提交 a5694968 编写于 作者: W WenmuZhou

fix bug when inference with network img

上级 b2debedb
......@@ -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']
......@@ -5,23 +5,29 @@
### 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
......@@ -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
<div align="center">
<img src="../imgs_results/whl/11_det_rec.jpg" width="800">
</div>
* 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
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]
......@@ -73,37 +85,45 @@ 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
<div align="center">
<img src="../imgs_results/whl/11_det_rec.jpg" width="800">
</div>
* 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
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
img_path = 'PaddleOCR/doc/imgs/11.jpg'
result = ocr.ocr(img_path, rec=False)
......@@ -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')
</div>
* 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
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
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]
......@@ -269,8 +321,10 @@ 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
......@@ -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]
......@@ -289,16 +345,21 @@ 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
......@@ -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]
......
......@@ -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]
......
......@@ -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': {
......
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