diff --git a/__init__.py b/__init__.py
index 504aeca61b734937b97bab18dec8e49237d873d5..e22e466a8426c437407c491bbae47c3b66defa2e 100644
--- a/__init__.py
+++ b/__init__.py
@@ -15,4 +15,4 @@ import paddleocr
from .paddleocr import *
__version__ = paddleocr.VERSION
-__all__ = ['PaddleOCR', 'PPStructure', 'draw_ocr', 'draw_structure_result', 'save_structure_res']
+__all__ = ['PaddleOCR', 'PPStructure', 'draw_ocr', 'draw_structure_result', 'save_structure_res','download_with_progressbar']
diff --git a/doc/doc_ch/whl.md b/doc/doc_ch/whl.md
index edacb5b2d804d85fd593f4a6c439fc223a8f5e4b..167ed7b2b8a13706dfe1533265b6d96560265511 100644
--- a/doc/doc_ch/whl.md
+++ b/doc/doc_ch/whl.md
@@ -5,26 +5,32 @@
### 1.1 安装whl包
pip安装
+
```bash
pip install "paddleocr>=2.0.1" # 推荐使用2.0.1+版本
```
本地构建并安装
+
```bash
python3 setup.py bdist_wheel
pip3 install dist/paddleocr-x.x.x-py3-none-any.whl # x.x.x是paddleocr的版本号
```
## 2 使用
+
### 2.1 代码使用
+
paddleocr whl包会自动下载ppocr轻量级模型作为默认模型，可以根据第3节**自定义模型**进行自定义更换。
* 检测+方向分类器+识别全流程
+
```python
from paddleocr import PaddleOCR, draw_ocr
+
# Paddleocr目前支持中英文、英文、法语、德语、韩语、日语，可以通过修改lang参数进行切换
# 参数依次为`ch`, `en`, `french`, `german`, `korean`, `japan`。
-ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
+ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs/11.jpg'
result = ocr.ocr(img_path, cls=True)
for line in result:
@@ -32,6 +38,7 @@ for line in result:
# 显示结果
from PIL import Image
+
image = Image.open(img_path).convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
@@ -40,31 +47,36 @@ im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')
```
+
结果是一个list，每个item包含了文本框，文字和识别置信度
+
```bash
[[[24.0, 36.0], [304.0, 34.0], [304.0, 72.0], [24.0, 74.0]], ['纯臻营养护发素', 0.964739]]
[[[24.0, 80.0], [172.0, 80.0], [172.0, 104.0], [24.0, 104.0]], ['产品信息/参数', 0.98069626]]
[[[24.0, 109.0], [333.0, 109.0], [333.0, 136.0], [24.0, 136.0]], ['（45元/每公斤，100公斤起订）', 0.9676722]]
......
```
+
结果可视化
-
* 检测+识别
+
```python
from paddleocr import PaddleOCR, draw_ocr
-ocr = PaddleOCR() # need to run only once to download and load model into memory
+
+ocr = PaddleOCR() # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs/11.jpg'
-result = ocr.ocr(img_path,cls=False)
+result = ocr.ocr(img_path, cls=False)
for line in result:
print(line)
# 显示结果
from PIL import Image
+
image = Image.open(img_path).convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
@@ -73,38 +85,46 @@ im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')
```
+
结果是一个list，每个item包含了文本框，文字和识别置信度
+
```bash
[[[24.0, 36.0], [304.0, 34.0], [304.0, 72.0], [24.0, 74.0]], ['纯臻营养护发素', 0.964739]]
[[[24.0, 80.0], [172.0, 80.0], [172.0, 104.0], [24.0, 104.0]], ['产品信息/参数', 0.98069626]]
[[[24.0, 109.0], [333.0, 109.0], [333.0, 136.0], [24.0, 136.0]], ['（45元/每公斤，100公斤起订）', 0.9676722]]
......
```
+
结果可视化
-
* 方向分类器+识别
+
```python
from paddleocr import PaddleOCR
-ocr = PaddleOCR(use_angle_cls=True) # need to run only once to download and load model into memory
+
+ocr = PaddleOCR(use_angle_cls=True) # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs_words/ch/word_1.jpg'
result = ocr.ocr(img_path, det=False, cls=True)
for line in result:
print(line)
```
+
结果是一个list，每个item只包含识别结果和识别置信度
+
```bash
['韩国小馆', 0.9907421]
```
* 单独执行检测
+
```python
from paddleocr import PaddleOCR, draw_ocr
-ocr = PaddleOCR() # need to run only once to download and load model into memory
+
+ocr = PaddleOCR() # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs/11.jpg'
result = ocr.ocr(img_path, rec=False)
for line in result:
@@ -118,13 +138,16 @@ im_show = draw_ocr(image, result, txts=None, scores=None, font_path='/path/to/Pa
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')
```
+
结果是一个list，每个item只包含文本框
+
```bash
[[26.0, 457.0], [137.0, 457.0], [137.0, 477.0], [26.0, 477.0]]
[[25.0, 425.0], [372.0, 425.0], [372.0, 448.0], [25.0, 448.0]]
[[128.0, 397.0], [273.0, 397.0], [273.0, 414.0], [128.0, 414.0]]
......
```
+
结果可视化
@@ -133,29 +156,37 @@ im_show.save('result.jpg')
* 单独执行识别
+
```python
from paddleocr import PaddleOCR
-ocr = PaddleOCR() # need to run only once to download and load model into memory
+
+ocr = PaddleOCR() # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs_words/ch/word_1.jpg'
result = ocr.ocr(img_path, det=False)
for line in result:
print(line)
```
+
结果是一个list，每个item只包含识别结果和识别置信度
+
```bash
['韩国小馆', 0.9907421]
```
* 单独执行方向分类器
+
```python
from paddleocr import PaddleOCR
-ocr = PaddleOCR(use_angle_cls=True) # need to run only once to download and load model into memory
+
+ocr = PaddleOCR(use_angle_cls=True) # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs_words/ch/word_1.jpg'
result = ocr.ocr(img_path, det=False, rec=False, cls=True)
for line in result:
print(line)
```
+
结果是一个list，每个item只包含分类结果和分类置信度
+
```bash
['0', 0.9999924]
```
@@ -163,15 +194,19 @@ for line in result:
### 2.2 通过命令行使用
查看帮助信息
+
```bash
paddleocr -h
```
* 检测+方向分类器+识别全流程
+
```bash
paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --use_angle_cls true
```
+
结果是一个list，每个item包含了文本框，文字和识别置信度
+
```bash
[[[24.0, 36.0], [304.0, 34.0], [304.0, 72.0], [24.0, 74.0]], ['纯臻营养护发素', 0.964739]]
[[[24.0, 80.0], [172.0, 80.0], [172.0, 104.0], [24.0, 104.0]], ['产品信息/参数', 0.98069626]]
@@ -180,10 +215,13 @@ paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --use_angle_cls true
```
* 检测+识别
+
```bash
paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg
```
+
结果是一个list，每个item包含了文本框，文字和识别置信度
+
```bash
[[[24.0, 36.0], [304.0, 34.0], [304.0, 72.0], [24.0, 74.0]], ['纯臻营养护发素', 0.964739]]
[[[24.0, 80.0], [172.0, 80.0], [172.0, 104.0], [24.0, 104.0]], ['产品信息/参数', 0.98069626]]
@@ -192,20 +230,25 @@ paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg
```
* 方向分类器+识别
+
```bash
paddleocr --image_dir PaddleOCR/doc/imgs_words/ch/word_1.jpg --use_angle_cls true --det false
```
结果是一个list，每个item只包含识别结果和识别置信度
+
```bash
['韩国小馆', 0.9907421]
```
* 单独执行检测
+
```bash
paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --rec false
```
+
结果是一个list，每个item只包含文本框
+
```bash
[[26.0, 457.0], [137.0, 457.0], [137.0, 477.0], [26.0, 477.0]]
[[25.0, 425.0], [372.0, 425.0], [372.0, 448.0], [25.0, 448.0]]
@@ -214,34 +257,42 @@ paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --rec false
```
* 单独执行识别
+
```bash
paddleocr --image_dir PaddleOCR/doc/imgs_words/ch/word_1.jpg --det false
```
结果是一个list，每个item只包含识别结果和识别置信度
+
```bash
['韩国小馆', 0.9907421]
```
* 单独执行方向分类器
+
```bash
paddleocr --image_dir PaddleOCR/doc/imgs_words/ch/word_1.jpg --use_angle_cls true --det false --rec false
```
结果是一个list，每个item只包含分类结果和分类置信度
+
```bash
['0', 0.9999924]
```
## 3 自定义模型
-当内置模型无法满足需求时，需要使用到自己训练的模型。
-首先，参照[inference.md](./inference.md) 第一节转换将检测、分类和识别模型转换为inference模型，然后按照如下方式使用
+
+当内置模型无法满足需求时，需要使用到自己训练的模型。 首先，参照[inference.md](./inference.md) 第一节转换将检测、分类和识别模型转换为inference模型，然后按照如下方式使用
### 3.1 代码使用
+
```python
from paddleocr import PaddleOCR, draw_ocr
+
# 模型路径下必须含有model和params文件
-ocr = PaddleOCR(det_model_dir='{your_det_model_dir}', rec_model_dir='{your_rec_model_dir}', rec_char_dict_path='{your_rec_char_dict_path}', cls_model_dir='{your_cls_model_dir}', use_angle_cls=True)
+ocr = PaddleOCR(det_model_dir='{your_det_model_dir}', rec_model_dir='{your_rec_model_dir}',
+ rec_char_dict_path='{your_rec_char_dict_path}', cls_model_dir='{your_cls_model_dir}',
+ use_angle_cls=True)
img_path = 'PaddleOCR/doc/imgs/11.jpg'
result = ocr.ocr(img_path, cls=True)
for line in result:
@@ -249,6 +300,7 @@ for line in result:
# 显示结果
from PIL import Image
+
image = Image.open(img_path).convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
@@ -269,11 +321,13 @@ paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --det_model_dir {your_det_model_
### 4.1 网络图片
- 代码使用
+
```python
-from paddleocr import PaddleOCR, draw_ocr
+from paddleocr import PaddleOCR, draw_ocr, download_with_progressbar
+
# Paddleocr目前支持中英文、英文、法语、德语、韩语、日语，可以通过修改lang参数进行切换
# 参数依次为`ch`, `en`, `french`, `german`, `korean`, `japan`。
-ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
+ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
img_path = 'http://n.sinaimg.cn/ent/transform/w630h933/20171222/o111-fypvuqf1838418.jpg'
result = ocr.ocr(img_path, cls=True)
for line in result:
@@ -281,7 +335,9 @@ for line in result:
# 显示结果
from PIL import Image
-image = Image.open(img_path).convert('RGB')
+
+download_with_progressbar(img_path, 'tmp.jpg')
+image = Image.open('tmp.jpg').convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
scores = [line[1][1] for line in result]
@@ -289,19 +345,24 @@ im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')
```
+
- 命令行模式
+
```bash
paddleocr --image_dir http://n.sinaimg.cn/ent/transform/w630h933/20171222/o111-fypvuqf1838418.jpg --use_angle_cls=true
```
### 4.2 numpy数组
+
仅通过代码使用时支持numpy数组作为输入
+
```python
import cv2
from paddleocr import PaddleOCR, draw_ocr
+
# Paddleocr目前支持中英文、英文、法语、德语、韩语、日语，可以通过修改lang参数进行切换
# 参数依次为`ch`, `en`, `french`, `german`, `korean`, `japan`。
-ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
+ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs/11.jpg'
img = cv2.imread(img_path)
# img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY), 如果你自己训练的模型支持灰度图，可以将这句话的注释取消
@@ -311,6 +372,7 @@ for line in result:
# 显示结果
from PIL import Image
+
image = Image.open(img_path).convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
diff --git a/doc/doc_en/whl_en.md b/doc/doc_en/whl_en.md
index 79bc9b0bc5c5f7f33682d5829e5b613b278a4964..c8c8353accdf7f6ce179d3700547bfe9bd70c200 100644
--- a/doc/doc_en/whl_en.md
+++ b/doc/doc_en/whl_en.md
@@ -306,7 +306,7 @@ Support numpy array as input only when used by code
```python
import cv2
-from paddleocr import PaddleOCR, draw_ocr
+from paddleocr import PaddleOCR, draw_ocr, download_with_progressbar
ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs/11.jpg'
img = cv2.imread(img_path)
@@ -317,7 +317,9 @@ for line in result:
# show result
from PIL import Image
-image = Image.open(img_path).convert('RGB')
+
+download_with_progressbar(img_path, 'tmp.jpg')
+image = Image.open('tmp.jpg').convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
scores = [line[1][1] for line in result]
diff --git a/paddleocr.py b/paddleocr.py
index 5ae812fa8741a9007bacb4fb64a43f97648d8f77..c52737f55b61cd29c08367adb6d7e05c561e933e 100644
--- a/paddleocr.py
+++ b/paddleocr.py
@@ -33,7 +33,7 @@ from tools.infer.utility import draw_ocr, str2bool
from ppstructure.utility import init_args, draw_structure_result
from ppstructure.predict_system import OCRSystem, save_structure_res
-__all__ = ['PaddleOCR', 'PPStructure', 'draw_ocr', 'draw_structure_result', 'save_structure_res']
+__all__ = ['PaddleOCR', 'PPStructure', 'draw_ocr', 'draw_structure_result', 'save_structure_res','download_with_progressbar']
model_urls = {
'det': {
