics.cloudfunctions.net/token/ping/l63cvzo0w09yxypc7ygl" alt="traffic" />
| [车牌识别](./轻量级车牌识别.md) | 多角度图像、轻量模型、端侧部署 | 快递单识别 | 尽请期待 | </a>
| 驾驶证/行驶证识别 | 尽请期待 | | |
\ No newline at end of file
applications/手写文字识别.md 0 → 100644
浏览文件 @ 6fe01d43
# 基于PP-OCRv3的手写文字识别
- [1. 项目背景及意义](#1-项目背景及意义)
- [2. 项目内容](#2-项目内容)
- [3. PP-OCRv3识别算法介绍](#3-PP-OCRv3识别算法介绍)
- [4. 安装环境](#4-安装环境)
- [5. 数据准备](#5-数据准备)
- [6. 模型训练](#6-模型训练)
- [6.1 下载预训练模型](#61-下载预训练模型)
- [6.2 修改配置文件](#62-修改配置文件)
- [6.3 开始训练](#63-开始训练)
- [7. 模型评估](#7-模型评估)
- [8. 模型导出推理](#8-模型导出推理)
- [8.1 模型导出](#81-模型导出)
- [8.2 模型推理](#82-模型推理)
## 1. 项目背景及意义
目前光学字符识别(OCR)技术在我们的生活当中被广泛使用，但是大多数模型在通用场景下的准确性还有待提高。针对于此我们借助飞桨提供的PaddleOCR套件较容易的实现了在垂类场景下的应用。手写体在日常生活中较为常见，然而手写体的识别却存在着很大的挑战，因为每个人的手写字体风格不一样，这对于视觉模型来说还是相当有挑战的。因此训练一个手写体识别模型具有很好的现实意义。下面给出一些手写体的示例图：
![example](https://ai-studio-static-online.cdn.bcebos.com/7a8865b2836f42d382e7c3fdaedc4d307d797fa2bcd0466e9f8b7705efff5a7b)
## 2. 项目内容
本项目基于PaddleOCR套件，以PP-OCRv3识别模型为基础，针对手写文字识别场景进行优化。
Aistudio项目链接：[OCR手写文字识别](https://aistudio.baidu.com/aistudio/projectdetail/4330587)
## 3. PP-OCRv3识别算法介绍
PP-OCRv3的识别模块是基于文本识别算法[SVTR](https://arxiv.org/abs/2205.00159)优化。SVTR不再采用RNN结构，通过引入Transformers结构更加有效地挖掘文本行图像的上下文信息，从而提升文本识别能力。如下图所示，PP-OCRv3采用了6个优化策略。
![v3_rec](https://ai-studio-static-online.cdn.bcebos.com/d4f5344b5b854d50be738671598a89a45689c6704c4d481fb904dd7cf72f2a1a)
优化策略汇总如下：
* SVTR_LCNet：轻量级文本识别网络
* GTC：Attention指导CTC训练策略
* TextConAug：挖掘文字上下文信息的数据增广策略
* TextRotNet：自监督的预训练模型
* UDML：联合互学习策略
* UIM：无标注数据挖掘方案
详细优化策略描述请参考[PP-OCRv3优化策略](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.5/doc/doc_ch/PP-OCRv3_introduction.md#3-%E8%AF%86%E5%88%AB%E4%BC%98%E5%8C%96)
## 4. 安装环境
```python
# 首先git官方的PaddleOCR项目，安装需要的依赖
git clone https://github.com/PaddlePaddle/PaddleOCR.git
cd PaddleOCR
pip install -r requirements.txt
```
## 5. 数据准备
本项目使用公开的手写文本识别数据集，包含Chinese OCR, 中科院自动化研究所-手写中文数据集[CASIA-HWDB2.x](http://www.nlpr.ia.ac.cn/databases/handwriting/Download.html)，以及由中科院手写数据和网上开源数据合并组合的[数据集](https://aistudio.baidu.com/aistudio/datasetdetail/102884/0)等，该项目已经挂载处理好的数据集，可直接下载使用进行训练。
```python
下载并解压数据
tar -xf hw_data.tar
```
## 6. 模型训练
### 6.1 下载预训练模型
首先需要下载我们需要的PP-OCRv3识别预训练模型，更多选择请自行选择其他的[文字识别模型](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.5/doc/doc_ch/models_list.md#2-%E6%96%87%E6%9C%AC%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B)
```python
# 使用该指令下载需要的预训练模型
wget -P ./pretrained_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar
# 解压预训练模型文件
tar -xf ./pretrained_models/ch_PP-OCRv3_rec_train.tar -C pretrained_models
```
### 6.2 修改配置文件
我们使用`configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml`，主要修改训练轮数和学习率参相关参数，设置预训练模型路径，设置数据集路径。 另外，batch_size可根据自己机器显存大小进行调整。 具体修改如下几个地方：
```
epoch_num: 100 # 训练epoch数
save_model_dir: ./output/ch_PP-OCR_v3_rec
save_epoch_step: 10
eval_batch_step: [0, 100] # 评估间隔，每隔100step评估一次
pretrained_model: ./pretrained_models/ch_PP-OCRv3_rec_train/best_accuracy # 预训练模型路径
lr:
name: Cosine # 修改学习率衰减策略为Cosine
learning_rate: 0.0001 # 修改fine-tune的学习率
warmup_epoch: 2 # 修改warmup轮数
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data # 训练集图片路径
ext_op_transform_idx: 1
label_file_list:
- ./train_data/chineseocr-data/rec_hand_line_all_label_train.txt # 训练集标签
- ./train_data/handwrite/HWDB2.0Train_label.txt
- ./train_data/handwrite/HWDB2.1Train_label.txt
- ./train_data/handwrite/HWDB2.2Train_label.txt
- ./train_data/handwrite/hwdb_ic13/handwriting_hwdb_train_labels.txt
- ./train_data/handwrite/HW_Chinese/train_hw.txt
ratio_list:
- 0.1
- 1.0
- 1.0
- 1.0
- 0.02
- 1.0
loader:
shuffle: true
batch_size_per_card: 64
drop_last: true
num_workers: 4
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data # 测试集图片路径
label_file_list:
- ./train_data/chineseocr-data/rec_hand_line_all_label_val.txt # 测试集标签
- ./train_data/handwrite/HWDB2.0Test_label.txt
- ./train_data/handwrite/HWDB2.1Test_label.txt
- ./train_data/handwrite/HWDB2.2Test_label.txt
- ./train_data/handwrite/hwdb_ic13/handwriting_hwdb_val_labels.txt
- ./train_data/handwrite/HW_Chinese/test_hw.txt
loader:
shuffle: false
drop_last: false
batch_size_per_card: 64
num_workers: 4
```
由于数据集大多是长文本，因此需要**注释**掉下面的数据增广策略，以便训练出更好的模型。
```
- RecConAug:
prob: 0.5
ext_data_num: 2
image_shape: [48, 320, 3]
```
### 6.3 开始训练
我们使用上面修改好的配置文件`configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml`，预训练模型，数据集路径，学习率，训练轮数等都已经设置完毕后，可以使用下面命令开始训练。
```python
# 开始训练识别模型
python tools/train.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml
```
## 7. 模型评估
在训练之前，我们可以直接使用下面命令来评估预训练模型的效果:
```python
# 评估预训练模型
python tools/eval.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml -o Global.pretrained_model="./pretrained_models/ch_PP-OCRv3_rec_train/best_accuracy"
```
```
[2022/07/14 10:46:22] ppocr INFO: load pretrain successful from ./pretrained_models/ch_PP-OCRv3_rec_train/best_accuracy
eval model:: 100%|████████████████████████████| 687/687 [03:29<00:00, 3.27it/s]
[2022/07/14 10:49:52] ppocr INFO: metric eval ***************
[2022/07/14 10:49:52] ppocr INFO: acc:0.03724954461811258
[2022/07/14 10:49:52] ppocr INFO: norm_edit_dis:0.4859541065843199
[2022/07/14 10:49:52] ppocr INFO: Teacher_acc:0.0371584699368947
[2022/07/14 10:49:52] ppocr INFO: Teacher_norm_edit_dis:0.48718814890536477
[2022/07/14 10:49:52] ppocr INFO: fps:947.8562684823883
```
可以看出，直接加载预训练模型进行评估，效果较差，因为预训练模型并不是基于手写文字进行单独训练的，所以我们需要基于预训练模型进行finetune。
训练完成后，可以进行测试评估，评估命令如下：
```python
# 评估finetune效果
python tools/eval.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml -o Global.pretrained_model="./output/ch_PP-OCR_v3_rec/best_accuracy"
```
评估结果如下，可以看出识别准确率为54.3%。
```
[2022/07/14 10:54:06] ppocr INFO: metric eval ***************
[2022/07/14 10:54:06] ppocr INFO: acc:0.5430100180913
[2022/07/14 10:54:06] ppocr INFO: norm_edit_dis:0.9203322593158589
[2022/07/14 10:54:06] ppocr INFO: Teacher_acc:0.5401183969626324
[2022/07/14 10:54:06] ppocr INFO: Teacher_norm_edit_dis:0.919827504507755
[2022/07/14 10:54:06] ppocr INFO: fps:928.948733797251
```
如需获取已训练模型，请扫码填写问卷，加入PaddleOCR官方交流群获取全部OCR垂类模型下载链接、《动手学OCR》电子书等全套OCR学习资料🎁
<div align="left">
<img src="https://ai-studio-static-online.cdn.bcebos.com/dd721099bd50478f9d5fb13d8dd00fad69c22d6848244fd3a1d3980d7fefc63e" width = "150" height = "150" />
</div>
将下载或训练完成的模型放置在对应目录下即可完成模型推理。
## 8. 模型导出推理
训练完成后，可以将训练模型转换成inference模型。inference 模型会额外保存模型的结构信息，在预测部署、加速推理上性能优越，灵活方便，适合于实际系统集成。
### 8.1 模型导出
导出命令如下：
```python
# 转化为推理模型
python tools/export_model.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml -o Global.pretrained_model="./output/ch_PP-OCR_v3_rec/best_accuracy" Global.save_inference_dir="./inference/rec_ppocrv3/"
```
### 8.2 模型推理
导出模型后，可以使用如下命令进行推理预测:
```python
# 推理预测
python tools/infer/predict_rec.py --image_dir="train_data/handwrite/HWDB2.0Test_images/104-P16_4.jpg" --rec_model_dir="./inference/rec_ppocrv3/Student"
```
```
[2022/07/14 10:55:56] ppocr INFO: In PP-OCRv3, rec_image_shape parameter defaults to '3, 48, 320', if you are using recognition model with PP-OCRv2 or an older version, please set --rec_image_shape='3,32,320
[2022/07/14 10:55:58] ppocr INFO: Predicts of train_data/handwrite/HWDB2.0Test_images/104-P16_4.jpg:('品结构,差异化的多品牌渗透使欧莱雅确立了其在中国化妆', 0.9904912114143372)
```
```python
# 可视化文字识别图片
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
import os
img_path = 'train_data/handwrite/HWDB2.0Test_images/104-P16_4.jpg'
def vis(img_path):
plt.figure()
image = Image.open(img_path)
plt.imshow(image)
plt.show()
# image = image.resize([208, 208])
vis(img_path)
```
![res](https://ai-studio-static-online.cdn.bcebos.com/ad7c02745491498d82e0ce95f4a274f9b3920b2f467646858709359b7af9d869)
applications/高精度中文识别模型.md
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...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
## 1. 简介 ## 1. 简介
PP-OCRv3是百度开源的超轻量级场景文本检测识别模型库，其中超轻量的场景中文识别模型SVTR_LCNet使用了SVTR算法结构。为了保证速度，SVTR_LCNet将SVTR模型的Local Blocks替换为LCNet，使用两层Global Blocks。在中文场景中，PP-OCRv3识别主要使用如下优化策略： PP-OCRv3是百度开源的超轻量级场景文本检测识别模型库，其中超轻量的场景中文识别模型SVTR_LCNet使用了SVTR算法结构。为了保证速度，SVTR_LCNet将SVTR模型的Local Blocks替换为LCNet，使用两层Global Blocks。在中文场景中，PP-OCRv3识别主要使用如下优化策略（[详细技术报告](../doc/doc_ch/PP-OCRv3_introduction.md)）：
- GTC：Attention指导CTC训练策略； - GTC：Attention指导CTC训练策略；
- TextConAug：挖掘文字上下文信息的数据增广策略； - TextConAug：挖掘文字上下文信息的数据增广策略；
- TextRotNet：自监督的预训练模型； - TextRotNet：自监督的预训练模型；
......
configs/vqa/re/layoutlmv2_xund_zh.yml → configs/kie/layoutlm_series/re_layoutlmv2_xfund_zh.yml
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...@@ -6,11 +6,11 @@ Global: ...@@ -6,11 +6,11 @@ Global:
save_model_dir: ./output/re_layoutlmv2_xfund_zh save_model_dir: ./output/re_layoutlmv2_xfund_zh
save_epoch_step: 2000 save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration # evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 57 ] eval_batch_step: [ 0, 19 ]
cal_metric_during_train: False cal_metric_during_train: False
save_inference_dir: save_inference_dir:
use_visualdl: False use_visualdl: False
seed: 2048 seed: 2022
infer_img: ppstructure/docs/vqa/input/zh_val_21.jpg infer_img: ppstructure/docs/vqa/input/zh_val_21.jpg
save_res_path: ./output/re_layoutlmv2_xfund_zh/res/ save_res_path: ./output/re_layoutlmv2_xfund_zh/res/
......
configs/vqa/re/layoutxlm_xfund_zh.yml → configs/kie/layoutlm_series/re_layoutxlm_xfund_zh.yml
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Global: Global:
use_gpu: True use_gpu: True
epoch_num: &epoch_num 200 epoch_num: &epoch_num 130
log_smooth_window: 10 log_smooth_window: 10
print_batch_step: 10 print_batch_step: 10
save_model_dir: ./output/re_layoutxlm/ save_model_dir: ./output/re_layoutxlm_xfund_zh
save_epoch_step: 2000 save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration # evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 19 ] eval_batch_step: [ 0, 19 ]
...@@ -12,7 +12,7 @@ Global: ...@@ -12,7 +12,7 @@ Global:
use_visualdl: False use_visualdl: False
seed: 2022 seed: 2022
infer_img: ppstructure/docs/vqa/input/zh_val_21.jpg infer_img: ppstructure/docs/vqa/input/zh_val_21.jpg
save_res_path: ./output/re/ save_res_path: ./output/re_layoutxlm_xfund_zh/res/
Architecture: Architecture:
model_type: vqa model_type: vqa
...@@ -81,7 +81,7 @@ Train: ...@@ -81,7 +81,7 @@ Train:
loader: loader:
shuffle: True shuffle: True
drop_last: False drop_last: False
batch_size_per_card: 8 batch_size_per_card: 2
num_workers: 8 num_workers: 8
collate_fn: ListCollator collate_fn: ListCollator
......
configs/vqa/ser/layoutlm_xfund_zh.yml → configs/kie/layoutlm_series/ser_layoutlm_xfund_zh.yml
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...@@ -6,13 +6,13 @@ Global: ...@@ -6,13 +6,13 @@ Global:
save_model_dir: ./output/ser_layoutlm_xfund_zh save_model_dir: ./output/ser_layoutlm_xfund_zh
save_epoch_step: 2000 save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration # evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 57 ] eval_batch_step: [ 0, 19 ]
cal_metric_during_train: False cal_metric_during_train: False
save_inference_dir: save_inference_dir:
use_visualdl: False use_visualdl: False
seed: 2022 seed: 2022
infer_img: ppstructure/docs/vqa/input/zh_val_42.jpg infer_img: ppstructure/docs/vqa/input/zh_val_42.jpg
save_res_path: ./output/ser_layoutlm_xfund_zh/res/ save_res_path: ./output/re_layoutlm_xfund_zh/res
Architecture: Architecture:
model_type: vqa model_type: vqa
...@@ -55,6 +55,7 @@ Train: ...@@ -55,6 +55,7 @@ Train:
data_dir: train_data/XFUND/zh_train/image data_dir: train_data/XFUND/zh_train/image
label_file_list: label_file_list:
- train_data/XFUND/zh_train/train.json - train_data/XFUND/zh_train/train.json
ratio_list: [ 1.0 ]
transforms: transforms:
- DecodeImage: # load image - DecodeImage: # load image
img_mode: RGB img_mode: RGB
......
configs/vqa/ser/layoutlmv2_xfund_zh.yml → configs/kie/layoutlm_series/ser_layoutlmv2_xfund_zh.yml
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...@@ -27,6 +27,7 @@ Architecture: ...@@ -27,6 +27,7 @@ Architecture:
Loss: Loss:
name: VQASerTokenLayoutLMLoss name: VQASerTokenLayoutLMLoss
num_classes: *num_classes num_classes: *num_classes
key: "backbone_out"
Optimizer: Optimizer:
name: AdamW name: AdamW
......
configs/vqa/ser/layoutxlm_xfund_zh.yml → configs/kie/layoutlm_series/ser_layoutxlm_xfund_zh.yml
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...@@ -27,6 +27,7 @@ Architecture: ...@@ -27,6 +27,7 @@ Architecture:
Loss: Loss:
name: VQASerTokenLayoutLMLoss name: VQASerTokenLayoutLMLoss
num_classes: *num_classes num_classes: *num_classes
key: "backbone_out"
Optimizer: Optimizer:
name: AdamW name: AdamW
......
configs/vqa/re/layoutxlm_funsd.yml → configs/kie/vi_layoutxlm/re_vi_layoutxlm_xfund_zh.yml
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Global: Global:
use_gpu: True use_gpu: True
epoch_num: &epoch_num 200 epoch_num: &epoch_num 130
log_smooth_window: 10 log_smooth_window: 10
print_batch_step: 10 print_batch_step: 10
save_model_dir: ./output/re_layoutxlm_funsd save_model_dir: ./output/re_vi_layoutxlm_xfund_zh
save_epoch_step: 2000 save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration # evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 57 ] eval_batch_step: [ 0, 19 ]
cal_metric_during_train: False cal_metric_during_train: False
save_inference_dir: save_inference_dir:
use_visualdl: False use_visualdl: False
seed: 2022 seed: 2022
infer_img: train_data/FUNSD/testing_data/images/83624198.png infer_img: ppstructure/docs/vqa/input/zh_val_21.jpg
save_res_path: ./output/re_layoutxlm_funsd/res/ save_res_path: ./output/re/xfund_zh/with_gt
Architecture: Architecture:
model_type: vqa model_type: vqa
...@@ -21,6 +21,7 @@ Architecture: ...@@ -21,6 +21,7 @@ Architecture:
Backbone: Backbone:
name: LayoutXLMForRe name: LayoutXLMForRe
pretrained: True pretrained: True
mode: vi
checkpoints: checkpoints:
Loss: Loss:
...@@ -50,10 +51,9 @@ Metric: ...@@ -50,10 +51,9 @@ Metric:
Train: Train:
dataset: dataset:
name: SimpleDataSet name: SimpleDataSet
data_dir: ./train_data/FUNSD/training_data/images/ data_dir: train_data/XFUND/zh_train/image
label_file_list: label_file_list:
- ./train_data/FUNSD/train_v4.json - train_data/XFUND/zh_train/train.json
# - ./train_data/FUNSD/train.json
ratio_list: [ 1.0 ] ratio_list: [ 1.0 ]
transforms: transforms:
- DecodeImage: # load image - DecodeImage: # load image
...@@ -62,8 +62,9 @@ Train: ...@@ -62,8 +62,9 @@ Train:
- VQATokenLabelEncode: # Class handling label - VQATokenLabelEncode: # Class handling label
contains_re: True contains_re: True
algorithm: *algorithm algorithm: *algorithm
class_path: &class_path ./train_data/FUNSD/class_list.txt class_path: &class_path train_data/XFUND/class_list_xfun.txt
use_textline_bbox_info: &use_textline_bbox_info True use_textline_bbox_info: &use_textline_bbox_info True
order_method: &order_method "tb-yx"
- VQATokenPad: - VQATokenPad:
max_seq_len: &max_seq_len 512 max_seq_len: &max_seq_len 512
return_attention_mask: True return_attention_mask: True
...@@ -79,22 +80,20 @@ Train: ...@@ -79,22 +80,20 @@ Train:
order: 'hwc' order: 'hwc'
- ToCHWImage: - ToCHWImage:
- KeepKeys: - KeepKeys:
# dataloader will return list in this order keep_keys: [ 'input_ids', 'bbox','attention_mask', 'token_type_ids', 'image', 'entities', 'relations'] # dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'entities', 'relations']
loader: loader:
shuffle: False shuffle: True
drop_last: False drop_last: False
batch_size_per_card: 8 batch_size_per_card: 2
num_workers: 16 num_workers: 4
collate_fn: ListCollator collate_fn: ListCollator
Eval: Eval:
dataset: dataset:
name: SimpleDataSet name: SimpleDataSet
data_dir: ./train_data/FUNSD/testing_data/images/ data_dir: train_data/XFUND/zh_val/image
label_file_list: label_file_list:
- ./train_data/FUNSD/test_v4.json - train_data/XFUND/zh_val/val.json
# - ./train_data/FUNSD/test.json
transforms: transforms:
- DecodeImage: # load image - DecodeImage: # load image
img_mode: RGB img_mode: RGB
...@@ -104,6 +103,7 @@ Eval: ...@@ -104,6 +103,7 @@ Eval:
algorithm: *algorithm algorithm: *algorithm
class_path: *class_path class_path: *class_path
use_textline_bbox_info: *use_textline_bbox_info use_textline_bbox_info: *use_textline_bbox_info
order_method: *order_method
- VQATokenPad: - VQATokenPad:
max_seq_len: *max_seq_len max_seq_len: *max_seq_len
return_attention_mask: True return_attention_mask: True
...@@ -119,11 +119,11 @@ Eval: ...@@ -119,11 +119,11 @@ Eval:
order: 'hwc' order: 'hwc'
- ToCHWImage: - ToCHWImage:
- KeepKeys: - KeepKeys:
# dataloader will return list in this order keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'entities', 'relations'] # dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'entities', 'relations']
loader: loader:
shuffle: False shuffle: False
drop_last: False drop_last: False
batch_size_per_card: 8 batch_size_per_card: 8
num_workers: 8 num_workers: 8
collate_fn: ListCollator collate_fn: ListCollator
configs/kie/vi_layoutxlm/re_vi_layoutxlm_xfund_zh_udml.yml 0 → 100644
浏览文件 @ 6fe01d43
Global:
use_gpu: True
epoch_num: &epoch_num 130
log_smooth_window: 10
print_batch_step: 10
save_model_dir: ./output/re_vi_layoutxlm_xfund_zh_udml
save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 19 ]
cal_metric_during_train: False
save_inference_dir:
use_visualdl: False
seed: 2022
infer_img: ppstructure/docs/vqa/input/zh_val_21.jpg
save_res_path: ./output/re/xfund_zh/with_gt
Architecture:
model_type: &model_type "vqa"
name: DistillationModel
algorithm: Distillation
Models:
Teacher:
pretrained:
freeze_params: false
return_all_feats: true
model_type: *model_type
algorithm: &algorithm "LayoutXLM"
Transform:
Backbone:
name: LayoutXLMForRe
pretrained: True
mode: vi
checkpoints:
Student:
pretrained:
freeze_params: false
return_all_feats: true
model_type: *model_type
algorithm: *algorithm
Transform:
Backbone:
name: LayoutXLMForRe
pretrained: True
mode: vi
checkpoints:
Loss:
name: CombinedLoss
loss_config_list:
- DistillationLossFromOutput:
weight: 1.0
model_name_list: ["Student", "Teacher"]
key: loss
reduction: mean
- DistillationVQADistanceLoss:
weight: 0.5
mode: "l2"
model_name_pairs:
- ["Student", "Teacher"]
key: hidden_states_5
name: "loss_5"
- DistillationVQADistanceLoss:
weight: 0.5
mode: "l2"
model_name_pairs:
- ["Student", "Teacher"]
key: hidden_states_8
name: "loss_8"
Optimizer:
name: AdamW
beta1: 0.9
beta2: 0.999
clip_norm: 10
lr:
learning_rate: 0.00005
warmup_epoch: 10
regularizer:
name: L2
factor: 0.00000
PostProcess:
name: DistillationRePostProcess
model_name: ["Student", "Teacher"]
key: null
Metric:
name: DistillationMetric
base_metric_name: VQAReTokenMetric
main_indicator: hmean
key: "Student"
Train:
dataset:
name: SimpleDataSet
data_dir: train_data/XFUND/zh_train/image
label_file_list:
- train_data/XFUND/zh_train/train.json
ratio_list: [ 1.0 ]
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: True
algorithm: *algorithm
class_path: &class_path train_data/XFUND/class_list_xfun.txt
use_textline_bbox_info: &use_textline_bbox_info True
# [None, "tb-yx"]
order_method: &order_method "tb-yx"
- VQATokenPad:
max_seq_len: &max_seq_len 512
return_attention_mask: True
- VQAReTokenRelation:
- VQAReTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
keep_keys: [ 'input_ids', 'bbox','attention_mask', 'token_type_ids', 'image', 'entities', 'relations'] # dataloader will return list in this order
loader:
shuffle: True
drop_last: False
batch_size_per_card: 2
num_workers: 4
collate_fn: ListCollator
Eval:
dataset:
name: SimpleDataSet
data_dir: train_data/XFUND/zh_val/image
label_file_list:
- train_data/XFUND/zh_val/val.json
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: True
algorithm: *algorithm
class_path: *class_path
use_textline_bbox_info: *use_textline_bbox_info
order_method: *order_method
- VQATokenPad:
max_seq_len: *max_seq_len
return_attention_mask: True
- VQAReTokenRelation:
- VQAReTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'entities', 'relations'] # dataloader will return list in this order
loader:
shuffle: False
drop_last: False
batch_size_per_card: 8
num_workers: 8
collate_fn: ListCollator
configs/vqa/ser/layoutlm_funsd.yml → configs/kie/vi_layoutxlm/ser_vi_layoutxlm_xfund_zh.yml
浏览文件 @ 6fe01d43
...@@ -3,30 +3,38 @@ Global: ...@@ -3,30 +3,38 @@ Global:
epoch_num: &epoch_num 200 epoch_num: &epoch_num 200
log_smooth_window: 10 log_smooth_window: 10
print_batch_step: 10 print_batch_step: 10
save_model_dir: ./output/ser_layoutlm_funsd save_model_dir: ./output/ser_vi_layoutxlm_xfund_zh
save_epoch_step: 2000 save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration # evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 57 ] eval_batch_step: [ 0, 19 ]
cal_metric_during_train: False cal_metric_during_train: False
save_inference_dir: save_inference_dir:
use_visualdl: False use_visualdl: False
seed: 2022 seed: 2022
infer_img: train_data/FUNSD/testing_data/images/83624198.png infer_img: ppstructure/docs/vqa/input/zh_val_42.jpg
save_res_path: ./output/ser_layoutlm_funsd/res/ # if you want to predict using the groundtruth ocr info,
# you can use the following config
# infer_img: train_data/XFUND/zh_val/val.json
# infer_mode: False
save_res_path: ./output/ser/xfund_zh/res
Architecture: Architecture:
model_type: vqa model_type: vqa
algorithm: &algorithm "LayoutLM" algorithm: &algorithm "LayoutXLM"
Transform: Transform:
Backbone: Backbone:
name: LayoutLMForSer name: LayoutXLMForSer
pretrained: True pretrained: True
checkpoints: checkpoints:
# one of base or vi
mode: vi
num_classes: &num_classes 7 num_classes: &num_classes 7
Loss: Loss:
name: VQASerTokenLayoutLMLoss name: VQASerTokenLayoutLMLoss
num_classes: *num_classes num_classes: *num_classes
key: "backbone_out"
Optimizer: Optimizer:
name: AdamW name: AdamW
...@@ -43,7 +51,7 @@ Optimizer: ...@@ -43,7 +51,7 @@ Optimizer:
PostProcess: PostProcess:
name: VQASerTokenLayoutLMPostProcess name: VQASerTokenLayoutLMPostProcess
class_path: &class_path ./train_data/FUNSD/class_list.txt class_path: &class_path train_data/XFUND/class_list_xfun.txt
Metric: Metric:
name: VQASerTokenMetric name: VQASerTokenMetric
...@@ -52,9 +60,10 @@ Metric: ...@@ -52,9 +60,10 @@ Metric:
Train: Train:
dataset: dataset:
name: SimpleDataSet name: SimpleDataSet
data_dir: ./train_data/FUNSD/training_data/images/ data_dir: train_data/XFUND/zh_train/image
label_file_list: label_file_list:
- ./train_data/FUNSD/train.json - train_data/XFUND/zh_train/train.json
ratio_list: [ 1.0 ]
transforms: transforms:
- DecodeImage: # load image - DecodeImage: # load image
img_mode: RGB img_mode: RGB
...@@ -64,6 +73,8 @@ Train: ...@@ -64,6 +73,8 @@ Train:
algorithm: *algorithm algorithm: *algorithm
class_path: *class_path class_path: *class_path
use_textline_bbox_info: &use_textline_bbox_info True use_textline_bbox_info: &use_textline_bbox_info True
# one of [None, "tb-yx"]
order_method: &order_method "tb-yx"
- VQATokenPad: - VQATokenPad:
max_seq_len: &max_seq_len 512 max_seq_len: &max_seq_len 512
return_attention_mask: True return_attention_mask: True
...@@ -78,8 +89,7 @@ Train: ...@@ -78,8 +89,7 @@ Train:
order: 'hwc' order: 'hwc'
- ToCHWImage: - ToCHWImage:
- KeepKeys: - KeepKeys:
# dataloader will return list in this order keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels'] # dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader: loader:
shuffle: True shuffle: True
drop_last: False drop_last: False
...@@ -89,9 +99,9 @@ Train: ...@@ -89,9 +99,9 @@ Train:
Eval: Eval:
dataset: dataset:
name: SimpleDataSet name: SimpleDataSet
data_dir: train_data/FUNSD/testing_data/images/ data_dir: train_data/XFUND/zh_val/image
label_file_list: label_file_list:
- ./train_data/FUNSD/test.json - train_data/XFUND/zh_val/val.json
transforms: transforms:
- DecodeImage: # load image - DecodeImage: # load image
img_mode: RGB img_mode: RGB
...@@ -101,6 +111,7 @@ Eval: ...@@ -101,6 +111,7 @@ Eval:
algorithm: *algorithm algorithm: *algorithm
class_path: *class_path class_path: *class_path
use_textline_bbox_info: *use_textline_bbox_info use_textline_bbox_info: *use_textline_bbox_info
order_method: *order_method
- VQATokenPad: - VQATokenPad:
max_seq_len: *max_seq_len max_seq_len: *max_seq_len
return_attention_mask: True return_attention_mask: True
...@@ -115,8 +126,7 @@ Eval: ...@@ -115,8 +126,7 @@ Eval:
order: 'hwc' order: 'hwc'
- ToCHWImage: - ToCHWImage:
- KeepKeys: - KeepKeys:
# dataloader will return list in this order keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels'] # dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader: loader:
shuffle: False shuffle: False
drop_last: False drop_last: False
......
configs/vqa/ser/layoutxlm_funsd.yml → configs/kie/vi_layoutxlm/ser_vi_layoutxlm_xfund_zh_udml.yml
浏览文件 @ 6fe01d43
...@@ -3,30 +3,84 @@ Global: ...@@ -3,30 +3,84 @@ Global:
epoch_num: &epoch_num 200 epoch_num: &epoch_num 200
log_smooth_window: 10 log_smooth_window: 10
print_batch_step: 10 print_batch_step: 10
save_model_dir: ./output/ser_layoutxlm_funsd save_model_dir: ./output/ser_vi_layoutxlm_xfund_zh_udml
save_epoch_step: 2000 save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration # evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 57 ] eval_batch_step: [ 0, 19 ]
cal_metric_during_train: False cal_metric_during_train: False
save_inference_dir: save_inference_dir:
use_visualdl: False use_visualdl: False
seed: 2022 seed: 2022
infer_img: train_data/FUNSD/testing_data/images/83624198.png infer_img: ppstructure/docs/vqa/input/zh_val_42.jpg
save_res_path: output/ser_layoutxlm_funsd/res/ save_res_path: ./output/ser_layoutxlm_xfund_zh/res
Architecture: Architecture:
model_type: vqa model_type: &model_type "vqa"
name: DistillationModel
algorithm: Distillation
Models:
Teacher:
pretrained:
freeze_params: false
return_all_feats: true
model_type: *model_type
algorithm: &algorithm "LayoutXLM" algorithm: &algorithm "LayoutXLM"
Transform: Transform:
Backbone: Backbone:
name: LayoutXLMForSer name: LayoutXLMForSer
pretrained: True pretrained: True
# one of base or vi
mode: vi
checkpoints: checkpoints:
num_classes: &num_classes 7 num_classes: &num_classes 7
Student:
pretrained:
freeze_params: false
return_all_feats: true
model_type: *model_type
algorithm: *algorithm
Transform:
Backbone:
name: LayoutXLMForSer
pretrained: True
# one of base or vi
mode: vi
checkpoints:
num_classes: *num_classes
Loss: Loss:
name: VQASerTokenLayoutLMLoss name: CombinedLoss
loss_config_list:
- DistillationVQASerTokenLayoutLMLoss:
weight: 1.0
model_name_list: ["Student", "Teacher"]
key: backbone_out
num_classes: *num_classes num_classes: *num_classes
- DistillationSERDMLLoss:
weight: 1.0
act: "softmax"
use_log: true
model_name_pairs:
- ["Student", "Teacher"]
key: backbone_out
- DistillationVQADistanceLoss:
weight: 0.5
mode: "l2"
model_name_pairs:
- ["Student", "Teacher"]
key: hidden_states_5
name: "loss_5"
- DistillationVQADistanceLoss:
weight: 0.5
mode: "l2"
model_name_pairs:
- ["Student", "Teacher"]
key: hidden_states_8
name: "loss_8"
Optimizer: Optimizer:
name: AdamW name: AdamW
...@@ -36,25 +90,29 @@ Optimizer: ...@@ -36,25 +90,29 @@ Optimizer:
name: Linear name: Linear
learning_rate: 0.00005 learning_rate: 0.00005
epochs: *epoch_num epochs: *epoch_num
warmup_epoch: 2 warmup_epoch: 10
regularizer: regularizer:
name: L2 name: L2
factor: 0.00000 factor: 0.00000
PostProcess: PostProcess:
name: VQASerTokenLayoutLMPostProcess name: DistillationSerPostProcess
class_path: &class_path ./train_data/FUNSD/class_list.txt model_name: ["Student", "Teacher"]
key: backbone_out
class_path: &class_path train_data/XFUND/class_list_xfun.txt
Metric: Metric:
name: VQASerTokenMetric name: DistillationMetric
base_metric_name: VQASerTokenMetric
main_indicator: hmean main_indicator: hmean
key: "Student"
Train: Train:
dataset: dataset:
name: SimpleDataSet name: SimpleDataSet
data_dir: ./train_data/FUNSD/training_data/images/ data_dir: train_data/XFUND/zh_train/image
label_file_list: label_file_list:
- ./train_data/FUNSD/train.json - train_data/XFUND/zh_train/train.json
ratio_list: [ 1.0 ] ratio_list: [ 1.0 ]
transforms: transforms:
- DecodeImage: # load image - DecodeImage: # load image
...@@ -64,6 +122,8 @@ Train: ...@@ -64,6 +122,8 @@ Train:
contains_re: False contains_re: False
algorithm: *algorithm algorithm: *algorithm
class_path: *class_path class_path: *class_path
# one of [None, "tb-yx"]
order_method: &order_method "tb-yx"
- VQATokenPad: - VQATokenPad:
max_seq_len: &max_seq_len 512 max_seq_len: &max_seq_len 512
return_attention_mask: True return_attention_mask: True
...@@ -78,20 +138,19 @@ Train: ...@@ -78,20 +138,19 @@ Train:
order: 'hwc' order: 'hwc'
- ToCHWImage: - ToCHWImage:
- KeepKeys: - KeepKeys:
# dataloader will return list in this order keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels'] # dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader: loader:
shuffle: True shuffle: True
drop_last: False drop_last: False
batch_size_per_card: 8 batch_size_per_card: 4
num_workers: 4 num_workers: 4
Eval: Eval:
dataset: dataset:
name: SimpleDataSet name: SimpleDataSet
data_dir: train_data/FUNSD/testing_data/images/ data_dir: train_data/XFUND/zh_val/image
label_file_list: label_file_list:
- ./train_data/FUNSD/test.json - train_data/XFUND/zh_val/val.json
transforms: transforms:
- DecodeImage: # load image - DecodeImage: # load image
img_mode: RGB img_mode: RGB
...@@ -100,6 +159,7 @@ Eval: ...@@ -100,6 +159,7 @@ Eval:
contains_re: False contains_re: False
algorithm: *algorithm algorithm: *algorithm
class_path: *class_path class_path: *class_path
order_method: *order_method
- VQATokenPad: - VQATokenPad:
max_seq_len: *max_seq_len max_seq_len: *max_seq_len
return_attention_mask: True return_attention_mask: True
...@@ -114,10 +174,10 @@ Eval: ...@@ -114,10 +174,10 @@ Eval:
order: 'hwc' order: 'hwc'
- ToCHWImage: - ToCHWImage:
- KeepKeys: - KeepKeys:
# dataloader will return list in this order keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels'] # dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader: loader:
shuffle: False shuffle: False
drop_last: False drop_last: False
batch_size_per_card: 8 batch_size_per_card: 8
num_workers: 4 num_workers: 4
configs/table/table_master.yml
浏览文件 @ 6fe01d43
...@@ -107,7 +107,7 @@ Train: ...@@ -107,7 +107,7 @@ Train:
Eval: Eval:
dataset: dataset:
name: PubTabDataSet name: PubTabDataSet
data_dir: train_data/table/pubtabnet/train/ data_dir: train_data/table/pubtabnet/val/
label_file_list: [train_data/table/pubtabnet/PubTabNet_2.0.0_val.jsonl] label_file_list: [train_data/table/pubtabnet/PubTabNet_2.0.0_val.jsonl]
transforms: transforms:
- DecodeImage: - DecodeImage:
......
configs/vqa/re/layoutlmv2_funsd.yml 已删除 100644 → 0
浏览文件 @ ddaa2c25
Global:
use_gpu: True
epoch_num: &epoch_num 200
log_smooth_window: 10
print_batch_step: 10
save_model_dir: ./output/re_layoutlmv2_funsd
save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 57 ]
cal_metric_during_train: False
save_inference_dir:
use_visualdl: False
seed: 2022
infer_img: train_data/FUNSD/testing_data/images/83624198.png
save_res_path: ./output/re_layoutlmv2_funsd/res/
Architecture:
model_type: vqa
algorithm: &algorithm "LayoutLMv2"
Transform:
Backbone:
name: LayoutLMv2ForRe
pretrained: True
checkpoints:
Loss:
name: LossFromOutput
key: loss
reduction: mean
Optimizer:
name: AdamW
beta1: 0.9
beta2: 0.999
clip_norm: 10
lr:
learning_rate: 0.00005
warmup_epoch: 10
regularizer:
name: L2
factor: 0.00000
PostProcess:
name: VQAReTokenLayoutLMPostProcess
Metric:
name: VQAReTokenMetric
main_indicator: hmean
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/FUNSD/training_data/images/
label_file_list:
- ./train_data/FUNSD/train.json
ratio_list: [ 1.0 ]
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: True
algorithm: *algorithm
class_path: &class_path train_data/FUNSD/class_list.txt
- VQATokenPad:
max_seq_len: &max_seq_len 512
return_attention_mask: True
- VQAReTokenRelation:
- VQAReTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1./255.
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'entities', 'relations']
loader:
shuffle: True
drop_last: False
batch_size_per_card: 8
num_workers: 8
collate_fn: ListCollator
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/FUNSD/testing_data/images/
label_file_list:
- ./train_data/FUNSD/test.json
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: True
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: *max_seq_len
return_attention_mask: True
- VQAReTokenRelation:
- VQAReTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1./255.
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'entities', 'relations']
loader:
shuffle: False
drop_last: False
batch_size_per_card: 8
num_workers: 8
collate_fn: ListCollator
configs/vqa/ser/layoutlm_sroie.yml 已删除 100644 → 0
浏览文件 @ ddaa2c25
Global:
use_gpu: True
epoch_num: &epoch_num 200
log_smooth_window: 10
print_batch_step: 10
save_model_dir: ./output/ser_layoutlm_sroie
save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 200 ]
cal_metric_during_train: False
save_inference_dir:
use_visualdl: False
seed: 2022
infer_img: train_data/SROIE/test/X00016469670.jpg
save_res_path: ./output/ser_layoutlm_sroie/res/
Architecture:
model_type: vqa
algorithm: &algorithm "LayoutLM"
Transform:
Backbone:
name: LayoutLMForSer
pretrained: True
checkpoints:
num_classes: &num_classes 9
Loss:
name: VQASerTokenLayoutLMLoss
num_classes: *num_classes
Optimizer:
name: AdamW
beta1: 0.9
beta2: 0.999
lr:
name: Linear
learning_rate: 0.00005
epochs: *epoch_num
warmup_epoch: 2
regularizer:
name: L2
factor: 0.00000
PostProcess:
name: VQASerTokenLayoutLMPostProcess
class_path: &class_path ./train_data/SROIE/class_list.txt
Metric:
name: VQASerTokenMetric
main_indicator: hmean
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/SROIE/train
label_file_list:
- ./train_data/SROIE/train.txt
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
use_textline_bbox_info: &use_textline_bbox_info True
- VQATokenPad:
max_seq_len: &max_seq_len 512
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: True
drop_last: False
batch_size_per_card: 8
num_workers: 4
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/SROIE/test
label_file_list:
- ./train_data/SROIE/test.txt
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
use_textline_bbox_info: *use_textline_bbox_info
- VQATokenPad:
max_seq_len: *max_seq_len
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: False
drop_last: False
batch_size_per_card: 8
num_workers: 4
configs/vqa/ser/layoutlmv2_funsd.yml 已删除 100644 → 0
浏览文件 @ ddaa2c25
Global:
use_gpu: True
epoch_num: &epoch_num 200
log_smooth_window: 10
print_batch_step: 10
save_model_dir: ./output/ser_layoutlmv2_funsd
save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 100 ]
cal_metric_during_train: False
save_inference_dir:
use_visualdl: False
seed: 2022
infer_img: train_data/FUNSD/testing_data/images/83624198.png
save_res_path: ./output/ser_layoutlmv2_funsd/res/
Architecture:
model_type: vqa
algorithm: &algorithm "LayoutLMv2"
Transform:
Backbone:
name: LayoutLMv2ForSer
pretrained: True
checkpoints:
num_classes: &num_classes 7
Loss:
name: VQASerTokenLayoutLMLoss
num_classes: *num_classes
Optimizer:
name: AdamW
beta1: 0.9
beta2: 0.999
lr:
name: Linear
learning_rate: 0.00005
epochs: *epoch_num
warmup_epoch: 2
regularizer:
name: L2
factor: 0.00000
PostProcess:
name: VQASerTokenLayoutLMPostProcess
class_path: &class_path train_data/FUNSD/class_list.txt
Metric:
name: VQASerTokenMetric
main_indicator: hmean
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/FUNSD/training_data/images/
label_file_list:
- ./train_data/FUNSD/train.json
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: &max_seq_len 512
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: True
drop_last: False
batch_size_per_card: 8
num_workers: 4
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/FUNSD/testing_data/images/
label_file_list:
- ./train_data/FUNSD/test.json
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: *max_seq_len
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: False
drop_last: False
batch_size_per_card: 8
num_workers: 4
configs/vqa/ser/layoutlmv2_sroie.yml 已删除 100644 → 0
浏览文件 @ ddaa2c25
Global:
use_gpu: True
epoch_num: &epoch_num 200
log_smooth_window: 10
print_batch_step: 10
save_model_dir: ./output/ser_layoutlmv2_sroie
save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 200 ]
cal_metric_during_train: False
save_inference_dir:
use_visualdl: False
seed: 2022
infer_img: train_data/SROIE/test/X00016469670.jpg
save_res_path: ./output/ser_layoutlmv2_sroie/res/
Architecture:
model_type: vqa
algorithm: &algorithm "LayoutLMv2"
Transform:
Backbone:
name: LayoutLMv2ForSer
pretrained: True
checkpoints:
num_classes: &num_classes 9
Loss:
name: VQASerTokenLayoutLMLoss
num_classes: *num_classes
Optimizer:
name: AdamW
beta1: 0.9
beta2: 0.999
lr:
name: Linear
learning_rate: 0.00005
epochs: *epoch_num
warmup_epoch: 2
regularizer:
name: L2
factor: 0.00000
PostProcess:
name: VQASerTokenLayoutLMPostProcess
class_path: &class_path ./train_data/SROIE/class_list.txt
Metric:
name: VQASerTokenMetric
main_indicator: hmean
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/SROIE/train
label_file_list:
- ./train_data/SROIE/train.txt
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: &max_seq_len 512
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: True
drop_last: False
batch_size_per_card: 8
num_workers: 4
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/SROIE/test
label_file_list:
- ./train_data/SROIE/test.txt
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: *max_seq_len
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: False
drop_last: False
batch_size_per_card: 8
num_workers: 4
configs/vqa/ser/layoutxlm_sroie.yml 已删除 100644 → 0
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Global:
use_gpu: True
epoch_num: &epoch_num 200
log_smooth_window: 10
print_batch_step: 10
save_model_dir: ./output/ser_layoutxlm_sroie
save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 200 ]
cal_metric_during_train: False
save_inference_dir:
use_visualdl: False
seed: 2022
infer_img: train_data/SROIE/test/X00016469670.jpg
save_res_path: res_img_aug_with_gt
Architecture:
model_type: vqa
algorithm: &algorithm "LayoutXLM"
Transform:
Backbone:
name: LayoutXLMForSer
pretrained: True
checkpoints:
num_classes: &num_classes 9
Loss:
name: VQASerTokenLayoutLMLoss
num_classes: *num_classes
Optimizer:
name: AdamW
beta1: 0.9
beta2: 0.999
lr:
name: Linear
learning_rate: 0.00005
epochs: *epoch_num
warmup_epoch: 2
regularizer:
name: L2
factor: 0.00000
PostProcess:
name: VQASerTokenLayoutLMPostProcess
class_path: &class_path ./train_data/SROIE/class_list.txt
Metric:
name: VQASerTokenMetric
main_indicator: hmean
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/SROIE/train
label_file_list:
- ./train_data/SROIE/train.txt
ratio_list: [ 1.0 ]
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: &max_seq_len 512
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: True
drop_last: False
batch_size_per_card: 8
num_workers: 4
Eval:
dataset:
name: SimpleDataSet
data_dir: train_data/SROIE/test
label_file_list:
- ./train_data/SROIE/test.txt
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: *max_seq_len
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: False
drop_last: False
batch_size_per_card: 8
num_workers: 4
configs/vqa/ser/layoutxlm_wildreceipt.yml 已删除 100644 → 0
浏览文件 @ ddaa2c25
Global:
use_gpu: True
epoch_num: &epoch_num 100
log_smooth_window: 10
print_batch_step: 10
save_model_dir: ./output/ser_layoutxlm_wildreceipt
save_epoch_step: 2000
# evaluation is run every 10 iterations after the 0th iteration
eval_batch_step: [ 0, 200 ]
cal_metric_during_train: False
save_inference_dir:
use_visualdl: False
seed: 2022
infer_img: train_data//wildreceipt/image_files/Image_12/10/845be0dd6f5b04866a2042abd28d558032ef2576.jpeg
save_res_path: ./output/ser_layoutxlm_wildreceipt/res
Architecture:
model_type: vqa
algorithm: &algorithm "LayoutXLM"
Transform:
Backbone:
name: LayoutXLMForSer
pretrained: True
checkpoints:
num_classes: &num_classes 51
Loss:
name: VQASerTokenLayoutLMLoss
num_classes: *num_classes
Optimizer:
name: AdamW
beta1: 0.9
beta2: 0.999
lr:
name: Linear
learning_rate: 0.00005
epochs: *epoch_num
warmup_epoch: 2
regularizer:
name: L2
factor: 0.00000
PostProcess:
name: VQASerTokenLayoutLMPostProcess
class_path: &class_path ./train_data/wildreceipt/class_list.txt
Metric:
name: VQASerTokenMetric
main_indicator: hmean
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/wildreceipt/
label_file_list:
- ./train_data/wildreceipt/wildreceipt_train.txt
ratio_list: [ 1.0 ]
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: &max_seq_len 512
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: True
drop_last: False
batch_size_per_card: 8
num_workers: 4
Eval:
dataset:
name: SimpleDataSet
data_dir: train_data/wildreceipt
label_file_list:
- ./train_data/wildreceipt/wildreceipt_test.txt
transforms:
- DecodeImage: # load image
img_mode: RGB
channel_first: False
- VQATokenLabelEncode: # Class handling label
contains_re: False
algorithm: *algorithm
class_path: *class_path
- VQATokenPad:
max_seq_len: *max_seq_len
return_attention_mask: True
- VQASerTokenChunk:
max_seq_len: *max_seq_len
- Resize:
size: [224,224]
- NormalizeImage:
scale: 1
mean: [ 123.675, 116.28, 103.53 ]
std: [ 58.395, 57.12, 57.375 ]
order: 'hwc'
- ToCHWImage:
- KeepKeys:
# dataloader will return list in this order
keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'labels']
loader:
shuffle: False
drop_last: False
batch_size_per_card: 8
num_workers: 4
doc/doc_ch/PP-OCRv3_introduction.md
浏览文件 @ 6fe01d43
...@@ -53,10 +53,11 @@ PP-OCRv3检测模型是对PP-OCRv2中的[CML](https://arxiv.org/pdf/2109.03144.p ...@@ -53,10 +53,11 @@ PP-OCRv3检测模型是对PP-OCRv2中的[CML](https://arxiv.org/pdf/2109.03144.p
|序号|策略|模型大小|hmean|速度（cpu + mkldnn)| |序号|策略|模型大小|hmean|速度（cpu + mkldnn)|
|-|-|-|-|-| |-|-|-|-|-|
|baseline teacher|DB-R50|99M|83.5%|260ms| |baseline teacher|PP-OCR server|49M|83.2%|171ms|
|teacher1|DB-R50-LK-PAN|124M|85.0%|396ms| |teacher1|DB-R50-LK-PAN|124M|85.0%|396ms|
|teacher2|DB-R50-LK-PAN-DML|124M|86.0%|396ms| |teacher2|DB-R50-LK-PAN-DML|124M|86.0%|396ms|
|baseline student|PP-OCRv2|3M|83.2%|117ms| |baseline student|PP-OCRv2|3M|83.2%|117ms|
|student0|DB-MV3-RSE-FPN|3.6M|84.5%|124ms|
|student1|DB-MV3-CML（teacher2）|3M|84.3%|117ms| |student1|DB-MV3-CML（teacher2）|3M|84.3%|117ms|
|student2|DB-MV3-RSE-FPN-CML（teacher2）|3.6M|85.4%|124ms| |student2|DB-MV3-RSE-FPN-CML（teacher2）|3.6M|85.4%|124ms|
...@@ -184,7 +185,7 @@ UDML（Unified-Deep Mutual Learning）联合互学习是PP-OCRv2中就采用的 ...@@ -184,7 +185,7 @@ UDML（Unified-Deep Mutual Learning）联合互学习是PP-OCRv2中就采用的
**（6）UIM：无标注数据挖掘方案** **（6）UIM：无标注数据挖掘方案**
UIM（Unlabeled Images Mining）是一种非常简单的无标注数据挖掘方案。核心思想是利用高精度的文本识别大模型对无标注数据进行预测，获取伪标签，并且选择预测置信度高的样本作为训练数据，用于训练小模型。使用该策略，识别模型的准确率进一步提升到79.4%（+1%）。 UIM（Unlabeled Images Mining）是一种非常简单的无标注数据挖掘方案。核心思想是利用高精度的文本识别大模型对无标注数据进行预测，获取伪标签，并且选择预测置信度高的样本作为训练数据，用于训练小模型。使用该策略，识别模型的准确率进一步提升到79.4%（+1%）。实际操作中，我们使用全量数据集训练高精度SVTR-Tiny模型（acc=82.5%）进行数据挖掘，点击获取[模型下载地址和使用教程](../../applications/高精度中文识别模型.md)。
<div align="center"> <div align="center">
<img src="../ppocr_v3/UIM.png" width="500"> <img src="../ppocr_v3/UIM.png" width="500">
......
doc/doc_ch/detection.md
浏览文件 @ 6fe01d43
...@@ -65,7 +65,7 @@ python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/train.py -c configs/ ...@@ -65,7 +65,7 @@ python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/train.py -c configs/
``` ```
上述指令中，通过-c 选择训练使用configs/det/det_db_mv3.yml配置文件。 上述指令中，通过-c 选择训练使用configs/det/det_mv3_db.yml配置文件。
有关配置文件的详细解释，请参考[链接](./config.md)。 有关配置文件的详细解释，请参考[链接](./config.md)。
您也可以通过-o参数在不需要修改yml文件的情况下，改变训练的参数，比如，调整训练的学习率为0.0001 您也可以通过-o参数在不需要修改yml文件的情况下，改变训练的参数，比如，调整训练的学习率为0.0001
......
doc/doc_en/PP-OCRv3_introduction_en.md
浏览文件 @ 6fe01d43
...@@ -55,10 +55,11 @@ The ablation experiments are as follows: ...@@ -55,10 +55,11 @@ The ablation experiments are as follows:
|ID|Strategy|Model Size|Hmean|The Inference Time（cpu + mkldnn)| |ID|Strategy|Model Size|Hmean|The Inference Time（cpu + mkldnn)|
|-|-|-|-|-| |-|-|-|-|-|
|baseline teacher|DB-R50|99M|83.5%|260ms| |baseline teacher|PP-OCR server|49M|83.2%|171ms|
|teacher1|DB-R50-LK-PAN|124M|85.0%|396ms| |teacher1|DB-R50-LK-PAN|124M|85.0%|396ms|
|teacher2|DB-R50-LK-PAN-DML|124M|86.0%|396ms| |teacher2|DB-R50-LK-PAN-DML|124M|86.0%|396ms|
|baseline student|PP-OCRv2|3M|83.2%|117ms| |baseline student|PP-OCRv2|3M|83.2%|117ms|
|student0|DB-MV3-RSE-FPN|3.6M|84.5%|124ms|
|student1|DB-MV3-CML（teacher2）|3M|84.3%|117ms| |student1|DB-MV3-CML（teacher2）|3M|84.3%|117ms|
|student2|DB-MV3-RSE-FPN-CML（teacher2）|3.6M|85.4%|124ms| |student2|DB-MV3-RSE-FPN-CML（teacher2）|3.6M|85.4%|124ms|
...@@ -199,7 +200,7 @@ UDML (Unified-Deep Mutual Learning) is a strategy proposed in PP-OCRv2 which is ...@@ -199,7 +200,7 @@ UDML (Unified-Deep Mutual Learning) is a strategy proposed in PP-OCRv2 which is
**（6）UIM：Unlabeled Images Mining** **（6）UIM：Unlabeled Images Mining**
UIM (Unlabeled Images Mining) is a very simple unlabeled data mining strategy. The main idea is to use a high-precision text recognition model to predict unlabeled images to obtain pseudo-labels, and select samples with high prediction confidence as training data for training lightweight models. Using this strategy, the accuracy of the recognition model is further improved to 79.4% (+1%). UIM (Unlabeled Images Mining) is a very simple unlabeled data mining strategy. The main idea is to use a high-precision text recognition model to predict unlabeled images to obtain pseudo-labels, and select samples with high prediction confidence as training data for training lightweight models. Using this strategy, the accuracy of the recognition model is further improved to 79.4% (+1%). In practice, we use the full data set to train the high-precision SVTR_Tiny model (acc=82.5%) for data mining. [SVTR_Tiny model download and tutorial](../../applications/高精度中文识别模型.md).
<div align="center"> <div align="center">
<img src="../ppocr_v3/UIM.png" width="500"> <img src="../ppocr_v3/UIM.png" width="500">
......
doc/doc_en/detection_en.md
浏览文件 @ 6fe01d43
...@@ -51,7 +51,7 @@ python3 tools/train.py -c configs/det/det_mv3_db.yml \ ...@@ -51,7 +51,7 @@ python3 tools/train.py -c configs/det/det_mv3_db.yml \
-o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
``` ```
In the above instruction, use `-c` to select the training to use the `configs/det/det_db_mv3.yml` configuration file. In the above instruction, use `-c` to select the training to use the `configs/det/det_mv3_db.yml` configuration file.
For a detailed explanation of the configuration file, please refer to [config](./config_en.md). For a detailed explanation of the configuration file, please refer to [config](./config_en.md).
You can also use `-o` to change the training parameters without modifying the yml file. For example, adjust the training learning rate to 0.0001 You can also use `-o` to change the training parameters without modifying the yml file. For example, adjust the training learning rate to 0.0001
......
ppocr/data/imaug/label_ops.py
浏览文件 @ 6fe01d43
...@@ -24,6 +24,7 @@ from shapely.geometry import LineString, Point, Polygon ...@@ -24,6 +24,7 @@ from shapely.geometry import LineString, Point, Polygon
import json import json
import copy import copy
from ppocr.utils.logging import get_logger from ppocr.utils.logging import get_logger
from ppocr.data.imaug.vqa.augment import order_by_tbyx
class ClsLabelEncode(object): class ClsLabelEncode(object):
...@@ -871,6 +872,7 @@ class VQATokenLabelEncode(object): ...@@ -871,6 +872,7 @@ class VQATokenLabelEncode(object):
add_special_ids=False, add_special_ids=False,
algorithm='LayoutXLM', algorithm='LayoutXLM',
use_textline_bbox_info=True, use_textline_bbox_info=True,
order_method=None,
infer_mode=False, infer_mode=False,
ocr_engine=None, ocr_engine=None,
**kwargs): **kwargs):
...@@ -900,6 +902,8 @@ class VQATokenLabelEncode(object): ...@@ -900,6 +902,8 @@ class VQATokenLabelEncode(object):
self.infer_mode = infer_mode self.infer_mode = infer_mode
self.ocr_engine = ocr_engine self.ocr_engine = ocr_engine
self.use_textline_bbox_info = use_textline_bbox_info self.use_textline_bbox_info = use_textline_bbox_info
self.order_method = order_method
assert self.order_method in [None, "tb-yx"]
def split_bbox(self, bbox, text, tokenizer): def split_bbox(self, bbox, text, tokenizer):
words = text.split() words = text.split()
...@@ -939,6 +943,14 @@ class VQATokenLabelEncode(object): ...@@ -939,6 +943,14 @@ class VQATokenLabelEncode(object):
# load bbox and label info # load bbox and label info
ocr_info = self._load_ocr_info(data) ocr_info = self._load_ocr_info(data)
for idx in range(len(ocr_info)):
if "bbox" not in ocr_info[idx]:
ocr_info[idx]["bbox"] = self.trans_poly_to_bbox(ocr_info[idx][
"points"])
if self.order_method == "tb-yx":
ocr_info = order_by_tbyx(ocr_info)
# for re # for re
train_re = self.contains_re and not self.infer_mode train_re = self.contains_re and not self.infer_mode
if train_re: if train_re:
...@@ -978,7 +990,10 @@ class VQATokenLabelEncode(object): ...@@ -978,7 +990,10 @@ class VQATokenLabelEncode(object):
info["bbox"] = self.trans_poly_to_bbox(info["points"]) info["bbox"] = self.trans_poly_to_bbox(info["points"])
encode_res = self.tokenizer.encode( encode_res = self.tokenizer.encode(
text, pad_to_max_seq_len=False, return_attention_mask=True) text,
pad_to_max_seq_len=False,
return_attention_mask=True,
return_token_type_ids=True)
if not self.add_special_ids: if not self.add_special_ids:
# TODO: use tok.all_special_ids to remove # TODO: use tok.all_special_ids to remove
...@@ -1050,10 +1065,10 @@ class VQATokenLabelEncode(object): ...@@ -1050,10 +1065,10 @@ class VQATokenLabelEncode(object):
return data return data
def trans_poly_to_bbox(self, poly): def trans_poly_to_bbox(self, poly):
x1 = np.min([p[0] for p in poly]) x1 = int(np.min([p[0] for p in poly]))
x2 = np.max([p[0] for p in poly]) x2 = int(np.max([p[0] for p in poly]))
y1 = np.min([p[1] for p in poly]) y1 = int(np.min([p[1] for p in poly]))
y2 = np.max([p[1] for p in poly]) y2 = int(np.max([p[1] for p in poly]))
return [x1, y1, x2, y2] return [x1, y1, x2, y2]
def _load_ocr_info(self, data): def _load_ocr_info(self, data):
......
ppocr/data/imaug/vqa/__init__.py
浏览文件 @ 6fe01d43
...@@ -13,12 +13,10 @@ ...@@ -13,12 +13,10 @@
# limitations under the License. # limitations under the License.
from .token import VQATokenPad, VQASerTokenChunk, VQAReTokenChunk, VQAReTokenRelation from .token import VQATokenPad, VQASerTokenChunk, VQAReTokenChunk, VQAReTokenRelation
from .augment import DistortBBox
__all__ = [ __all__ = [
'VQATokenPad', 'VQATokenPad',
'VQASerTokenChunk', 'VQASerTokenChunk',
'VQAReTokenChunk', 'VQAReTokenChunk',
'VQAReTokenRelation', 'VQAReTokenRelation',
'DistortBBox',
] ]
ppocr/data/imaug/vqa/augment.py
浏览文件 @ 6fe01d43
...@@ -16,22 +16,18 @@ import os ...@@ -16,22 +16,18 @@ import os
import sys import sys
import numpy as np import numpy as np
import random import random
from copy import deepcopy
class DistortBBox: def order_by_tbyx(ocr_info):
def __init__(self, prob=0.5, max_scale=1, **kwargs): res = sorted(ocr_info, key=lambda r: (r["bbox"][1], r["bbox"][0]))
"""Random distort bbox for i in range(len(res) - 1):
""" for j in range(i, 0, -1):
self.prob = prob if abs(res[j + 1]["bbox"][1] - res[j]["bbox"][1]) < 20 and \
self.max_scale = max_scale (res[j + 1]["bbox"][0] < res[j]["bbox"][0]):
tmp = deepcopy(res[j])
def __call__(self, data): res[j] = deepcopy(res[j + 1])
if random.random() > self.prob: res[j + 1] = deepcopy(tmp)
return data else:
bbox = np.array(data['bbox']) break
rnd_scale = (np.random.rand(*bbox.shape) - 0.5) * 2 * self.max_scale return res
bbox = np.round(bbox + rnd_scale).astype(bbox.dtype)
data['bbox'] = np.clip(data['bbox'], 0, 1000)
data['bbox'] = bbox.tolist()
sys.stdout.flush()
return data
ppocr/losses/basic_loss.py
浏览文件 @ 6fe01d43
...@@ -63,17 +63,20 @@ class KLJSLoss(object): ...@@ -63,17 +63,20 @@ class KLJSLoss(object):
def __call__(self, p1, p2, reduction="mean"): def __call__(self, p1, p2, reduction="mean"):
if self.mode.lower() == 'kl': if self.mode.lower() == 'kl':
loss = paddle.multiply(p2, paddle.log((p2 + 1e-5) / (p1 + 1e-5) + 1e-5)) loss = paddle.multiply(p2,
paddle.log((p2 + 1e-5) / (p1 + 1e-5) + 1e-5))
loss += paddle.multiply( loss += paddle.multiply(
p1, paddle.log((p1 + 1e-5) / (p2 + 1e-5) + 1e-5)) p1, paddle.log((p1 + 1e-5) / (p2 + 1e-5) + 1e-5))
loss *= 0.5 loss *= 0.5
elif self.mode.lower() == "js": elif self.mode.lower() == "js":
loss = paddle.multiply(p2, paddle.log((2*p2 + 1e-5) / (p1 + p2 + 1e-5) + 1e-5)) loss = paddle.multiply(
p2, paddle.log((2 * p2 + 1e-5) / (p1 + p2 + 1e-5) + 1e-5))
loss += paddle.multiply( loss += paddle.multiply(
p1, paddle.log((2*p1 + 1e-5) / (p1 + p2 + 1e-5) + 1e-5)) p1, paddle.log((2 * p1 + 1e-5) / (p1 + p2 + 1e-5) + 1e-5))
loss *= 0.5 loss *= 0.5
else: else:
raise ValueError("The mode.lower() if KLJSLoss should be one of ['kl', 'js']") raise ValueError(
"The mode.lower() if KLJSLoss should be one of ['kl', 'js']")
if reduction == "mean": if reduction == "mean":
loss = paddle.mean(loss, axis=[1, 2]) loss = paddle.mean(loss, axis=[1, 2])
...@@ -154,7 +157,9 @@ class LossFromOutput(nn.Layer): ...@@ -154,7 +157,9 @@ class LossFromOutput(nn.Layer):
self.reduction = reduction self.reduction = reduction
def forward(self, predicts, batch): def forward(self, predicts, batch):
loss = predicts[self.key] loss = predicts
if self.key is not None and isinstance(predicts, dict):
loss = loss[self.key]
if self.reduction == 'mean': if self.reduction == 'mean':
loss = paddle.mean(loss) loss = paddle.mean(loss)
elif self.reduction == 'sum': elif self.reduction == 'sum':
......
ppocr/losses/combined_loss.py
浏览文件 @ 6fe01d43
...@@ -24,6 +24,9 @@ from .distillation_loss import DistillationCTCLoss ...@@ -24,6 +24,9 @@ from .distillation_loss import DistillationCTCLoss
from .distillation_loss import DistillationSARLoss from .distillation_loss import DistillationSARLoss
from .distillation_loss import DistillationDMLLoss from .distillation_loss import DistillationDMLLoss
from .distillation_loss import DistillationDistanceLoss, DistillationDBLoss, DistillationDilaDBLoss from .distillation_loss import DistillationDistanceLoss, DistillationDBLoss, DistillationDilaDBLoss
from .distillation_loss import DistillationVQASerTokenLayoutLMLoss, DistillationSERDMLLoss
from .distillation_loss import DistillationLossFromOutput
from .distillation_loss import DistillationVQADistanceLoss
class CombinedLoss(nn.Layer): class CombinedLoss(nn.Layer):
......
ppocr/losses/distillation_loss.py
浏览文件 @ 6fe01d43
...@@ -21,8 +21,10 @@ from .rec_ctc_loss import CTCLoss ...@@ -21,8 +21,10 @@ from .rec_ctc_loss import CTCLoss
from .rec_sar_loss import SARLoss from .rec_sar_loss import SARLoss
from .basic_loss import DMLLoss from .basic_loss import DMLLoss
from .basic_loss import DistanceLoss from .basic_loss import DistanceLoss
from .basic_loss import LossFromOutput
from .det_db_loss import DBLoss from .det_db_loss import DBLoss
from .det_basic_loss import BalanceLoss, MaskL1Loss, DiceLoss from .det_basic_loss import BalanceLoss, MaskL1Loss, DiceLoss
from .vqa_token_layoutlm_loss import VQASerTokenLayoutLMLoss
def _sum_loss(loss_dict): def _sum_loss(loss_dict):
...@@ -322,3 +324,133 @@ class DistillationDistanceLoss(DistanceLoss): ...@@ -322,3 +324,133 @@ class DistillationDistanceLoss(DistanceLoss):
loss_dict["{}_{}_{}_{}".format(self.name, pair[0], pair[1], loss_dict["{}_{}_{}_{}".format(self.name, pair[0], pair[1],
idx)] = loss idx)] = loss
return loss_dict return loss_dict
class DistillationVQASerTokenLayoutLMLoss(VQASerTokenLayoutLMLoss):
def __init__(self,
num_classes,
model_name_list=[],
key=None,
name="loss_ser"):
super().__init__(num_classes=num_classes)
self.model_name_list = model_name_list
self.key = key
self.name = name
def forward(self, predicts, batch):
loss_dict = dict()
for idx, model_name in enumerate(self.model_name_list):
out = predicts[model_name]
if self.key is not None:
out = out[self.key]
loss = super().forward(out, batch)
loss_dict["{}_{}".format(self.name, model_name)] = loss["loss"]
return loss_dict
class DistillationLossFromOutput(LossFromOutput):
def __init__(self,
reduction="none",
model_name_list=[],
dist_key=None,
key="loss",
name="loss_re"):
super().__init__(key=key, reduction=reduction)
self.model_name_list = model_name_list
self.name = name
self.dist_key = dist_key
def forward(self, predicts, batch):
loss_dict = dict()
for idx, model_name in enumerate(self.model_name_list):
out = predicts[model_name]
if self.dist_key is not None:
out = out[self.dist_key]
loss = super().forward(out, batch)
loss_dict["{}_{}".format(self.name, model_name)] = loss["loss"]
return loss_dict
class DistillationSERDMLLoss(DMLLoss):
"""
"""
def __init__(self,
act="softmax",
use_log=True,
num_classes=7,
model_name_pairs=[],
key=None,
name="loss_dml_ser"):
super().__init__(act=act, use_log=use_log)
assert isinstance(model_name_pairs, list)
self.key = key
self.name = name
self.num_classes = num_classes
self.model_name_pairs = model_name_pairs
def forward(self, predicts, batch):
loss_dict = dict()
for idx, pair in enumerate(self.model_name_pairs):
out1 = predicts[pair[0]]
out2 = predicts[pair[1]]
if self.key is not None:
out1 = out1[self.key]
out2 = out2[self.key]
out1 = out1.reshape([-1, out1.shape[-1]])
out2 = out2.reshape([-1, out2.shape[-1]])
attention_mask = batch[2]
if attention_mask is not None:
active_output = attention_mask.reshape([-1, ]) == 1
out1 = out1[active_output]
out2 = out2[active_output]
loss_dict["{}_{}".format(self.name, idx)] = super().forward(out1,
out2)
return loss_dict
class DistillationVQADistanceLoss(DistanceLoss):
def __init__(self,
mode="l2",
model_name_pairs=[],
key=None,
name="loss_distance",
**kargs):
super().__init__(mode=mode, **kargs)
assert isinstance(model_name_pairs, list)
self.key = key
self.model_name_pairs = model_name_pairs
self.name = name + "_l2"
def forward(self, predicts, batch):
loss_dict = dict()
for idx, pair in enumerate(self.model_name_pairs):
out1 = predicts[pair[0]]
out2 = predicts[pair[1]]
attention_mask = batch[2]
if self.key is not None:
out1 = out1[self.key]
out2 = out2[self.key]
if attention_mask is not None:
max_len = attention_mask.shape[-1]
out1 = out1[:, :max_len]
out2 = out2[:, :max_len]
out1 = out1.reshape([-1, out1.shape[-1]])
out2 = out2.reshape([-1, out2.shape[-1]])
if attention_mask is not None:
active_output = attention_mask.reshape([-1, ]) == 1
out1 = out1[active_output]
out2 = out2[active_output]
loss = super().forward(out1, out2)
if isinstance(loss, dict):
for key in loss:
loss_dict["{}_{}nohu_{}".format(self.name, key,
idx)] = loss[key]
else:
loss_dict["{}_{}_{}_{}".format(self.name, pair[0], pair[1],
idx)] = loss
return loss_dict
ppocr/losses/vqa_token_layoutlm_loss.py
浏览文件 @ 6fe01d43
...@@ -17,24 +17,28 @@ from __future__ import division ...@@ -17,24 +17,28 @@ from __future__ import division
from __future__ import print_function from __future__ import print_function
from paddle import nn from paddle import nn
from ppocr.losses.basic_loss import DMLLoss
class VQASerTokenLayoutLMLoss(nn.Layer): class VQASerTokenLayoutLMLoss(nn.Layer):
def __init__(self, num_classes): def __init__(self, num_classes, key=None):
super().__init__() super().__init__()
self.loss_class = nn.CrossEntropyLoss() self.loss_class = nn.CrossEntropyLoss()
self.num_classes = num_classes self.num_classes = num_classes
self.ignore_index = self.loss_class.ignore_index self.ignore_index = self.loss_class.ignore_index
self.key = key
def forward(self, predicts, batch): def forward(self, predicts, batch):
if isinstance(predicts, dict) and self.key is not None:
predicts = predicts[self.key]
labels = batch[5] labels = batch[5]
attention_mask = batch[2] attention_mask = batch[2]
if attention_mask is not None: if attention_mask is not None:
active_loss = attention_mask.reshape([-1, ]) == 1 active_loss = attention_mask.reshape([-1, ]) == 1
active_outputs = predicts.reshape( active_output = predicts.reshape(
[-1, self.num_classes])[active_loss] [-1, self.num_classes])[active_loss]
active_labels = labels.reshape([-1, ])[active_loss] active_label = labels.reshape([-1, ])[active_loss]
loss = self.loss_class(active_outputs, active_labels) loss = self.loss_class(active_output, active_label)
else: else:
loss = self.loss_class( loss = self.loss_class(
predicts.reshape([-1, self.num_classes]), predicts.reshape([-1, self.num_classes]),
......
ppocr/metrics/distillation_metric.py
浏览文件 @ 6fe01d43
...@@ -19,6 +19,8 @@ from .rec_metric import RecMetric ...@@ -19,6 +19,8 @@ from .rec_metric import RecMetric
from .det_metric import DetMetric from .det_metric import DetMetric
from .e2e_metric import E2EMetric from .e2e_metric import E2EMetric
from .cls_metric import ClsMetric from .cls_metric import ClsMetric
from .vqa_token_ser_metric import VQASerTokenMetric
from .vqa_token_re_metric import VQAReTokenMetric
class DistillationMetric(object): class DistillationMetric(object):
......
ppocr/modeling/architectures/base_model.py
浏览文件 @ 6fe01d43
...@@ -73,14 +73,23 @@ class BaseModel(nn.Layer): ...@@ -73,14 +73,23 @@ class BaseModel(nn.Layer):
self.return_all_feats = config.get("return_all_feats", False) self.return_all_feats = config.get("return_all_feats", False)
def forward(self, x, data=None): def forward(self, x, data=None):
y = dict() y = dict()
if self.use_transform: if self.use_transform:
x = self.transform(x) x = self.transform(x)
x = self.backbone(x) x = self.backbone(x)
if isinstance(x, dict):
y.update(x)
else:
y["backbone_out"] = x y["backbone_out"] = x
final_name = "backbone_out"
if self.use_neck: if self.use_neck:
x = self.neck(x) x = self.neck(x)
if isinstance(x, dict):
y.update(x)
else:
y["neck_out"] = x y["neck_out"] = x
final_name = "neck_out"
if self.use_head: if self.use_head:
x = self.head(x, targets=data) x = self.head(x, targets=data)
# for multi head, save ctc neck out for udml # for multi head, save ctc neck out for udml
...@@ -91,10 +100,13 @@ class BaseModel(nn.Layer): ...@@ -91,10 +100,13 @@ class BaseModel(nn.Layer):
y.update(x) y.update(x)
else: else:
y["head_out"] = x y["head_out"] = x
final_name = "head_out"
if self.return_all_feats: if self.return_all_feats:
if self.training: if self.training:
return y return y
elif isinstance(x, dict):
return x
else: else:
return {"head_out": y["head_out"]} return {final_name: x}
else: else:
return x return x
ppocr/modeling/backbones/vqa_layoutlm.py
浏览文件 @ 6fe01d43
...@@ -22,13 +22,22 @@ from paddle import nn ...@@ -22,13 +22,22 @@ from paddle import nn
from paddlenlp.transformers import LayoutXLMModel, LayoutXLMForTokenClassification, LayoutXLMForRelationExtraction from paddlenlp.transformers import LayoutXLMModel, LayoutXLMForTokenClassification, LayoutXLMForRelationExtraction
from paddlenlp.transformers import LayoutLMModel, LayoutLMForTokenClassification from paddlenlp.transformers import LayoutLMModel, LayoutLMForTokenClassification
from paddlenlp.transformers import LayoutLMv2Model, LayoutLMv2ForTokenClassification, LayoutLMv2ForRelationExtraction from paddlenlp.transformers import LayoutLMv2Model, LayoutLMv2ForTokenClassification, LayoutLMv2ForRelationExtraction
from paddlenlp.transformers import AutoModel
__all__ = ["LayoutXLMForSer", 'LayoutLMForSer'] __all__ = ["LayoutXLMForSer", "LayoutLMForSer"]
pretrained_model_dict = { pretrained_model_dict = {
LayoutXLMModel: 'layoutxlm-base-uncased', LayoutXLMModel: {
LayoutLMModel: 'layoutlm-base-uncased', "base": "layoutxlm-base-uncased",
LayoutLMv2Model: 'layoutlmv2-base-uncased' "vi": "layoutxlm-wo-backbone-base-uncased",
},
LayoutLMModel: {
"base": "layoutlm-base-uncased",
},
LayoutLMv2Model: {
"base": "layoutlmv2-base-uncased",
"vi": "layoutlmv2-wo-backbone-base-uncased",
},
} }
...@@ -36,42 +45,47 @@ class NLPBaseModel(nn.Layer): ...@@ -36,42 +45,47 @@ class NLPBaseModel(nn.Layer):
def __init__(self, def __init__(self,
base_model_class, base_model_class,
model_class, model_class,
type='ser', mode="base",
type="ser",
pretrained=True, pretrained=True,
checkpoints=None, checkpoints=None,
**kwargs): **kwargs):
super(NLPBaseModel, self).__init__() super(NLPBaseModel, self).__init__()
if checkpoints is not None: if checkpoints is not None: # load the trained model
self.model = model_class.from_pretrained(checkpoints) self.model = model_class.from_pretrained(checkpoints)
elif isinstance(pretrained, (str, )) and os.path.exists(pretrained): else: # load the pretrained-model
self.model = model_class.from_pretrained(pretrained) pretrained_model_name = pretrained_model_dict[base_model_class][
else: mode]
pretrained_model_name = pretrained_model_dict[base_model_class]
if pretrained is True: if pretrained is True:
base_model = base_model_class.from_pretrained( base_model = base_model_class.from_pretrained(
pretrained_model_name) pretrained_model_name)
else: else:
base_model = base_model_class( base_model = base_model_class.from_pretrained(pretrained)
**base_model_class.pretrained_init_configuration[ if type == "ser":
pretrained_model_name])
if type == 'ser':
self.model = model_class( self.model = model_class(
base_model, num_classes=kwargs['num_classes'], dropout=None) base_model, num_classes=kwargs["num_classes"], dropout=None)
else: else:
self.model = model_class(base_model, dropout=None) self.model = model_class(base_model, dropout=None)
self.out_channels = 1 self.out_channels = 1
self.use_visual_backbone = True
class LayoutLMForSer(NLPBaseModel): class LayoutLMForSer(NLPBaseModel):
def __init__(self, num_classes, pretrained=True, checkpoints=None, def __init__(self,
num_classes,
pretrained=True,
checkpoints=None,
mode="base",
**kwargs): **kwargs):
super(LayoutLMForSer, self).__init__( super(LayoutLMForSer, self).__init__(
LayoutLMModel, LayoutLMModel,
LayoutLMForTokenClassification, LayoutLMForTokenClassification,
'ser', mode,
"ser",
pretrained, pretrained,
checkpoints, checkpoints,
num_classes=num_classes) num_classes=num_classes, )
self.use_visual_backbone = False
def forward(self, x): def forward(self, x):
x = self.model( x = self.model(
...@@ -85,62 +99,92 @@ class LayoutLMForSer(NLPBaseModel): ...@@ -85,62 +99,92 @@ class LayoutLMForSer(NLPBaseModel):
class LayoutLMv2ForSer(NLPBaseModel): class LayoutLMv2ForSer(NLPBaseModel):
def __init__(self, num_classes, pretrained=True, checkpoints=None, def __init__(self,
num_classes,
pretrained=True,
checkpoints=None,
mode="base",
**kwargs): **kwargs):
super(LayoutLMv2ForSer, self).__init__( super(LayoutLMv2ForSer, self).__init__(
LayoutLMv2Model, LayoutLMv2Model,
LayoutLMv2ForTokenClassification, LayoutLMv2ForTokenClassification,
'ser', mode,
"ser",
pretrained, pretrained,
checkpoints, checkpoints,
num_classes=num_classes) num_classes=num_classes)
self.use_visual_backbone = True
if hasattr(self.model.layoutlmv2, "use_visual_backbone"
) and self.model.layoutlmv2.use_visual_backbone is False:
self.use_visual_backbone = False
def forward(self, x): def forward(self, x):
if self.use_visual_backbone is True:
image = x[4]
else:
image = None
x = self.model( x = self.model(
input_ids=x[0], input_ids=x[0],
bbox=x[1], bbox=x[1],
attention_mask=x[2], attention_mask=x[2],
token_type_ids=x[3], token_type_ids=x[3],
image=x[4], image=image,
position_ids=None, position_ids=None,
head_mask=None, head_mask=None,
labels=None) labels=None)
if not self.training: if self.training:
res = {"backbone_out": x[0]}
res.update(x[1])
return res
else:
return x return x
return x[0]
class LayoutXLMForSer(NLPBaseModel): class LayoutXLMForSer(NLPBaseModel):
def __init__(self, num_classes, pretrained=True, checkpoints=None, def __init__(self,
num_classes,
pretrained=True,
checkpoints=None,
mode="base",
**kwargs): **kwargs):
super(LayoutXLMForSer, self).__init__( super(LayoutXLMForSer, self).__init__(
LayoutXLMModel, LayoutXLMModel,
LayoutXLMForTokenClassification, LayoutXLMForTokenClassification,
'ser', mode,
"ser",
pretrained, pretrained,
checkpoints, checkpoints,
num_classes=num_classes) num_classes=num_classes)
self.use_visual_backbone = True
def forward(self, x): def forward(self, x):
if self.use_visual_backbone is True:
image = x[4]
else:
image = None
x = self.model( x = self.model(
input_ids=x[0], input_ids=x[0],
bbox=x[1], bbox=x[1],
attention_mask=x[2], attention_mask=x[2],
token_type_ids=x[3], token_type_ids=x[3],
image=x[4], image=image,
position_ids=None, position_ids=None,
head_mask=None, head_mask=None,
labels=None) labels=None)
if not self.training: if self.training:
res = {"backbone_out": x[0]}
res.update(x[1])
return res
else:
return x return x
return x[0]
class LayoutLMv2ForRe(NLPBaseModel): class LayoutLMv2ForRe(NLPBaseModel):
def __init__(self, pretrained=True, checkpoints=None, **kwargs): def __init__(self, pretrained=True, checkpoints=None, mode="base",
super(LayoutLMv2ForRe, self).__init__(LayoutLMv2Model, **kwargs):
LayoutLMv2ForRelationExtraction, super(LayoutLMv2ForRe, self).__init__(
're', pretrained, checkpoints) LayoutLMv2Model, LayoutLMv2ForRelationExtraction, mode, "re",
pretrained, checkpoints)
def forward(self, x): def forward(self, x):
x = self.model( x = self.model(
...@@ -158,18 +202,27 @@ class LayoutLMv2ForRe(NLPBaseModel): ...@@ -158,18 +202,27 @@ class LayoutLMv2ForRe(NLPBaseModel):
class LayoutXLMForRe(NLPBaseModel): class LayoutXLMForRe(NLPBaseModel):
def __init__(self, pretrained=True, checkpoints=None, **kwargs): def __init__(self, pretrained=True, checkpoints=None, mode="base",
super(LayoutXLMForRe, self).__init__(LayoutXLMModel, **kwargs):
LayoutXLMForRelationExtraction, super(LayoutXLMForRe, self).__init__(
're', pretrained, checkpoints) LayoutXLMModel, LayoutXLMForRelationExtraction, mode, "re",
pretrained, checkpoints)
self.use_visual_backbone = True
if hasattr(self.model.layoutxlm, "use_visual_backbone"
) and self.model.layoutxlm.use_visual_backbone is False:
self.use_visual_backbone = False
def forward(self, x): def forward(self, x):
if self.use_visual_backbone is True:
image = x[4]
else:
image = None
x = self.model( x = self.model(
input_ids=x[0], input_ids=x[0],
bbox=x[1], bbox=x[1],
attention_mask=x[2], attention_mask=x[2],
token_type_ids=x[3], token_type_ids=x[3],
image=x[4], image=image,
position_ids=None, position_ids=None,
head_mask=None, head_mask=None,
labels=None, labels=None,
......
ppocr/postprocess/__init__.py
浏览文件 @ 6fe01d43
...@@ -31,21 +31,38 @@ from .rec_postprocess import CTCLabelDecode, AttnLabelDecode, SRNLabelDecode, \ ...@@ -31,21 +31,38 @@ from .rec_postprocess import CTCLabelDecode, AttnLabelDecode, SRNLabelDecode, \
SPINLabelDecode SPINLabelDecode
from .cls_postprocess import ClsPostProcess from .cls_postprocess import ClsPostProcess
from .pg_postprocess import PGPostProcess from .pg_postprocess import PGPostProcess
from .vqa_token_ser_layoutlm_postprocess import VQASerTokenLayoutLMPostProcess from .vqa_token_ser_layoutlm_postprocess import VQASerTokenLayoutLMPostProcess, DistillationSerPostProcess
from .vqa_token_re_layoutlm_postprocess import VQAReTokenLayoutLMPostProcess from .vqa_token_re_layoutlm_postprocess import VQAReTokenLayoutLMPostProcess, DistillationRePostProcess
from .table_postprocess import TableMasterLabelDecode, TableLabelDecode from .table_postprocess import TableMasterLabelDecode, TableLabelDecode
def build_post_process(config, global_config=None): def build_post_process(config, global_config=None):
support_dict = [ support_dict = [
'DBPostProcess', 'EASTPostProcess', 'SASTPostProcess', 'FCEPostProcess', 'DBPostProcess',
'CTCLabelDecode', 'AttnLabelDecode', 'ClsPostProcess', 'SRNLabelDecode', 'EASTPostProcess',
'PGPostProcess', 'DistillationCTCLabelDecode', 'TableLabelDecode', 'SASTPostProcess',
'DistillationDBPostProcess', 'NRTRLabelDecode', 'SARLabelDecode', 'FCEPostProcess',
'SEEDLabelDecode', 'VQASerTokenLayoutLMPostProcess', 'CTCLabelDecode',
'VQAReTokenLayoutLMPostProcess', 'PRENLabelDecode', 'AttnLabelDecode',
'DistillationSARLabelDecode', 'ViTSTRLabelDecode', 'ABINetLabelDecode', 'ClsPostProcess',
'TableMasterLabelDecode', 'SPINLabelDecode' 'SRNLabelDecode',
'PGPostProcess',
'DistillationCTCLabelDecode',
'TableLabelDecode',
'DistillationDBPostProcess',
'NRTRLabelDecode',
'SARLabelDecode',
'SEEDLabelDecode',
'VQASerTokenLayoutLMPostProcess',
'VQAReTokenLayoutLMPostProcess',
'PRENLabelDecode',
'DistillationSARLabelDecode',
'ViTSTRLabelDecode',
'ABINetLabelDecode',
'TableMasterLabelDecode',
'SPINLabelDecode',
'DistillationSerPostProcess',
'DistillationRePostProcess',
] ]
if config['name'] == 'PSEPostProcess': if config['name'] == 'PSEPostProcess':
......
ppocr/postprocess/vqa_token_re_layoutlm_postprocess.py
浏览文件 @ 6fe01d43
...@@ -49,3 +49,25 @@ class VQAReTokenLayoutLMPostProcess(object): ...@@ -49,3 +49,25 @@ class VQAReTokenLayoutLMPostProcess(object):
result.append((ocr_info_head, ocr_info_tail)) result.append((ocr_info_head, ocr_info_tail))
results.append(result) results.append(result)
return results return results
class DistillationRePostProcess(VQAReTokenLayoutLMPostProcess):
"""
DistillationRePostProcess
"""
def __init__(self, model_name=["Student"], key=None, **kwargs):
super().__init__(**kwargs)
if not isinstance(model_name, list):
model_name = [model_name]
self.model_name = model_name
self.key = key
def __call__(self, preds, *args, **kwargs):
output = dict()
for name in self.model_name:
pred = preds[name]
if self.key is not None:
pred = pred[self.key]
output[name] = super().__call__(pred, *args, **kwargs)
return output
ppocr/postprocess/vqa_token_ser_layoutlm_postprocess.py
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...@@ -93,3 +93,25 @@ class VQASerTokenLayoutLMPostProcess(object): ...@@ -93,3 +93,25 @@ class VQASerTokenLayoutLMPostProcess(object):
ocr_info[idx]["pred"] = self.id2label_map_for_show[int(pred_id)] ocr_info[idx]["pred"] = self.id2label_map_for_show[int(pred_id)]
results.append(ocr_info) results.append(ocr_info)
return results return results
class DistillationSerPostProcess(VQASerTokenLayoutLMPostProcess):
"""
DistillationSerPostProcess
"""
def __init__(self, class_path, model_name=["Student"], key=None, **kwargs):
super().__init__(class_path, **kwargs)
if not isinstance(model_name, list):
model_name = [model_name]
self.model_name = model_name
self.key = key
def __call__(self, preds, batch=None, *args, **kwargs):
output = dict()
for name in self.model_name:
pred = preds[name]
if self.key is not None:
pred = pred[self.key]
output[name] = super().__call__(pred, batch=batch, *args, **kwargs)
return output
ppocr/utils/save_load.py
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...@@ -55,6 +55,9 @@ def load_model(config, model, optimizer=None, model_type='det'): ...@@ -55,6 +55,9 @@ def load_model(config, model, optimizer=None, model_type='det'):
best_model_dict = {} best_model_dict = {}
if model_type == 'vqa': if model_type == 'vqa':
# NOTE: for vqa model, resume training is not supported now
if config["Architecture"]["algorithm"] in ["Distillation"]:
return best_model_dict
checkpoints = config['Architecture']['Backbone']['checkpoints'] checkpoints = config['Architecture']['Backbone']['checkpoints']
# load vqa method metric # load vqa method metric
if checkpoints: if checkpoints:
...@@ -78,6 +81,7 @@ def load_model(config, model, optimizer=None, model_type='det'): ...@@ -78,6 +81,7 @@ def load_model(config, model, optimizer=None, model_type='det'):
logger.warning( logger.warning(
"{}.pdopt is not exists, params of optimizer is not loaded". "{}.pdopt is not exists, params of optimizer is not loaded".
format(checkpoints)) format(checkpoints))
return best_model_dict return best_model_dict
if checkpoints: if checkpoints:
...@@ -166,15 +170,19 @@ def save_model(model, ...@@ -166,15 +170,19 @@ def save_model(model,
""" """
_mkdir_if_not_exist(model_path, logger) _mkdir_if_not_exist(model_path, logger)
model_prefix = os.path.join(model_path, prefix) model_prefix = os.path.join(model_path, prefix)
if config['Architecture']["model_type"] != 'vqa':
paddle.save(optimizer.state_dict(), model_prefix + '.pdopt') paddle.save(optimizer.state_dict(), model_prefix + '.pdopt')
if config['Architecture']["model_type"] != 'vqa': if config['Architecture']["model_type"] != 'vqa':
paddle.save(model.state_dict(), model_prefix + '.pdparams') paddle.save(model.state_dict(), model_prefix + '.pdparams')
metric_prefix = model_prefix metric_prefix = model_prefix
else: else: # for vqa system, we follow the save/load rules in NLP
if config['Global']['distributed']: if config['Global']['distributed']:
model._layers.backbone.model.save_pretrained(model_prefix) arch = model._layers
else: else:
model.backbone.model.save_pretrained(model_prefix) arch = model
if config["Architecture"]["algorithm"] in ["Distillation"]:
arch = arch.Student
arch.backbone.model.save_pretrained(model_prefix)
metric_prefix = os.path.join(model_prefix, 'metric') metric_prefix = os.path.join(model_prefix, 'metric')
# save metric and config # save metric and config
with open(metric_prefix + '.states', 'wb') as f: with open(metric_prefix + '.states', 'wb') as f:
......
ppstructure/vqa/README.md
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...@@ -216,7 +216,7 @@ Use the following command to complete the tandem prediction of `OCR + SER` based ...@@ -216,7 +216,7 @@ Use the following command to complete the tandem prediction of `OCR + SER` based
```shell ```shell
cd ppstructure cd ppstructure
CUDA_VISIBLE_DEVICES=0 python3.7 vqa/predict_vqa_token_ser.py --vqa_algorithm=LayoutXLM --ser_model_dir=../output/ser/infer --ser_dict_path=../train_data/XFUND/class_list_xfun.txt --image_dir=docs/vqa/input/zh_val_42.jpg --output=output CUDA_VISIBLE_DEVICES=0 python3.7 vqa/predict_vqa_token_ser.py --vqa_algorithm=LayoutXLM --ser_model_dir=../output/ser/infer --ser_dict_path=../train_data/XFUND/class_list_xfun.txt --vis_font_path=../doc/fonts/simfang.ttf --image_dir=docs/vqa/input/zh_val_42.jpg --output=output
``` ```
After the prediction is successful, the visualization images and results will be saved in the directory specified by the `output` field After the prediction is successful, the visualization images and results will be saved in the directory specified by the `output` field
......
ppstructure/vqa/README_ch.md
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...@@ -215,7 +215,7 @@ python3.7 tools/export_model.py -c configs/vqa/ser/layoutxlm.yml -o Architecture ...@@ -215,7 +215,7 @@ python3.7 tools/export_model.py -c configs/vqa/ser/layoutxlm.yml -o Architecture
```shell ```shell
cd ppstructure cd ppstructure
CUDA_VISIBLE_DEVICES=0 python3.7 vqa/predict_vqa_token_ser.py --vqa_algorithm=LayoutXLM --ser_model_dir=../output/ser/infer --ser_dict_path=../train_data/XFUND/class_list_xfun.txt --image_dir=docs/vqa/input/zh_val_42.jpg --output=output CUDA_VISIBLE_DEVICES=0 python3.7 vqa/predict_vqa_token_ser.py --vqa_algorithm=LayoutXLM --ser_model_dir=../output/ser/infer --ser_dict_path=../train_data/XFUND/class_list_xfun.txt --vis_font_path=../doc/fonts/simfang.ttf --image_dir=docs/vqa/input/zh_val_42.jpg --output=output
``` ```
预测成功后，可视化图片和结果会保存在`output`字段指定的目录下 预测成功后，可视化图片和结果会保存在`output`字段指定的目录下
......
ppstructure/vqa/predict_vqa_token_ser.py
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...@@ -153,7 +153,7 @@ def main(args): ...@@ -153,7 +153,7 @@ def main(args):
img_res = draw_ser_results( img_res = draw_ser_results(
image_file, image_file,
ser_res, ser_res,
font_path="../doc/fonts/simfang.ttf", ) font_path=args.vis_font_path, )
img_save_path = os.path.join(args.output, img_save_path = os.path.join(args.output,
os.path.basename(image_file)) os.path.basename(image_file))
......
test_tipc/configs/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.yml
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...@@ -114,7 +114,7 @@ Train: ...@@ -114,7 +114,7 @@ Train:
name: SimpleDataSet name: SimpleDataSet
data_dir: ./train_data/ic15_data/ data_dir: ./train_data/ic15_data/
label_file_list: label_file_list:
- ./train_data/ic15_data/rec_gt_train4w.txt - ./train_data/ic15_data/rec_gt_train.txt
transforms: transforms:
- DecodeImage: - DecodeImage:
img_mode: BGR img_mode: BGR
......
test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml
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...@@ -153,7 +153,7 @@ Train: ...@@ -153,7 +153,7 @@ Train:
data_dir: ./train_data/ic15_data/ data_dir: ./train_data/ic15_data/
ext_op_transform_idx: 1 ext_op_transform_idx: 1
label_file_list: label_file_list:
- ./train_data/ic15_data/rec_gt_train4w.txt - ./train_data/ic15_data/rec_gt_train.txt
transforms: transforms:
- DecodeImage: - DecodeImage:
img_mode: BGR img_mode: BGR
......
test_tipc/configs/ch_PP-OCRv3_rec/train_infer_python.txt
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...@@ -52,8 +52,9 @@ null:null ...@@ -52,8 +52,9 @@ null:null
===========================infer_benchmark_params========================== ===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,48,320]}] random_infer_input:[{float32,[3,48,320]}]
===========================train_benchmark_params========================== ===========================train_benchmark_params==========================
batch_size:128 batch_size:64
fp_items:fp32|fp16 fp_items:fp32|fp16
epoch:1 epoch:1
--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile --profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096 flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
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===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_mobile_v2.0 model_name:ch_ppocr_mobile_v2_0
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/ infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
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===========================ch_ppocr_mobile_v2.0=========================== ===========================ch_ppocr_mobile_v2.0===========================
model_name:ch_ppocr_mobile_v2.0 model_name:ch_ppocr_mobile_v2_0
python:python3.7 python:python3.7
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/ infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_export:null infer_export:null
......
test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
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===========================paddle2onnx_params=========================== ===========================paddle2onnx_params===========================
model_name:ch_ppocr_mobile_v2.0 model_name:ch_ppocr_mobile_v2_0
python:python3.7 python:python3.7
2onnx: paddle2onnx 2onnx: paddle2onnx
--det_model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/ --det_model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0 model_name:ch_ppocr_mobile_v2_0
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0 model_name:ch_ppocr_mobile_v2_0
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
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===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_mobile_v2.0_det model_name:ch_ppocr_mobile_v2_0_det
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/ infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt
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===========================infer_params=========================== ===========================infer_params===========================
model_name:ch_ppocr_mobile_v2.0_det model_name:ch_ppocr_mobile_v2_0_det
python:python python:python
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer
infer_export:null infer_export:null
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
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===========================paddle2onnx_params=========================== ===========================paddle2onnx_params===========================
model_name:ch_ppocr_mobile_v2.0_det model_name:ch_ppocr_mobile_v2_0_det
python:python3.7 python:python3.7
2onnx: paddle2onnx 2onnx: paddle2onnx
--det_model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/ --det_model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_det model_name:ch_ppocr_mobile_v2_0_det
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/train_infer_python.txt
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===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_det model_name:ch_ppocr_mobile_v2_0_det
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
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===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_det model_name:ch_ppocr_mobile_v2_0_det
python:python3.7 python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1 gpu_list:192.168.0.1,192.168.0.2;0,1
Global.use_gpu:True Global.use_gpu:True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
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===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_det model_name:ch_ppocr_mobile_v2_0_det
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_pact_infer_python.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/train_pact_infer_python.txt
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===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_det_PACT model_name:ch_ppocr_mobile_v2_0_det_PACT
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_ptq_infer_python.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det/train_ptq_infer_python.txt
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===========================kl_quant_params=========================== ===========================kl_quant_params===========================
model_name:ch_ppocr_mobile_v2.0_det_KL model_name:ch_ppocr_mobile_v2_0_det_KL
python:python3.7 python:python3.7
Global.pretrained_model:null Global.pretrained_model:null
Global.save_inference_dir:null Global.save_inference_dir:null
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_infer_python.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det_FPGM/train_infer_python.txt
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===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_det_FPGM model_name:ch_ppocr_mobile_v2_0_det_FPGM
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
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===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_det_FPGM model_name:ch_ppocr_mobile_v2_0_det_FPGM
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
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===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_mobile_v2.0_det_KL model_name:ch_ppocr_mobile_v2_0_det_KL
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer infer_model:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_KL model_name:ch_ppocr_mobile_v2_0_det_KL
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_det_KL model_name:ch_ppocr_mobile_v2_0_det_KL
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
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===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_mobile_v2.0_det_PACT model_name:ch_ppocr_mobile_v2_0_det_PACT
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_det_pact_infer infer_model:./inference/ch_ppocr_mobile_v2.0_det_pact_infer
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_PACT model_name:ch_ppocr_mobile_v2_0_det_PACT
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_det_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_det_PACT model_name:ch_ppocr_mobile_v2_0_det_PACT
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_mobile_v2.0_rec model_name:ch_ppocr_mobile_v2_0_rec
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/ infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
浏览文件 @ 6fe01d43
===========================paddle2onnx_params=========================== ===========================paddle2onnx_params===========================
model_name:ch_ppocr_mobile_v2.0_rec model_name:ch_ppocr_mobile_v2_0_rec
python:python3.7 python:python3.7
2onnx: paddle2onnx 2onnx: paddle2onnx
--det_model_dir: --det_model_dir:
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_rec model_name:ch_ppocr_mobile_v2_0_rec
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:null --det_dirname:null
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_infer_python.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec model_name:ch_ppocr_mobile_v2_0_rec
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec model_name:ch_ppocr_mobile_v2_0_rec
python:python3.7 python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1 gpu_list:192.168.0.1,192.168.0.2;0,1
Global.use_gpu:True Global.use_gpu:True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec model_name:ch_ppocr_mobile_v2_0_rec
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_pact_infer_python.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec/train_pact_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_PACT model_name:ch_ppocr_mobile_v2_0_rec_PACT
python:python3.7 python:python3.7
gpu_list:0 gpu_list:0
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -14,7 +14,7 @@ null:null ...@@ -14,7 +14,7 @@ null:null
## ##
trainer:pact_train trainer:pact_train
norm_train:null norm_train:null
pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/rec_chinese_lite_train_v2.0.yml -o pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/ch_ppocr_mobile_v2_0_rec_PACT/rec_chinese_lite_train_v2.0.yml -o
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
null:null null:null
...@@ -28,7 +28,7 @@ null:null ...@@ -28,7 +28,7 @@ null:null
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:null norm_export:null
quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/rec_chinese_lite_train_v2.0.yml -o quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/ch_ppocr_mobile_v2_0_rec_PACT/rec_chinese_lite_train_v2.0.yml -o
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
export1:null export1:null
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_ptq_infer_python.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec/train_ptq_infer_python.txt
浏览文件 @ 6fe01d43
===========================kl_quant_params=========================== ===========================kl_quant_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_KL model_name:ch_ppocr_mobile_v2_0_rec_KL
python:python3.7 python:python3.7
Global.pretrained_model:null Global.pretrained_model:null
Global.save_inference_dir:null Global.save_inference_dir:null
infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/ infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/
infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/rec_chinese_lite_train_v2.0.yml -o infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/ch_ppocr_mobile_v2_0_rec_KL/rec_chinese_lite_train_v2.0.yml -o
infer_quant:True infer_quant:True
inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320" inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320"
--use_gpu:False|True --use_gpu:False|True
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_infer_python.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec_FPGM/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_FPGM model_name:ch_ppocr_mobile_v2_0_rec_FPGM
python:python3.7 python:python3.7
gpu_list:0 gpu_list:0
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -15,7 +15,7 @@ null:null ...@@ -15,7 +15,7 @@ null:null
trainer:fpgm_train trainer:fpgm_train
norm_train:null norm_train:null
pact_train:null pact_train:null
fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model=./pretrain_models/ch_ppocr_mobile_v2.0_rec_train/best_accuracy fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ch_ppocr_mobile_v2_0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model=./pretrain_models/ch_ppocr_mobile_v2.0_rec_train/best_accuracy
distill_train:null distill_train:null
null:null null:null
null:null null:null
...@@ -29,7 +29,7 @@ Global.save_inference_dir:./output/ ...@@ -29,7 +29,7 @@ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:null norm_export:null
quant_export:null quant_export:null
fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ch_ppocr_mobile_v2_0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o
distill_export:null distill_export:null
export1:null export1:null
export2:null export2:null
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_FPGM model_name:ch_ppocr_mobile_v2_0_rec_FPGM
python:python3.7 python:python3.7
gpu_list:0 gpu_list:0
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -15,7 +15,7 @@ null:null ...@@ -15,7 +15,7 @@ null:null
trainer:fpgm_train trainer:fpgm_train
norm_train:null norm_train:null
pact_train:null pact_train:null
fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model=./pretrain_models/ch_ppocr_mobile_v2.0_rec_train/best_accuracy fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ch_ppocr_mobile_v2_0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model=./pretrain_models/ch_ppocr_mobile_v2.0_rec_train/best_accuracy
distill_train:null distill_train:null
null:null null:null
null:null null:null
...@@ -29,7 +29,7 @@ Global.save_inference_dir:./output/ ...@@ -29,7 +29,7 @@ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:null norm_export:null
quant_export:null quant_export:null
fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ch_ppocr_mobile_v2_0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o
distill_export:null distill_export:null
export1:null export1:null
export2:null export2:null
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec_KL/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
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===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_KL model_name:ch_ppocr_mobile_v2_0_rec_KL
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_rec_klquant_infer infer_model:./inference/ch_ppocr_mobile_v2.0_rec_klquant_infer
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec_KL/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_det_KL model_name:ch_ppocr_mobile_v2_0_rec_KL
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_klquant_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec_KL/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_KL model_name:ch_ppocr_mobile_v2_0_rec_KL
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:null --det_dirname:null
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec_PACT/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
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===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_PACT model_name:ch_ppocr_mobile_v2_0_rec_PACT
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_rec_pact_infer infer_model:./inference/ch_ppocr_mobile_v2.0_rec_pact_infer
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec_PACT/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_det_PACT model_name:ch_ppocr_mobile_v2_0_rec_PACT
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/ --det_dirname:./inference/ch_ppocr_mobile_v2.0_det_pact_infer/
......
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_mobile_v2_0_rec_PACT/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
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===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_PACT model_name:ch_ppocr_mobile_v2_0_rec_PACT
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:null --det_dirname:null
......
test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_server_v2.0 model_name:ch_ppocr_server_v2_0
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_server_v2.0_det_infer/ infer_model:./inference/ch_ppocr_server_v2.0_det_infer/
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================ch_ppocr_server_v2.0=========================== ===========================ch_ppocr_server_v2.0===========================
model_name:ch_ppocr_server_v2.0 model_name:ch_ppocr_server_v2_0
python:python3.7 python:python3.7
infer_model:./inference/ch_ppocr_server_v2.0_det_infer/ infer_model:./inference/ch_ppocr_server_v2.0_det_infer/
infer_export:null infer_export:null
......
test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
浏览文件 @ 6fe01d43
===========================paddle2onnx_params=========================== ===========================paddle2onnx_params===========================
model_name:ch_ppocr_server_v2.0 model_name:ch_ppocr_server_v2_0
python:python3.7 python:python3.7
2onnx: paddle2onnx 2onnx: paddle2onnx
--det_model_dir:./inference/ch_ppocr_server_v2.0_det_infer/ --det_model_dir:./inference/ch_ppocr_server_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0/model_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_server_v2.0 model_name:ch_ppocr_server_v2_0
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/ --det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_server_v2.0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_server_v2.0 model_name:ch_ppocr_server_v2_0
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/ --det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_det/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_server_v2.0_det model_name:ch_ppocr_server_v2_0_det
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_server_v2.0_det_infer/ infer_model:./inference/ch_ppocr_server_v2.0_det_infer/
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_det/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
浏览文件 @ 6fe01d43
===========================paddle2onnx_params=========================== ===========================paddle2onnx_params===========================
model_name:ch_ppocr_server_v2.0_det model_name:ch_ppocr_server_v2_0_det
python:python3.7 python:python3.7
2onnx: paddle2onnx 2onnx: paddle2onnx
--det_model_dir:./inference/ch_ppocr_server_v2.0_det_infer/ --det_model_dir:./inference/ch_ppocr_server_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_server_v2.0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_det/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_server_v2.0_det model_name:ch_ppocr_server_v2_0_det
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/ --det_dirname:./inference/ch_ppocr_server_v2.0_det_infer/
......
test_tipc/configs/ch_ppocr_server_v2.0_det/train_infer_python.txt → test_tipc/configs/ch_ppocr_server_v2_0_det/train_infer_python.txt
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===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_server_v2.0_det model_name:ch_ppocr_server_v2_0_det
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ ...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
quant_train:null quant_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
......
test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_det/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_server_v2.0_det model_name:ch_ppocr_server_v2_0_det
python:python3.7 python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1 gpu_list:192.168.0.1,192.168.0.2;0,1
Global.use_gpu:True Global.use_gpu:True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ ...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
quant_train:null quant_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
......
test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_server_v2.0_det model_name:ch_ppocr_server_v2_0_det
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ ...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
quant_train:null quant_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_det/det_r50_vd_db.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
......
test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_rec/model_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================cpp_infer_params=========================== ===========================cpp_infer_params===========================
model_name:ch_ppocr_server_v2.0_rec model_name:ch_ppocr_server_v2_0_rec
use_opencv:True use_opencv:True
infer_model:./inference/ch_ppocr_server_v2.0_rec_infer/ infer_model:./inference/ch_ppocr_server_v2.0_rec_infer/
infer_quant:False infer_quant:False
......
test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_rec/model_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
浏览文件 @ 6fe01d43
===========================paddle2onnx_params=========================== ===========================paddle2onnx_params===========================
model_name:ch_ppocr_server_v2.0_rec model_name:ch_ppocr_server_v2_0_rec
python:python3.7 python:python3.7
2onnx: paddle2onnx 2onnx: paddle2onnx
--det_model_dir: --det_model_dir:
......
test_tipc/configs/ch_ppocr_server_v2.0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_rec/model_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================serving_params=========================== ===========================serving_params===========================
model_name:ch_ppocr_server_v2.0_rec model_name:ch_ppocr_server_v2_0_rec
python:python3.7 python:python3.7
trans_model:-m paddle_serving_client.convert trans_model:-m paddle_serving_client.convert
--det_dirname:null --det_dirname:null
......
test_tipc/configs/ch_ppocr_server_v2.0_rec/train_infer_python.txt → test_tipc/configs/ch_ppocr_server_v2_0_rec/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_server_v2.0_rec model_name:ch_ppocr_server_v2_0_rec
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o Global.print_batch_step=4 Train.loader.shuffle=false norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o Global.print_batch_step=4 Train.loader.shuffle=false
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/ch_ppocr_server_v2.0_rec_train/best_accuracy train_model:./inference/ch_ppocr_server_v2.0_rec_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py inference:tools/infer/predict_rec.py
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_rec/train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_server_v2.0_rec model_name:ch_ppocr_server_v2_0_rec
python:python3.7 python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1 gpu_list:192.168.0.1,192.168.0.2;0,1
Global.use_gpu:True Global.use_gpu:True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/ch_ppocr_server_v2.0_rec_train/best_accuracy train_model:./inference/ch_ppocr_server_v2.0_rec_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py inference:tools/infer/predict_rec.py
--use_gpu:False --use_gpu:False
......
test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt → test_tipc/configs/ch_ppocr_server_v2_0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:ch_ppocr_server_v2.0_rec model_name:ch_ppocr_server_v2_0_rec
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/ch_ppocr_server_v2.0_rec_train/best_accuracy train_model:./inference/ch_ppocr_server_v2.0_rec_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2_0_rec/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py inference:tools/infer/predict_rec.py
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/det_mv3_east_v2.0/train_infer_python.txt → test_tipc/configs/det_mv3_east_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:det_mv3_east_v2.0 model_name:det_mv3_east_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ ...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/det_mv3_east_v2.0/det_mv3_east.yml -o norm_train:tools/train.py -c test_tipc/configs/det_mv3_east_v2_0/det_mv3_east.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -27,7 +27,7 @@ null:null ...@@ -27,7 +27,7 @@ null:null
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/det_mv3_east_v2.0/det_mv3_east.yml -o norm_export:tools/export_model.py -c test_tipc/configs/det_mv3_east_v2_0/det_mv3_east.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/det_mv3_east_v2.0_train/best_accuracy train_model:./inference/det_mv3_east_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/det_mv3_east_v2.0/det_mv3_east.yml -o infer_export:tools/export_model.py -c test_tipc/configs/det_mv3_east_v2_0/det_mv3_east.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_det.py inference:tools/infer/predict_det.py
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/det_mv3_pse_v2.0/train_infer_python.txt → test_tipc/configs/det_mv3_pse_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:det_mv3_pse_v2.0 model_name:det_mv3_pse_v2_0
python:python3.7 python:python3.7
gpu_list:0 gpu_list:0
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ ...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/det_mv3_pse_v2.0/det_mv3_pse.yml -o norm_train:tools/train.py -c test_tipc/configs/det_mv3_pse_v2_0/det_mv3_pse.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -27,7 +27,7 @@ null:null ...@@ -27,7 +27,7 @@ null:null
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/det_mv3_pse_v2.0/det_mv3_pse.yml -o norm_export:tools/export_model.py -c test_tipc/configs/det_mv3_pse_v2_0/det_mv3_pse.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/det_mv3_pse_v2.0_train/best_accuracy train_model:./inference/det_mv3_pse_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/det_mv3_pse_v2.0/det_mv3_pse.yml -o infer_export:tools/export_model.py -c test_tipc/configs/det_mv3_pse_v2_0/det_mv3_pse.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_det.py inference:tools/infer/predict_det.py
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/det_r50_db_v2.0/train_infer_python.txt → test_tipc/configs/det_r50_db_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:det_r50_db_v2.0 model_name:det_r50_db_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
......
test_tipc/configs/det_r50_dcn_fce_ctw_v2.0/train_infer_python.txt → test_tipc/configs/det_r50_dcn_fce_ctw_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:det_r50_dcn_fce_ctw_v2.0 model_name:det_r50_dcn_fce_ctw_v2_0
python:python3.7 python:python3.7
gpu_list:0 gpu_list:0
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ ...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/det_r50_dcn_fce_ctw_v2.0/det_r50_vd_dcn_fce_ctw.yml -o Global.print_batch_step=1 Train.loader.shuffle=false norm_train:tools/train.py -c test_tipc/configs/det_r50_dcn_fce_ctw_v2_0/det_r50_vd_dcn_fce_ctw.yml -o Global.print_batch_step=1 Train.loader.shuffle=false
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -27,7 +27,7 @@ null:null ...@@ -27,7 +27,7 @@ null:null
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/det_r50_dcn_fce_ctw_v2.0/det_r50_vd_dcn_fce_ctw.yml -o norm_export:tools/export_model.py -c test_tipc/configs/det_r50_dcn_fce_ctw_v2_0/det_r50_vd_dcn_fce_ctw.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/det_r50_dcn_fce_ctw_v2.0_train/best_accuracy train_model:./inference/det_r50_dcn_fce_ctw_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/det_r50_dcn_fce_ctw_v2.0/det_r50_vd_dcn_fce_ctw.yml -o infer_export:tools/export_model.py -c test_tipc/configs/det_r50_dcn_fce_ctw_v2_0/det_r50_vd_dcn_fce_ctw.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_det.py inference:tools/infer/predict_det.py
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/train_infer_python.txt → test_tipc/configs/det_r50_vd_sast_icdar15_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:det_r50_vd_sast_icdar15_v2.0 model_name:det_r50_vd_sast_icdar15_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ ...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml -o norm_train:tools/train.py -c test_tipc/configs/det_r50_vd_sast_icdar15_v2_0/det_r50_vd_sast_icdar2015.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -27,7 +27,7 @@ null:null ...@@ -27,7 +27,7 @@ null:null
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml -o norm_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_icdar15_v2_0/det_r50_vd_sast_icdar2015.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
inference_dir:null inference_dir:null
train_model:./inference/det_r50_vd_sast_icdar15_v2.0_train/best_accuracy train_model:./inference/det_r50_vd_sast_icdar15_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml -o infer_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_icdar15_v2_0/det_r50_vd_sast_icdar2015.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_det.py inference:tools/infer/predict_det.py
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/train_infer_python.txt → test_tipc/configs/det_r50_vd_sast_totaltext_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:det_r50_vd_sast_totaltext_v2.0 model_name:det_r50_vd_sast_totaltext_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/ ...@@ -13,7 +13,7 @@ train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/det_r50_vd_sast_totaltext.yml -o Global.pretrained_model=./pretrain_models/ResNet50_vd_ssld_pretrained norm_train:tools/train.py -c test_tipc/configs/det_r50_vd_sast_totaltext_v2_0/det_r50_vd_sast_totaltext.yml -o Global.pretrained_model=./pretrain_models/ResNet50_vd_ssld_pretrained
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -27,7 +27,7 @@ null:null ...@@ -27,7 +27,7 @@ null:null
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/det_r50_vd_sast_totaltext.yml -o norm_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_totaltext_v2_0/det_r50_vd_sast_totaltext.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
inference_dir:null inference_dir:null
train_model:./inference/det_r50_vd_sast_totaltext_v2.0_train/best_accuracy train_model:./inference/det_r50_vd_sast_totaltext_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/det_r50_vd_sast_totaltext.yml -o infer_export:tools/export_model.py -c test_tipc/configs/det_r50_vd_sast_totaltext_v2_0/det_r50_vd_sast_totaltext.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_det.py inference:tools/infer/predict_det.py
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/layoutxlm_ser/train_infer_python.txt 0 → 100644
浏览文件 @ 6fe01d43
===========================train_params===========================
model_name:layoutxlm_ser
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:fp32
Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=17
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=8|whole_train_whole_infer=8
Architecture.Backbone.checkpoints:null
train_model_name:latest
train_infer_img_dir:ppstructure/docs/vqa/input/zh_val_42.jpg
null:null
##
trainer:norm_train
norm_train:tools/train.py -c configs/vqa/ser/layoutxlm_xfund_zh.yml -o Global.print_batch_step=1 Global.eval_batch_step=[1000,1000] Train.loader.shuffle=false
pact_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:null
null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Architecture.Backbone.checkpoints:
norm_export:tools/export_model.py -c configs/vqa/ser/layoutxlm_xfund_zh.yml -o
quant_export:
fpgm_export:
distill_export:null
export1:null
export2:null
##
infer_model:null
infer_export:null
infer_quant:False
inference:ppstructure/vqa/predict_vqa_token_ser.py --vqa_algorithm=LayoutXLM --ser_dict_path=train_data/XFUND/class_list_xfun.txt --output=output
--use_gpu:True|False
--enable_mkldnn:False
--cpu_threads:6
--rec_batch_num:1
--use_tensorrt:False
--precision:fp32
--ser_model_dir:
--image_dir:./ppstructure/docs/vqa/input/zh_val_42.jpg
null:null
--benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,224,224]}]
===========================train_benchmark_params==========================
batch_size:4
fp_items:fp32|fp16
epoch:3
--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98
test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/train_infer_python.txt → test_tipc/configs/rec_mv3_none_bilstm_ctc_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_mv3_none_bilstm_ctc_v2.0 model_name:rec_mv3_none_bilstm_ctc_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/rec_icdar15_train.yml -o Global.print_batch_step=4 Train.loader.shuffle=false norm_train:tools/train.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_v2_0/rec_icdar15_train.yml -o Global.print_batch_step=4 Train.loader.shuffle=false
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/rec_mv3_none_bilstm_ctc_v2.0_train/best_accuracy train_model:./inference/rec_mv3_none_bilstm_ctc_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_v2.0/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100"
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/rec_mv3_none_none_ctc_v2.0/train_infer_python.txt → test_tipc/configs/rec_mv3_none_none_ctc_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_mv3_none_none_ctc_v2.0 model_name:rec_mv3_none_none_ctc_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2.0/rec_icdar15_train.yml -o norm_train:tools/train.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2_0/rec_icdar15_train.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2.0/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2_0/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2.0/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2_0/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/rec_mv3_none_none_ctc_v2.0_train/best_accuracy train_model:./inference/rec_mv3_none_none_ctc_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2.0/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_none_none_ctc_v2_0/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100"
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/train_infer_python.txt → test_tipc/configs/rec_mv3_tps_bilstm_att_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_mv3_tps_bilstm_att_v2.0 model_name:rec_mv3_tps_bilstm_att_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/rec_mv3_tps_bilstm_att.yml -o norm_train:tools/train.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v2_0/rec_mv3_tps_bilstm_att.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/rec_mv3_tps_bilstm_att.yml -o eval:tools/eval.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v2_0/rec_mv3_tps_bilstm_att.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/rec_mv3_tps_bilstm_att.yml -o norm_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v2_0/rec_mv3_tps_bilstm_att.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/rec_mv3_tps_bilstm_att_v2.0_train/best_accuracy train_model:./inference/rec_mv3_tps_bilstm_att_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v2.0/rec_mv3_tps_bilstm_att.yml -o infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_att_v2_0/rec_mv3_tps_bilstm_att.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="RARE" --min_subgraph_size=5 inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="RARE" --min_subgraph_size=5
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/train_infer_python.txt → test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_mv3_tps_bilstm_ctc_v2.0 model_name:rec_mv3_tps_bilstm_ctc_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/rec_icdar15_train.yml -o norm_train:tools/train.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/rec_mv3_tps_bilstm_ctc_v2.0_train/best_accuracy train_model:./inference/rec_mv3_tps_bilstm_ctc_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2.0/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/rec_mv3_tps_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="StarNet" inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="StarNet"
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/rec_r32_gaspin_bilstm_att/rec_r32_gaspin_bilstm_att.yml
浏览文件 @ 6fe01d43
...@@ -8,7 +8,7 @@ Global: ...@@ -8,7 +8,7 @@ Global:
# evaluation is run every 5000 iterations after the 4000th iteration # evaluation is run every 5000 iterations after the 4000th iteration
eval_batch_step: [0, 2000] eval_batch_step: [0, 2000]
cal_metric_during_train: True cal_metric_during_train: True
pretrained_model: pretrained_model: pretrain_models/rec_r32_gaspin_bilstm_att_train/best_accuracy
checkpoints: checkpoints:
save_inference_dir: save_inference_dir:
use_visualdl: False use_visualdl: False
......
test_tipc/configs/rec_r32_gaspin_bilstm_att/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_r32_gaspin_bilstm_att model_name:rec_r32_gaspin_bilstm_att
python:python python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
Global.auto_cast:null Global.auto_cast:null
...@@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_r32_gaspin_bilstm_at ...@@ -39,11 +39,11 @@ infer_export:tools/export_model.py -c test_tipc/configs/rec_r32_gaspin_bilstm_at
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/dict/spin_dict.txt --use_space_char=False --rec_image_shape="3,32,100" --rec_algorithm="SPIN" inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/dict/spin_dict.txt --use_space_char=False --rec_image_shape="3,32,100" --rec_algorithm="SPIN"
--use_gpu:True|False --use_gpu:True|False
--enable_mkldnn:True|False --enable_mkldnn:False
--cpu_threads:1|6 --cpu_threads:6
--rec_batch_num:1|6 --rec_batch_num:1|6
--use_tensorrt:False|False --use_tensorrt:False
--precision:fp32|int8 --precision:fp32
--rec_model_dir: --rec_model_dir:
--image_dir:./inference/rec_inference --image_dir:./inference/rec_inference
--save_log_path:./test/output/ --save_log_path:./test/output/
......
test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/train_infer_python.txt → test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_r34_vd_none_bilstm_ctc_v2.0 model_name:rec_r34_vd_none_bilstm_ctc_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/rec_icdar15_train.yml -o norm_train:tools/train.py -c test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/rec_r34_vd_none_bilstm_ctc_v2.0_train/best_accuracy train_model:./inference/rec_r34_vd_none_bilstm_ctc_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2.0/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100"
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/train_infer_python.txt → test_tipc/configs/rec_r34_vd_none_none_ctc_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_r34_vd_none_none_ctc_v2.0 model_name:rec_r34_vd_none_none_ctc_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/rec_icdar15_train.yml -o norm_train:tools/train.py -c test_tipc/configs/rec_r34_vd_none_none_ctc_v2_0/rec_icdar15_train.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/rec_r34_vd_none_none_ctc_v2_0/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_none_ctc_v2_0/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/rec_r34_vd_none_none_ctc_v2.0_train/best_accuracy train_model:./inference/rec_r34_vd_none_none_ctc_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_none_ctc_v2.0/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_none_none_ctc_v2_0/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100"
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/train_infer_python.txt → test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_r34_vd_tps_bilstm_att_v2.0 model_name:rec_r34_vd_tps_bilstm_att_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/rec_r34_vd_tps_bilstm_att.yml -o norm_train:tools/train.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2_0/rec_r34_vd_tps_bilstm_att.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/rec_r34_vd_tps_bilstm_att.yml -o eval:tools/eval.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2_0/rec_r34_vd_tps_bilstm_att.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/rec_r34_vd_tps_bilstm_att.yml -o norm_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2_0/rec_r34_vd_tps_bilstm_att.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/rec_r34_vd_tps_bilstm_att_v2.0_train/best_accuracy train_model:./inference/rec_r34_vd_tps_bilstm_att_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2.0/rec_r34_vd_tps_bilstm_att.yml -o infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_att_v2_0/rec_r34_vd_tps_bilstm_att.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="RARE" --min_subgraph_size=5 inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="RARE" --min_subgraph_size=5
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/train_infer_python.txt → test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2_0/train_infer_python.txt
浏览文件 @ 6fe01d43
===========================train_params=========================== ===========================train_params===========================
model_name:rec_r34_vd_tps_bilstm_ctc_v2.0 model_name:rec_r34_vd_tps_bilstm_ctc_v2_0
python:python3.7 python:python3.7
gpu_list:0|0,1 gpu_list:0|0,1
Global.use_gpu:True|True Global.use_gpu:True|True
...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference ...@@ -13,7 +13,7 @@ train_infer_img_dir:./inference/rec_inference
null:null null:null
## ##
trainer:norm_train trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/rec_icdar15_train.yml -o norm_train:tools/train.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
pact_train:null pact_train:null
fpgm_train:null fpgm_train:null
distill_train:null distill_train:null
...@@ -21,13 +21,13 @@ null:null ...@@ -21,13 +21,13 @@ null:null
null:null null:null
## ##
===========================eval_params=========================== ===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/rec_icdar15_train.yml -o eval:tools/eval.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
null:null null:null
## ##
===========================infer_params=========================== ===========================infer_params===========================
Global.save_inference_dir:./output/ Global.save_inference_dir:./output/
Global.checkpoints: Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/rec_icdar15_train.yml -o norm_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
quant_export:null quant_export:null
fpgm_export:null fpgm_export:null
distill_export:null distill_export:null
...@@ -35,7 +35,7 @@ export1:null ...@@ -35,7 +35,7 @@ export1:null
export2:null export2:null
## ##
train_model:./inference/rec_r34_vd_tps_bilstm_ctc_v2.0_train/best_accuracy train_model:./inference/rec_r34_vd_tps_bilstm_ctc_v2.0_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2.0/rec_icdar15_train.yml -o infer_export:tools/export_model.py -c test_tipc/configs/rec_r34_vd_tps_bilstm_ctc_v2_0/rec_icdar15_train.yml -o
infer_quant:False infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="StarNet" inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100" --rec_algorithm="StarNet"
--use_gpu:True|False --use_gpu:True|False
......
test_tipc/docs/benchmark_train.md
浏览文件 @ 6fe01d43
...@@ -69,7 +69,8 @@ train_log/ ...@@ -69,7 +69,8 @@ train_log/
| det_r50_vd_east_v2.0 |[config](../configs/det_r50_vd_east_v2.0/train_infer_python.txt) | 42.485 | 42.624 / 42.663 / 42.561 |0.00239083 | 67.61 |67.825/ 68.299/ 68.51| 0.00999854 | 10,000| 2,000| | det_r50_vd_east_v2.0 |[config](../configs/det_r50_vd_east_v2.0/train_infer_python.txt) | 42.485 | 42.624 / 42.663 / 42.561 |0.00239083 | 67.61 |67.825/ 68.299/ 68.51| 0.00999854 | 10,000| 2,000|
| det_r50_vd_pse_v2.0 |[config](../configs/det_r50_vd_pse_v2.0/train_infer_python.txt) | 16.455 | 16.517 / 16.555 / 16.353 |0.012201752 | 27.02 |27.288 / 27.152 / 27.408| 0.009340339 | 10,000| 2,000| | det_r50_vd_pse_v2.0 |[config](../configs/det_r50_vd_pse_v2.0/train_infer_python.txt) | 16.455 | 16.517 / 16.555 / 16.353 |0.012201752 | 27.02 |27.288 / 27.152 / 27.408| 0.009340339 | 10,000| 2,000|
| rec_mv3_none_bilstm_ctc_v2.0 |[config](../configs/rec_mv3_none_bilstm_ctc_v2.0/train_infer_python.txt) | 2288.358 | 2291.906 / 2293.725 / 2290.05 |0.001602197 | 2336.17 |2327.042 / 2328.093 / 2344.915| 0.007622025 | 600,000| 160,000| | rec_mv3_none_bilstm_ctc_v2.0 |[config](../configs/rec_mv3_none_bilstm_ctc_v2.0/train_infer_python.txt) | 2288.358 | 2291.906 / 2293.725 / 2290.05 |0.001602197 | 2336.17 |2327.042 / 2328.093 / 2344.915| 0.007622025 | 600,000| 160,000|
| layoutxlm_ser |[config](../configs/layoutxlm/train_infer_python.txt) | 18.001 | 18.114 / 18.107 / 18.307 |0.010924783 | 21.982 | 21.507 / 21.116 / 21.406| 0.018180127 | 1490 | 1490|
| PP-Structure-table |[config](../configs/en_table_structure/train_infer_python.txt) | 14.151 | 14.077 / 14.23 / 14.25 |0.012140351 | 16.285 | 16.595 / 16.878 / 16.531 | 0.020559308 | 20,000| 5,000| | PP-Structure-table |[config](../configs/en_table_structure/train_infer_python.txt) | 14.151 | 14.077 / 14.23 / 14.25 |0.012140351 | 16.285 | 16.595 / 16.878 / 16.531 | 0.020559308 | 20,000| 5,000|
| det_r50_dcn_fce_ctw_v2.0 |[config](../configs/det_r50_dcn_fce_ctw_v2.0/train_infer_python.txt) | 14.057 | 14.029 / 14.02 / 14.014 |0.001069214 | 18.298 |18.411 / 18.376 / 18.331| 0.004345228 | 10,000| 2,000| | det_r50_dcn_fce_ctw_v2.0 |[config](../configs/det_r50_dcn_fce_ctw_v2.0/train_infer_python.txt) | 14.057 | 14.029 / 14.02 / 14.014 |0.001069214 | 18.298 |18.411 / 18.376 / 18.331| 0.004345228 | 10,000| 2,000|
| ch_PP-OCRv3_det |[config](../configs/ch_PP-OCRv3_det/train_infer_python.txt) | 8.622 | 8.431 / 8.423 / 8.479|0.006604552 | 14.203 |14.346 14.468 14.23| 0.016450097 | 10,000| 2,000| | ch_PP-OCRv3_det |[config](../configs/ch_PP-OCRv3_det/train_infer_python.txt) | 8.622 | 8.431 / 8.423 / 8.479|0.006604552 | 14.203 |14.346 14.468 14.23| 0.016450097 | 10,000| 2,000|
| ch_PP-OCRv3_rec |[config](../configs/ch_PP-OCRv3_rec/train_infer_python.txt) | 73.627 | 72.46 / 73.575 / 73.704|0.016878324 | | | | 160,000| 40,000| | ch_PP-OCRv3_rec |[config](../configs/ch_PP-OCRv3_rec/train_infer_python.txt) | 90.239 | 90.077 / 91.513 / 91.325|0.01569176 | | | | 160,000| 40,000|
\ No newline at end of file
test_tipc/prepare.sh
浏览文件 @ 6fe01d43
...@@ -22,7 +22,7 @@ trainer_list=$(func_parser_value "${lines[14]}") ...@@ -22,7 +22,7 @@ trainer_list=$(func_parser_value "${lines[14]}")
if [ ${MODE} = "benchmark_train" ];then if [ ${MODE} = "benchmark_train" ];then
pip install -r requirements.txt pip install -r requirements.txt
if [[ ${model_name} =~ "ch_ppocr_mobile_v2.0_det" || ${model_name} =~ "det_mv3_db_v2_0" ]];then if [[ ${model_name} =~ "ch_ppocr_mobile_v2_0_det" || ${model_name} =~ "det_mv3_db_v2_0" ]];then
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate
rm -rf ./train_data/icdar2015 rm -rf ./train_data/icdar2015
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/icdar2015_benckmark.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/icdar2015_benckmark.tar --no-check-certificate
...@@ -30,7 +30,7 @@ if [ ${MODE} = "benchmark_train" ];then ...@@ -30,7 +30,7 @@ if [ ${MODE} = "benchmark_train" ];then
ln -s ./icdar2015_benckmark ./icdar2015 ln -s ./icdar2015_benckmark ./icdar2015
cd ../ cd ../
fi fi
if [[ ${model_name} =~ "ch_ppocr_server_v2.0_det" || ${model_name} =~ "ch_PP-OCRv3_det" ]];then if [[ ${model_name} =~ "ch_ppocr_server_v2_0_det" || ${model_name} =~ "ch_PP-OCRv3_det" ]];then
rm -rf ./train_data/icdar2015 rm -rf ./train_data/icdar2015
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/icdar2015_benckmark.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/icdar2015_benckmark.tar --no-check-certificate
cd ./train_data/ && tar xf icdar2015_benckmark.tar cd ./train_data/ && tar xf icdar2015_benckmark.tar
...@@ -55,7 +55,7 @@ if [ ${MODE} = "benchmark_train" ];then ...@@ -55,7 +55,7 @@ if [ ${MODE} = "benchmark_train" ];then
ln -s ./icdar2015_benckmark ./icdar2015 ln -s ./icdar2015_benckmark ./icdar2015
cd ../ cd ../
fi fi
if [[ ${model_name} =~ "det_r50_db_v2.0" || ${model_name} =~ "det_r50_vd_pse_v2_0" ]];then if [[ ${model_name} =~ "det_r50_db_v2_0" || ${model_name} =~ "det_r50_vd_pse_v2_0" ]];then
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate
rm -rf ./train_data/icdar2015 rm -rf ./train_data/icdar2015
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/icdar2015_benckmark.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/icdar2015_benckmark.tar --no-check-certificate
...@@ -71,11 +71,21 @@ if [ ${MODE} = "benchmark_train" ];then ...@@ -71,11 +71,21 @@ if [ ${MODE} = "benchmark_train" ];then
ln -s ./icdar2015_benckmark ./icdar2015 ln -s ./icdar2015_benckmark ./icdar2015
cd ../ cd ../
fi fi
if [[ ${model_name} =~ "ch_ppocr_mobile_v2.0_rec" || ${model_name} =~ "ch_ppocr_server_v2.0_rec" || ${model_name} =~ "ch_PP-OCRv2_rec" || ${model_name} =~ "rec_mv3_none_bilstm_ctc_v2.0" || ${model_name} =~ "ch_PP-OCRv3_rec" ]];then if [[ ${model_name} =~ "ch_ppocr_mobile_v2_0_rec" || ${model_name} =~ "ch_ppocr_server_v2_0_rec" || ${model_name} =~ "ch_PP-OCRv2_rec" || ${model_name} =~ "rec_mv3_none_bilstm_ctc_v2_0" || ${model_name} =~ "ch_PP-OCRv3_rec" ]];then
rm -rf ./train_data/ic15_data_benckmark rm -rf ./train_data/ic15_data
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/ic15_data_benckmark.tar --no-check-certificate
cd ./train_data/ && tar xf ic15_data_benckmark.tar
ln -s ./ic15_data_benckmark ./ic15_data
cd ../
fi
if [[ ${model_name} =~ "ch_PP-OCRv2_rec" || ${model_name} =~ "ch_PP-OCRv3_rec" ]];then
rm -rf ./train_data/ic15_data
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/ic15_data_benckmark.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/ic15_data_benckmark.tar --no-check-certificate
cd ./train_data/ && tar xf ic15_data_benckmark.tar cd ./train_data/ && tar xf ic15_data_benckmark.tar
ln -s ./ic15_data_benckmark ./ic15_data ln -s ./ic15_data_benckmark ./ic15_data
cd ic15_data
mv rec_gt_train4w.txt rec_gt_train.txt
cd ../
cd ../ cd ../
fi fi
if [[ ${model_name} == "en_table_structure" ]];then if [[ ${model_name} == "en_table_structure" ]];then
...@@ -87,7 +97,7 @@ if [ ${MODE} = "benchmark_train" ];then ...@@ -87,7 +97,7 @@ if [ ${MODE} = "benchmark_train" ];then
ln -s ./pubtabnet_benckmark ./pubtabnet ln -s ./pubtabnet_benckmark ./pubtabnet
cd ../ cd ../
fi fi
if [[ ${model_name} == "det_r50_dcn_fce_ctw_v2.0" ]]; then if [[ ${model_name} == "det_r50_dcn_fce_ctw_v2_0" ]]; then
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/contribution/det_r50_dcn_fce_ctw_v2.0_train.tar --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/contribution/det_r50_dcn_fce_ctw_v2.0_train.tar --no-check-certificate
cd ./pretrain_models/ && tar xf det_r50_dcn_fce_ctw_v2.0_train.tar && cd ../ cd ./pretrain_models/ && tar xf det_r50_dcn_fce_ctw_v2.0_train.tar && cd ../
rm -rf ./train_data/icdar2015 rm -rf ./train_data/icdar2015
...@@ -96,6 +106,19 @@ if [ ${MODE} = "benchmark_train" ];then ...@@ -96,6 +106,19 @@ if [ ${MODE} = "benchmark_train" ];then
ln -s ./icdar2015_benckmark ./icdar2015 ln -s ./icdar2015_benckmark ./icdar2015
cd ../ cd ../
fi fi
if [ ${model_name} == "layoutxlm_ser" ]; then
pip install -r ppstructure/vqa/requirements.txt
pip install paddlenlp\>=2.3.5 --force-reinstall
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/ppstructure/dataset/XFUND.tar --no-check-certificate
cd ./train_data/ && tar xf XFUND.tar
# expand gt.txt 10 times
cd XFUND/zh_train
for i in `seq 10`;do cp train.json dup$i.txt;done
cat dup* > train.json && rm -rf dup*
cd ../../
cd ../
fi
fi fi
if [ ${MODE} = "lite_train_lite_infer" ];then if [ ${MODE} = "lite_train_lite_infer" ];then
...@@ -161,7 +184,7 @@ if [ ${MODE} = "lite_train_lite_infer" ];then ...@@ -161,7 +184,7 @@ if [ ${MODE} = "lite_train_lite_infer" ];then
cd ./pretrain_models/ && tar xf en_server_pgnetA.tar && cd ../ cd ./pretrain_models/ && tar xf en_server_pgnetA.tar && cd ../
cd ./train_data && tar xf total_text_lite.tar && ln -s total_text_lite total_text && cd ../ cd ./train_data && tar xf total_text_lite.tar && ln -s total_text_lite total_text && cd ../
fi fi
if [ ${model_name} == "det_r50_vd_sast_icdar15_v2.0" ] || [ ${model_name} == "det_r50_vd_sast_totaltext_v2.0" ]; then if [ ${model_name} == "det_r50_vd_sast_icdar15_v2_0" ] || [ ${model_name} == "det_r50_vd_sast_totaltext_v2_0" ]; then
wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar --no-check-certificate
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate
...@@ -172,16 +195,16 @@ if [ ${MODE} = "lite_train_lite_infer" ];then ...@@ -172,16 +195,16 @@ if [ ${MODE} = "lite_train_lite_infer" ];then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_mv3_db_v2.0_train.tar && cd ../ cd ./inference/ && tar xf det_mv3_db_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "det_r50_db_v2.0" ]; then if [ ${model_name} == "det_r50_db_v2_0" ]; then
wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_r50_vd_db_v2.0_train.tar && cd ../ cd ./inference/ && tar xf det_r50_vd_db_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "ch_ppocr_mobile_v2.0_rec_FPGM" ]; then if [ ${model_name} == "ch_ppocr_mobile_v2_0_rec_FPGM" ]; then
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar --no-check-certificate
cd ./pretrain_models/ && tar xf ch_ppocr_mobile_v2.0_rec_train.tar && cd ../ cd ./pretrain_models/ && tar xf ch_ppocr_mobile_v2.0_rec_train.tar && cd ../
fi fi
if [ ${model_name} == "det_mv3_east_v2.0" ]; then if [ ${model_name} == "det_mv3_east_v2_0" ]; then
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar --no-check-certificate
cd ./pretrain_models/ && tar xf det_mv3_east_v2.0_train.tar && cd ../ cd ./pretrain_models/ && tar xf det_mv3_east_v2.0_train.tar && cd ../
fi fi
...@@ -189,10 +212,21 @@ if [ ${MODE} = "lite_train_lite_infer" ];then ...@@ -189,10 +212,21 @@ if [ ${MODE} = "lite_train_lite_infer" ];then
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar --no-check-certificate
cd ./pretrain_models/ && tar xf det_r50_vd_east_v2.0_train.tar && cd ../ cd ./pretrain_models/ && tar xf det_r50_vd_east_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "det_r50_dcn_fce_ctw_v2.0" ]; then if [ ${model_name} == "det_r50_dcn_fce_ctw_v2_0" ]; then
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/contribution/det_r50_dcn_fce_ctw_v2.0_train.tar --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/contribution/det_r50_dcn_fce_ctw_v2.0_train.tar --no-check-certificate
cd ./pretrain_models/ && tar xf det_r50_dcn_fce_ctw_v2.0_train.tar & cd ../ cd ./pretrain_models/ && tar xf det_r50_dcn_fce_ctw_v2.0_train.tar & cd ../
fi fi
if [ ${model_name} == "rec_r32_gaspin_bilstm_att" ]; then
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/rec_r32_gaspin_bilstm_att_train.tar --no-check-certificate
cd ./pretrain_models/ && tar xf rec_r32_gaspin_bilstm_att_train.tar && cd ../
fi
if [ ${model_name} == "layoutxlm_ser" ]; then
pip install -r ppstructure/vqa/requirements.txt
pip install paddlenlp\>=2.3.5 --force-reinstall
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/ppstructure/dataset/XFUND.tar --no-check-certificate
cd ./train_data/ && tar xf XFUND.tar
cd ../
fi
elif [ ${MODE} = "whole_train_whole_infer" ];then elif [ ${MODE} = "whole_train_whole_infer" ];then
wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate
...@@ -220,7 +254,7 @@ elif [ ${MODE} = "whole_train_whole_infer" ];then ...@@ -220,7 +254,7 @@ elif [ ${MODE} = "whole_train_whole_infer" ];then
cd ./pretrain_models/ && tar xf en_server_pgnetA.tar && cd ../ cd ./pretrain_models/ && tar xf en_server_pgnetA.tar && cd ../
cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text && cd ../ cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text && cd ../
fi fi
if [ ${model_name} == "det_r50_vd_sast_totaltext_v2.0" ]; then if [ ${model_name} == "det_r50_vd_sast_totaltext_v2_0" ]; then
wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate
cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text && cd ../ cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text && cd ../
...@@ -264,32 +298,32 @@ elif [ ${MODE} = "whole_infer" ];then ...@@ -264,32 +298,32 @@ elif [ ${MODE} = "whole_infer" ];then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate
cd ./inference && tar xf rec_inference.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf rec_inference.tar && tar xf ch_det_data_50.tar && cd ../
if [ ${model_name} = "ch_ppocr_mobile_v2.0_det" ]; then if [ ${model_name} = "ch_ppocr_mobile_v2_0_det" ]; then
eval_model_name="ch_ppocr_mobile_v2.0_det_train" eval_model_name="ch_ppocr_mobile_v2.0_det_train"
rm -rf ./train_data/icdar2015 rm -rf ./train_data/icdar2015
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && cd ../ cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0_det_PACT" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0_det_PACT" ]; then
eval_model_name="ch_ppocr_mobile_v2.0_det_prune_infer" eval_model_name="ch_ppocr_mobile_v2.0_det_prune_infer"
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_infer.tar --no-check-certificate
cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_server_v2.0_det" ]; then elif [ ${model_name} = "ch_ppocr_server_v2_0_det" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_server_v2.0_det_train.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_server_v2.0_det_train.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_server_v2.0" ]; then elif [ ${model_name} = "ch_ppocr_server_v2_0" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec_PACT" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0_rec_PACT" ]; then
eval_model_name="ch_ppocr_mobile_v2.0_rec_slim_infer" eval_model_name="ch_ppocr_mobile_v2.0_rec_slim_infer"
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_slim_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_slim_infer.tar --no-check-certificate
cd ./inference && tar xf ${eval_model_name}.tar && cd ../ cd ./inference && tar xf ${eval_model_name}.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec_FPGM" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0_rec_FPGM" ]; then
eval_model_name="ch_PP-OCRv2_rec_infer" eval_model_name="ch_PP-OCRv2_rec_infer"
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ${eval_model_name}.tar && cd ../ cd ./inference && tar xf ${eval_model_name}.tar && cd ../
...@@ -334,39 +368,39 @@ elif [ ${MODE} = "whole_infer" ];then ...@@ -334,39 +368,39 @@ elif [ ${MODE} = "whole_infer" ];then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar --no-check-certificate
cd ./inference && tar xf en_server_pgnetA.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf en_server_pgnetA.tar && tar xf ch_det_data_50.tar && cd ../
fi fi
if [ ${model_name} == "det_r50_vd_sast_icdar15_v2.0" ]; then if [ ${model_name} == "det_r50_vd_sast_icdar15_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_icdar15_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_r50_vd_sast_icdar15_v2.0_train.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference/ && tar xf det_r50_vd_sast_icdar15_v2.0_train.tar && tar xf ch_det_data_50.tar && cd ../
fi fi
if [ ${model_name} == "rec_mv3_none_none_ctc_v2.0" ]; then if [ ${model_name} == "rec_mv3_none_none_ctc_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_none_ctc_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_none_ctc_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_mv3_none_none_ctc_v2.0_train.tar && cd ../ cd ./inference/ && tar xf rec_mv3_none_none_ctc_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "rec_r34_vd_none_none_ctc_v2.0" ]; then if [ ${model_name} == "rec_r34_vd_none_none_ctc_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_none_ctc_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_none_ctc_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_r34_vd_none_none_ctc_v2.0_train.tar && cd ../ cd ./inference/ && tar xf rec_r34_vd_none_none_ctc_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "rec_mv3_none_bilstm_ctc_v2.0" ]; then if [ ${model_name} == "rec_mv3_none_bilstm_ctc_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_bilstm_ctc_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_bilstm_ctc_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_mv3_none_bilstm_ctc_v2.0_train.tar && cd ../ cd ./inference/ && tar xf rec_mv3_none_bilstm_ctc_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "rec_r34_vd_none_bilstm_ctc_v2.0" ]; then if [ ${model_name} == "rec_r34_vd_none_bilstm_ctc_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_bilstm_ctc_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_none_bilstm_ctc_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_r34_vd_none_bilstm_ctc_v2.0_train.tar && cd ../ cd ./inference/ && tar xf rec_r34_vd_none_bilstm_ctc_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "rec_mv3_tps_bilstm_ctc_v2.0" ]; then if [ ${model_name} == "rec_mv3_tps_bilstm_ctc_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_ctc_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_ctc_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_mv3_tps_bilstm_ctc_v2.0_train.tar && cd ../ cd ./inference/ && tar xf rec_mv3_tps_bilstm_ctc_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "rec_r34_vd_tps_bilstm_ctc_v2.0" ]; then if [ ${model_name} == "rec_r34_vd_tps_bilstm_ctc_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar && cd ../ cd ./inference/ && tar xf rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "ch_ppocr_server_v2.0_rec" ]; then if [ ${model_name} == "ch_ppocr_server_v2_0_rec" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_train.tar --no-check-certificate
cd ./inference/ && tar xf ch_ppocr_server_v2.0_rec_train.tar && cd ../ cd ./inference/ && tar xf ch_ppocr_server_v2.0_rec_train.tar && cd ../
fi fi
if [ ${model_name} == "ch_ppocr_mobile_v2.0_rec" ]; then if [ ${model_name} == "ch_ppocr_mobile_v2_0_rec" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar --no-check-certificate
cd ./inference/ && tar xf ch_ppocr_mobile_v2.0_rec_train.tar && cd ../ cd ./inference/ && tar xf ch_ppocr_mobile_v2.0_rec_train.tar && cd ../
fi fi
...@@ -374,11 +408,11 @@ elif [ ${MODE} = "whole_infer" ];then ...@@ -374,11 +408,11 @@ elif [ ${MODE} = "whole_infer" ];then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mtb_nrtr_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mtb_nrtr_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_mtb_nrtr_train.tar && cd ../ cd ./inference/ && tar xf rec_mtb_nrtr_train.tar && cd ../
fi fi
if [ ${model_name} == "rec_mv3_tps_bilstm_att_v2.0" ]; then if [ ${model_name} == "rec_mv3_tps_bilstm_att_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_att_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_tps_bilstm_att_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_mv3_tps_bilstm_att_v2.0_train.tar && cd ../ cd ./inference/ && tar xf rec_mv3_tps_bilstm_att_v2.0_train.tar && cd ../
fi fi
if [ ${model_name} == "rec_r34_vd_tps_bilstm_att_v2.0" ]; then if [ ${model_name} == "rec_r34_vd_tps_bilstm_att_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_att_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_r34_vd_tps_bilstm_att_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf rec_r34_vd_tps_bilstm_att_v2.0_train.tar && cd ../ cd ./inference/ && tar xf rec_r34_vd_tps_bilstm_att_v2.0_train.tar && cd ../
fi fi
...@@ -391,7 +425,7 @@ elif [ ${MODE} = "whole_infer" ];then ...@@ -391,7 +425,7 @@ elif [ ${MODE} = "whole_infer" ];then
cd ./inference/ && tar xf rec_r50_vd_srn_train.tar && cd ../ cd ./inference/ && tar xf rec_r50_vd_srn_train.tar && cd ../
fi fi
if [ ${model_name} == "det_r50_vd_sast_totaltext_v2.0" ]; then if [ ${model_name} == "det_r50_vd_sast_totaltext_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_totaltext_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_sast_totaltext_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_r50_vd_sast_totaltext_v2.0_train.tar && cd ../ cd ./inference/ && tar xf det_r50_vd_sast_totaltext_v2.0_train.tar && cd ../
fi fi
...@@ -399,11 +433,11 @@ elif [ ${MODE} = "whole_infer" ];then ...@@ -399,11 +433,11 @@ elif [ ${MODE} = "whole_infer" ];then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_mv3_db_v2.0_train.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference/ && tar xf det_mv3_db_v2.0_train.tar && tar xf ch_det_data_50.tar && cd ../
fi fi
if [ ${model_name} == "det_r50_db_v2.0" ]; then if [ ${model_name} == "det_r50_db_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_db_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_r50_vd_db_v2.0_train.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference/ && tar xf det_r50_vd_db_v2.0_train.tar && tar xf ch_det_data_50.tar && cd ../
fi fi
if [ ${model_name} == "det_mv3_pse_v2.0" ]; then if [ ${model_name} == "det_mv3_pse_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_mv3_pse_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_mv3_pse_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_mv3_pse_v2.0_train.tar & cd ../ cd ./inference/ && tar xf det_mv3_pse_v2.0_train.tar & cd ../
fi fi
...@@ -411,7 +445,7 @@ elif [ ${MODE} = "whole_infer" ];then ...@@ -411,7 +445,7 @@ elif [ ${MODE} = "whole_infer" ];then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_r50_vd_pse_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/en_det/det_r50_vd_pse_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_r50_vd_pse_v2.0_train.tar & cd ../ cd ./inference/ && tar xf det_r50_vd_pse_v2.0_train.tar & cd ../
fi fi
if [ ${model_name} == "det_mv3_east_v2.0" ]; then if [ ${model_name} == "det_mv3_east_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_east_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_mv3_east_v2.0_train.tar & cd ../ cd ./inference/ && tar xf det_mv3_east_v2.0_train.tar & cd ../
fi fi
...@@ -419,7 +453,7 @@ elif [ ${MODE} = "whole_infer" ];then ...@@ -419,7 +453,7 @@ elif [ ${MODE} = "whole_infer" ];then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_r50_vd_east_v2.0_train.tar & cd ../ cd ./inference/ && tar xf det_r50_vd_east_v2.0_train.tar & cd ../
fi fi
if [ ${model_name} == "det_r50_dcn_fce_ctw_v2.0" ]; then if [ ${model_name} == "det_r50_dcn_fce_ctw_v2_0" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/contribution/det_r50_dcn_fce_ctw_v2.0_train.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/contribution/det_r50_dcn_fce_ctw_v2.0_train.tar --no-check-certificate
cd ./inference/ && tar xf det_r50_dcn_fce_ctw_v2.0_train.tar & cd ../ cd ./inference/ && tar xf det_r50_dcn_fce_ctw_v2.0_train.tar & cd ../
fi fi
...@@ -434,7 +468,7 @@ fi ...@@ -434,7 +468,7 @@ fi
if [[ ${model_name} =~ "KL" ]]; then if [[ ${model_name} =~ "KL" ]]; then
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar --no-check-certificate
cd ./train_data/ && tar xf icdar2015_lite.tar && rm -rf ./icdar2015 && ln -s ./icdar2015_lite ./icdar2015 && cd ../ cd ./train_data/ && tar xf icdar2015_lite.tar && rm -rf ./icdar2015 && ln -s ./icdar2015_lite ./icdar2015 && cd ../
if [ ${model_name} = "ch_ppocr_mobile_v2.0_det_KL" ]; then if [ ${model_name} = "ch_ppocr_mobile_v2_0_det_KL" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../
...@@ -466,7 +500,7 @@ if [[ ${model_name} =~ "KL" ]]; then ...@@ -466,7 +500,7 @@ if [[ ${model_name} =~ "KL" ]]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar --no-check-certificate
cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_PP-OCRv3_det_infer.tar && tar xf ch_det_data_50.tar && cd ../
fi fi
if [ ${model_name} = "ch_ppocr_mobile_v2.0_rec_KL" ]; then if [ ${model_name} = "ch_ppocr_mobile_v2_0_rec_KL" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate
...@@ -484,35 +518,35 @@ if [[ ${model_name} =~ "KL" ]]; then ...@@ -484,35 +518,35 @@ if [[ ${model_name} =~ "KL" ]]; then
fi fi
if [ ${MODE} = "cpp_infer" ];then if [ ${MODE} = "cpp_infer" ];then
if [ ${model_name} = "ch_ppocr_mobile_v2.0_det" ]; then if [ ${model_name} = "ch_ppocr_mobile_v2_0_det" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0_det_KL" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0_det_KL" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_klquant_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_klquant_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_klquant_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_klquant_infer.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0_det_PACT" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0_det_PACT" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_pact_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_pact_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_pact_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_pact_infer.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0_rec" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf rec_inference.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf rec_inference.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec_KL" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0_rec_KL" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_klquant_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_klquant_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_klquant_infer.tar && tar xf rec_inference.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_klquant_infer.tar && tar xf rec_inference.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0_rec_PACT" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0_rec_PACT" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_pact_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_pact_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_pact_infer.tar && tar xf rec_inference.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_rec_pact_infer.tar && tar xf rec_inference.tar && cd ../
elif [ ${model_name} = "ch_ppocr_server_v2.0_det" ]; then elif [ ${model_name} = "ch_ppocr_server_v2_0_det" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_server_v2.0_rec" ]; then elif [ ${model_name} = "ch_ppocr_server_v2_0_rec" ]; then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_server_v2.0_rec_infer.tar && tar xf rec_inference.tar && cd ../ cd ./inference && tar xf ch_ppocr_server_v2.0_rec_infer.tar && tar xf rec_inference.tar && cd ../
...@@ -564,12 +598,12 @@ if [ ${MODE} = "cpp_infer" ];then ...@@ -564,12 +598,12 @@ if [ ${MODE} = "cpp_infer" ];then
wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_pact_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_pact_infer.tar --no-check-certificate
cd ./inference && tar xf ch_PP-OCRv3_rec_pact_infer.tar && tar xf rec_inference.tar && cd ../ cd ./inference && tar xf ch_PP-OCRv3_rec_pact_infer.tar && tar xf rec_inference.tar && cd ../
elif [ ${model_name} = "ch_ppocr_mobile_v2.0" ]; then elif [ ${model_name} = "ch_ppocr_mobile_v2_0" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_det_data_50.tar && cd ../
elif [ ${model_name} = "ch_ppocr_server_v2.0" ]; then elif [ ${model_name} = "ch_ppocr_server_v2_0" ]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate
...@@ -597,7 +631,7 @@ if [ ${MODE} = "serving_infer" ];then ...@@ -597,7 +631,7 @@ if [ ${MODE} = "serving_infer" ];then
${python_name} -m pip install paddle_serving_client ${python_name} -m pip install paddle_serving_client
${python_name} -m pip install paddle-serving-app ${python_name} -m pip install paddle-serving-app
# wget model # wget model
if [ ${model_name} == "ch_ppocr_mobile_v2.0_det_KL" ] || [ ${model_name} == "ch_ppocr_mobile_v2.0_rec_KL" ] ; then if [ ${model_name} == "ch_ppocr_mobile_v2_0_det_KL" ] || [ ${model_name} == "ch_ppocr_mobile_v2.0_rec_KL" ] ; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_klquant_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_klquant_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_klquant_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_klquant_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_klquant_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_klquant_infer.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_klquant_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_klquant_infer.tar && cd ../
...@@ -609,7 +643,7 @@ if [ ${MODE} = "serving_infer" ];then ...@@ -609,7 +643,7 @@ if [ ${MODE} = "serving_infer" ];then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_det_klquant_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_det_klquant_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_klquant_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_klquant_infer.tar --no-check-certificate
cd ./inference && tar xf ch_PP-OCRv3_det_klquant_infer.tar && tar xf ch_PP-OCRv3_rec_klquant_infer.tar && cd ../ cd ./inference && tar xf ch_PP-OCRv3_det_klquant_infer.tar && tar xf ch_PP-OCRv3_rec_klquant_infer.tar && cd ../
elif [ ${model_name} == "ch_ppocr_mobile_v2.0_det_PACT" ] || [ ${model_name} == "ch_ppocr_mobile_v2.0_rec_PACT" ] ; then elif [ ${model_name} == "ch_ppocr_mobile_v2_0_det_PACT" ] || [ ${model_name} == "ch_ppocr_mobile_v2.0_rec_PACT" ] ; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_pact_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_det_pact_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_pact_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_ppocr_mobile_v2.0_rec_pact_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_pact_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_pact_infer.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_pact_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_pact_infer.tar && cd ../
...@@ -621,11 +655,11 @@ if [ ${MODE} = "serving_infer" ];then ...@@ -621,11 +655,11 @@ if [ ${MODE} = "serving_infer" ];then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_det_pact_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_det_pact_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_pact_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/tipc_fake_model/ch_PP-OCRv3_rec_pact_infer.tar --no-check-certificate
cd ./inference && tar xf ch_PP-OCRv3_det_pact_infer.tar && tar xf ch_PP-OCRv3_rec_pact_infer.tar && cd ../ cd ./inference && tar xf ch_PP-OCRv3_det_pact_infer.tar && tar xf ch_PP-OCRv3_rec_pact_infer.tar && cd ../
elif [[ ${model_name} =~ "ch_ppocr_mobile_v2.0" ]]; then elif [[ ${model_name} =~ "ch_ppocr_mobile_v2_0" ]]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && cd ../
elif [[ ${model_name} =~ "ch_ppocr_server_v2.0" ]]; then elif [[ ${model_name} =~ "ch_ppocr_server_v2_0" ]]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && cd ../ cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && cd ../
...@@ -650,11 +684,11 @@ if [ ${MODE} = "paddle2onnx_infer" ];then ...@@ -650,11 +684,11 @@ if [ ${MODE} = "paddle2onnx_infer" ];then
${python_name} -m pip install paddle2onnx ${python_name} -m pip install paddle2onnx
${python_name} -m pip install onnxruntime ${python_name} -m pip install onnxruntime
# wget model # wget model
if [[ ${model_name} =~ "ch_ppocr_mobile_v2.0" ]]; then if [[ ${model_name} =~ "ch_ppocr_mobile_v2_0" ]]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && cd ../ cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar && cd ../
elif [[ ${model_name} =~ "ch_ppocr_server_v2.0" ]]; then elif [[ ${model_name} =~ "ch_ppocr_server_v2_0" ]]; then
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar --no-check-certificate
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate
cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && cd ../ cd ./inference && tar xf ch_ppocr_server_v2.0_det_infer.tar && tar xf ch_ppocr_server_v2.0_rec_infer.tar && cd ../
......
test_tipc/prepare_lite_cpp.sh
浏览文件 @ 6fe01d43
...@@ -49,7 +49,7 @@ model_path=./inference_models ...@@ -49,7 +49,7 @@ model_path=./inference_models
for model in ${lite_model_list[*]}; do for model in ${lite_model_list[*]}; do
if [[ $model =~ "PP-OCRv2" ]]; then if [[ $model =~ "PP-OCRv2" ]]; then
inference_model_url=https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/${model}.tar inference_model_url=https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/${model}.tar
elif [[ $model =~ "v2.0" ]]; then elif [[ $model =~ "v2_0" ]]; then
inference_model_url=https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/${model}.tar inference_model_url=https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/${model}.tar
elif [[ $model =~ "PP-OCRv3" ]]; then elif [[ $model =~ "PP-OCRv3" ]]; then
inference_model_url=https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/${model}.tar inference_model_url=https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/${model}.tar
......
test_tipc/readme.md
浏览文件 @ 6fe01d43
...@@ -53,6 +53,7 @@ ...@@ -53,6 +53,7 @@
| SRN |rec_r50fpn_vd_none_srn | 识别 | 支持 | 多机多卡 <br> 混合精度 | - | - | | SRN |rec_r50fpn_vd_none_srn | 识别 | 支持 | 多机多卡 <br> 混合精度 | - | - |
| NRTR |rec_mtb_nrtr | 识别 | 支持 | 多机多卡 <br> 混合精度 | - | - | | NRTR |rec_mtb_nrtr | 识别 | 支持 | 多机多卡 <br> 混合精度 | - | - |
| SAR |rec_r31_sar | 识别 | 支持 | 多机多卡 <br> 混合精度 | - | - | | SAR |rec_r31_sar | 识别 | 支持 | 多机多卡 <br> 混合精度 | - | - |
| SPIN |rec_r32_gaspin_bilstm_att | 识别 | 支持 | 多机多卡 <br> 混合精度 | - | - |
| PGNet |rec_r34_vd_none_none_ctc_v2.0 | 端到端| 支持 | 多机多卡 <br> 混合精度 | - | - | | PGNet |rec_r34_vd_none_none_ctc_v2.0 | 端到端| 支持 | 多机多卡 <br> 混合精度 | - | - |
| TableMaster |table_structure_tablemaster_train | 表格识别| 支持 | 多机多卡 <br> 混合精度 | - | - | | TableMaster |table_structure_tablemaster_train | 表格识别| 支持 | 多机多卡 <br> 混合精度 | - | - |
......
test_tipc/test_paddle2onnx.sh
浏览文件 @ 6fe01d43
...@@ -54,7 +54,7 @@ function func_paddle2onnx(){ ...@@ -54,7 +54,7 @@ function func_paddle2onnx(){
_script=$1 _script=$1
# paddle2onnx # paddle2onnx
if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2_0" ] || [ ${model_name} = "ch_ppocr_server_v2_0" ]; then
# trans det # trans det
set_dirname=$(func_set_params "--model_dir" "${det_infer_model_dir_value}") set_dirname=$(func_set_params "--model_dir" "${det_infer_model_dir_value}")
set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}")
...@@ -113,7 +113,7 @@ function func_paddle2onnx(){ ...@@ -113,7 +113,7 @@ function func_paddle2onnx(){
_save_log_path="${LOG_PATH}/paddle2onnx_infer_cpu.log" _save_log_path="${LOG_PATH}/paddle2onnx_infer_cpu.log"
set_gpu=$(func_set_params "${use_gpu_key}" "${use_gpu}") set_gpu=$(func_set_params "${use_gpu_key}" "${use_gpu}")
set_img_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}") set_img_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}")
if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2_0" ] || [ ${model_name} = "ch_ppocr_server_v2_0" ]; then
set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}") set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}")
set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}") set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}")
infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 "
...@@ -132,7 +132,7 @@ function func_paddle2onnx(){ ...@@ -132,7 +132,7 @@ function func_paddle2onnx(){
_save_log_path="${LOG_PATH}/paddle2onnx_infer_gpu.log" _save_log_path="${LOG_PATH}/paddle2onnx_infer_gpu.log"
set_gpu=$(func_set_params "${use_gpu_key}" "${use_gpu}") set_gpu=$(func_set_params "${use_gpu_key}" "${use_gpu}")
set_img_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}") set_img_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}")
if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2_0" ] || [ ${model_name} = "ch_ppocr_server_v2_0" ]; then
set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}") set_det_model_dir=$(func_set_params "${det_model_key}" "${det_save_file_value}")
set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}") set_rec_model_dir=$(func_set_params "${rec_model_key}" "${rec_save_file_value}")
infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 " infer_model_cmd="${python} ${inference_py} ${set_gpu} ${set_img_dir} ${set_det_model_dir} ${set_rec_model_dir} --use_onnx=True > ${_save_log_path} 2>&1 "
......
test_tipc/test_serving_infer_python.sh
浏览文件 @ 6fe01d43
...@@ -71,7 +71,7 @@ function func_serving(){ ...@@ -71,7 +71,7 @@ function func_serving(){
# pdserving # pdserving
set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}") set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}")
set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}") set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2_0" ] || [ ${model_name} = "ch_ppocr_server_v2_0" ]; then
# trans det # trans det
set_dirname=$(func_set_params "--dirname" "${det_infer_model_dir_value}") set_dirname=$(func_set_params "--dirname" "${det_infer_model_dir_value}")
set_serving_server=$(func_set_params "--serving_server" "${det_serving_server_value}") set_serving_server=$(func_set_params "--serving_server" "${det_serving_server_value}")
...@@ -120,7 +120,7 @@ function func_serving(){ ...@@ -120,7 +120,7 @@ function func_serving(){
for threads in ${web_cpu_threads_list[*]}; do for threads in ${web_cpu_threads_list[*]}; do
set_cpu_threads=$(func_set_params "${web_cpu_threads_key}" "${threads}") set_cpu_threads=$(func_set_params "${web_cpu_threads_key}" "${threads}")
server_log_path="${LOG_PATH}/python_server_cpu_usemkldnn_${use_mkldnn}_threads_${threads}.log" server_log_path="${LOG_PATH}/python_server_cpu_usemkldnn_${use_mkldnn}_threads_${threads}.log"
if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2_0" ] || [ ${model_name} = "ch_ppocr_server_v2_0" ]; then
set_det_model_config=$(func_set_params "${det_server_key}" "${det_server_value}") set_det_model_config=$(func_set_params "${det_server_key}" "${det_server_value}")
set_rec_model_config=$(func_set_params "${rec_server_key}" "${rec_server_value}") set_rec_model_config=$(func_set_params "${rec_server_key}" "${rec_server_value}")
web_service_cmd="nohup ${python} ${web_service_py} ${web_use_gpu_key}="" ${web_use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_det_model_config} ${set_rec_model_config} > ${server_log_path} 2>&1 &" web_service_cmd="nohup ${python} ${web_service_py} ${web_use_gpu_key}="" ${web_use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_det_model_config} ${set_rec_model_config} > ${server_log_path} 2>&1 &"
...@@ -171,7 +171,7 @@ function func_serving(){ ...@@ -171,7 +171,7 @@ function func_serving(){
device_type=2 device_type=2
fi fi
set_precision=$(func_set_params "${web_precision_key}" "${precision}") set_precision=$(func_set_params "${web_precision_key}" "${precision}")
if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2.0" ] || [ ${model_name} = "ch_ppocr_server_v2.0" ]; then if [ ${model_name} = "ch_PP-OCRv2" ] || [ ${model_name} = "ch_PP-OCRv3" ] || [ ${model_name} = "ch_ppocr_mobile_v2_0" ] || [ ${model_name} = "ch_ppocr_server_v2_0" ]; then
set_det_model_config=$(func_set_params "${det_server_key}" "${det_server_value}") set_det_model_config=$(func_set_params "${det_server_key}" "${det_server_value}")
set_rec_model_config=$(func_set_params "${rec_server_key}" "${rec_server_value}") set_rec_model_config=$(func_set_params "${rec_server_key}" "${rec_server_value}")
web_service_cmd="nohup ${python} ${web_service_py} ${set_tensorrt} ${set_precision} ${set_det_model_config} ${set_rec_model_config} > ${server_log_path} 2>&1 &" web_service_cmd="nohup ${python} ${web_service_py} ${set_tensorrt} ${set_precision} ${set_det_model_config} ${set_rec_model_config} > ${server_log_path} 2>&1 &"
......
test_tipc/test_train_inference_python.sh
浏览文件 @ 6fe01d43
...@@ -101,6 +101,7 @@ function func_inference(){ ...@@ -101,6 +101,7 @@ function func_inference(){
_log_path=$4 _log_path=$4
_img_dir=$5 _img_dir=$5
_flag_quant=$6 _flag_quant=$6
_gpu=$7
# inference # inference
for use_gpu in ${use_gpu_list[*]}; do for use_gpu in ${use_gpu_list[*]}; do
if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then
...@@ -119,7 +120,7 @@ function func_inference(){ ...@@ -119,7 +120,7 @@ function func_inference(){
fi # skip when quant model inference but precision is not int8 fi # skip when quant model inference but precision is not int8
set_precision=$(func_set_params "${precision_key}" "${precision}") set_precision=$(func_set_params "${precision_key}" "${precision}")
_save_log_path="${_log_path}/python_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log" _save_log_path="${_log_path}/python_infer_cpu_gpus_${_gpu}_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}") set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}") set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}") set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
...@@ -150,7 +151,7 @@ function func_inference(){ ...@@ -150,7 +151,7 @@ function func_inference(){
continue continue
fi fi
for batch_size in ${batch_size_list[*]}; do for batch_size in ${batch_size_list[*]}; do
_save_log_path="${_log_path}/python_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log" _save_log_path="${_log_path}/python_infer_gpu_gpus_${_gpu}_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}") set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}") set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}") set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
...@@ -184,6 +185,7 @@ if [ ${MODE} = "whole_infer" ]; then ...@@ -184,6 +185,7 @@ if [ ${MODE} = "whole_infer" ]; then
# set CUDA_VISIBLE_DEVICES # set CUDA_VISIBLE_DEVICES
eval $env eval $env
export Count=0 export Count=0
gpu=0
IFS="|" IFS="|"
infer_run_exports=(${infer_export_list}) infer_run_exports=(${infer_export_list})
infer_quant_flag=(${infer_is_quant}) infer_quant_flag=(${infer_is_quant})
...@@ -205,7 +207,7 @@ if [ ${MODE} = "whole_infer" ]; then ...@@ -205,7 +207,7 @@ if [ ${MODE} = "whole_infer" ]; then
fi fi
#run inference #run inference
is_quant=${infer_quant_flag[Count]} is_quant=${infer_quant_flag[Count]}
func_inference "${python}" "${inference_py}" "${save_infer_dir}" "${LOG_PATH}" "${infer_img_dir}" ${is_quant} func_inference "${python}" "${inference_py}" "${save_infer_dir}" "${LOG_PATH}" "${infer_img_dir}" ${is_quant} "${gpu}"
Count=$(($Count + 1)) Count=$(($Count + 1))
done done
else else
...@@ -328,7 +330,7 @@ else ...@@ -328,7 +330,7 @@ else
else else
infer_model_dir=${save_infer_path} infer_model_dir=${save_infer_path}
fi fi
func_inference "${python}" "${inference_py}" "${infer_model_dir}" "${LOG_PATH}" "${train_infer_img_dir}" "${flag_quant}" func_inference "${python}" "${inference_py}" "${infer_model_dir}" "${LOG_PATH}" "${train_infer_img_dir}" "${flag_quant}" "${gpu}"
eval "unset CUDA_VISIBLE_DEVICES" eval "unset CUDA_VISIBLE_DEVICES"
fi fi
......
tools/infer/predict_rec.py
浏览文件 @ 6fe01d43
...@@ -83,7 +83,7 @@ class TextRecognizer(object): ...@@ -83,7 +83,7 @@ class TextRecognizer(object):
} }
elif self.rec_algorithm == "SPIN": elif self.rec_algorithm == "SPIN":
postprocess_params = { postprocess_params = {
'name': 'SPINAttnLabelDecode', 'name': 'SPINLabelDecode',
"character_dict_path": args.rec_char_dict_path, "character_dict_path": args.rec_char_dict_path,
"use_space_char": args.use_space_char "use_space_char": args.use_space_char
} }
......
tools/infer/utility.py
浏览文件 @ 6fe01d43
...@@ -38,6 +38,7 @@ def init_args(): ...@@ -38,6 +38,7 @@ def init_args():
parser.add_argument("--ir_optim", type=str2bool, default=True) parser.add_argument("--ir_optim", type=str2bool, default=True)
parser.add_argument("--use_tensorrt", type=str2bool, default=False) parser.add_argument("--use_tensorrt", type=str2bool, default=False)
parser.add_argument("--min_subgraph_size", type=int, default=15) parser.add_argument("--min_subgraph_size", type=int, default=15)
parser.add_argument("--shape_info_filename", type=str, default=None)
parser.add_argument("--precision", type=str, default="fp32") parser.add_argument("--precision", type=str, default="fp32")
parser.add_argument("--gpu_mem", type=int, default=500) parser.add_argument("--gpu_mem", type=int, default=500)
...@@ -206,9 +207,24 @@ def create_predictor(args, mode, logger): ...@@ -206,9 +207,24 @@ def create_predictor(args, mode, logger):
workspace_size=1 << 30, workspace_size=1 << 30,
precision_mode=precision, precision_mode=precision,
max_batch_size=args.max_batch_size, max_batch_size=args.max_batch_size,
min_subgraph_size=args.min_subgraph_size, min_subgraph_size=args.
min_subgraph_size, # skip the minmum trt subgraph
use_calib_mode=False) use_calib_mode=False)
# skip the minmum trt subgraph
# collect shape
if args.shape_info_filename is not None:
if not os.path.exists(args.shape_info_filename):
config.collect_shape_range_info(args.shape_info_filename)
logger.info(
f"collect dynamic shape info into : {args.shape_info_filename}"
)
else:
logger.info(
f"dynamic shape info file( {args.shape_info_filename} ) already exists, not need to generate again."
)
config.enable_tuned_tensorrt_dynamic_shape(
args.shape_info_filename, True)
use_dynamic_shape = True use_dynamic_shape = True
if mode == "det": if mode == "det":
min_input_shape = { min_input_shape = {
......
tools/infer_vqa_token_ser_re.py
浏览文件 @ 6fe01d43
...@@ -113,10 +113,13 @@ def make_input(ser_inputs, ser_results): ...@@ -113,10 +113,13 @@ def make_input(ser_inputs, ser_results):
class SerRePredictor(object): class SerRePredictor(object):
def __init__(self, config, ser_config): def __init__(self, config, ser_config):
global_config = config['Global']
if "infer_mode" in global_config:
ser_config["Global"]["infer_mode"] = global_config["infer_mode"]
self.ser_engine = SerPredictor(ser_config) self.ser_engine = SerPredictor(ser_config)
# init re model # init re model
global_config = config['Global']
# build post process # build post process
self.post_process_class = build_post_process(config['PostProcess'], self.post_process_class = build_post_process(config['PostProcess'],
...@@ -130,8 +133,8 @@ class SerRePredictor(object): ...@@ -130,8 +133,8 @@ class SerRePredictor(object):
self.model.eval() self.model.eval()
def __call__(self, img_path): def __call__(self, data):
ser_results, ser_inputs = self.ser_engine({'img_path': img_path}) ser_results, ser_inputs = self.ser_engine(data)
re_input, entity_idx_dict_batch = make_input(ser_inputs, ser_results) re_input, entity_idx_dict_batch = make_input(ser_inputs, ser_results)
preds = self.model(re_input) preds = self.model(re_input)
post_result = self.post_process_class( post_result = self.post_process_class(
...@@ -173,18 +176,33 @@ if __name__ == '__main__': ...@@ -173,18 +176,33 @@ if __name__ == '__main__':
ser_re_engine = SerRePredictor(config, ser_config) ser_re_engine = SerRePredictor(config, ser_config)
if config["Global"].get("infer_mode", None) is False:
data_dir = config['Eval']['dataset']['data_dir']
with open(config['Global']['infer_img'], "rb") as f:
infer_imgs = f.readlines()
else:
infer_imgs = get_image_file_list(config['Global']['infer_img']) infer_imgs = get_image_file_list(config['Global']['infer_img'])
with open( with open(
os.path.join(config['Global']['save_res_path'], os.path.join(config['Global']['save_res_path'],
"infer_results.txt"), "infer_results.txt"),
"w", "w",
encoding='utf-8') as fout: encoding='utf-8') as fout:
for idx, img_path in enumerate(infer_imgs): for idx, info in enumerate(infer_imgs):
if config["Global"].get("infer_mode", None) is False:
data_line = info.decode('utf-8')
substr = data_line.strip("\n").split("\t")
img_path = os.path.join(data_dir, substr[0])
data = {'img_path': img_path, 'label': substr[1]}
else:
img_path = info
data = {'img_path': img_path}
save_img_path = os.path.join( save_img_path = os.path.join(
config['Global']['save_res_path'], config['Global']['save_res_path'],
os.path.splitext(os.path.basename(img_path))[0] + "_ser_re.jpg") os.path.splitext(os.path.basename(img_path))[0] + "_ser_re.jpg")
result = ser_re_engine(img_path) result = ser_re_engine(data)
result = result[0] result = result[0]
fout.write(img_path + "\t" + json.dumps( fout.write(img_path + "\t" + json.dumps(
{ {
......
tools/train.py
浏览文件 @ 6fe01d43
...@@ -166,6 +166,8 @@ def main(config, device, logger, vdl_writer): ...@@ -166,6 +166,8 @@ def main(config, device, logger, vdl_writer):
else: else:
scaler = None scaler = None
if config['Global']['distributed']:
model = paddle.DataParallel(model)
# start train # start train
program.train(config, train_dataloader, valid_dataloader, device, model, program.train(config, train_dataloader, valid_dataloader, device, model,
loss_class, optimizer, lr_scheduler, post_process_class, loss_class, optimizer, lr_scheduler, post_process_class,
......
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