未验证 提交 0b944919 编写于 作者: A andyjpaddle 提交者: GitHub

Merge pull request #6095 from andyjpaddle/dygraph

[doc] update doc for whl and python cpp infer quick
......@@ -208,6 +208,8 @@ Execute the built executable file:
./build/ppocr [--param1] [--param2] [...]
```
**Note**:ppocr uses the `PP-OCRv3` model by default, and the input shape used by the recognition model is `3, 48, 320`, so if you use the recognition function, you need to add the parameter `--rec_img_h=48`, if you do not use the default `PP-OCRv3` model, you do not need to set this parameter.
Specifically,
##### 1. det+cls+rec:
......@@ -220,6 +222,7 @@ Specifically,
--det=true \
--rec=true \
--cls=true \
--rec_img_h=48\
```
##### 2. det+rec:
......@@ -231,6 +234,7 @@ Specifically,
--det=true \
--rec=true \
--cls=false \
--rec_img_h=48\
```
##### 3. det
......@@ -250,6 +254,7 @@ Specifically,
--det=false \
--rec=true \
--cls=true \
--rec_img_h=48\
```
##### 5. rec
......@@ -260,6 +265,7 @@ Specifically,
--det=false \
--rec=true \
--cls=false \
--rec_img_h=48\
```
##### 6. cls
......@@ -335,10 +341,10 @@ The detection results will be shown on the screen, which is as follows.
```bash
predict img: ../../doc/imgs/12.jpg
../../doc/imgs/12.jpg
0 det boxes: [[79,553],[399,541],[400,573],[80,585]] rec text: 打浦路252935号 rec score: 0.933757
1 det boxes: [[31,509],[510,488],[511,529],[33,549]] rec text: 绿洲仕格维花园公寓 rec score: 0.951745
2 det boxes: [[181,456],[395,448],[396,480],[182,488]] rec text: 打浦路15号 rec score: 0.91956
3 det boxes: [[43,413],[480,391],[481,428],[45,450]] rec text: 上海斯格威铂尔多大酒店 rec score: 0.915914
0 det boxes: [[74,553],[427,542],[428,571],[75,582]] rec text: 打浦路252935号 rec score: 0.947724
1 det boxes: [[23,507],[513,488],[515,529],[24,548]] rec text: 绿洲仕格维花园公寓 rec score: 0.993728
2 det boxes: [[187,456],[399,448],[400,480],[188,488]] rec text: 打浦路15号 rec score: 0.964994
3 det boxes: [[42,413],[483,391],[484,428],[43,450]] rec text: 上海斯格威铂尔大酒店 rec score: 0.980086
The detection visualized image saved in ./output//12.jpg
```
......
......@@ -213,6 +213,9 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
本demo支持系统串联调用,也支持单个功能的调用,如,只使用检测或识别功能。
**注意** ppocr默认使用`PP-OCRv3`模型,识别模型使用的输入shape为`3,48,320`, 因此如果使用识别功能,需要添加参数`--rec_img_h=48`,如果不使用默认的`PP-OCRv3`模型,则无需设置该参数。
运行方式:
```shell
./build/ppocr [--param1] [--param2] [...]
......@@ -229,6 +232,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
--det=true \
--rec=true \
--cls=true \
--rec_img_h=48\
```
##### 2. 检测+识别:
......@@ -240,6 +244,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
--det=true \
--rec=true \
--cls=false \
--rec_img_h=48\
```
##### 3. 检测:
......@@ -259,6 +264,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
--det=false \
--rec=true \
--cls=true \
--rec_img_h=48\
```
##### 5. 识别:
......@@ -269,6 +275,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
--det=false \
--rec=true \
--cls=false \
--rec_img_h=48\
```
##### 6. 分类:
......@@ -343,10 +350,10 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
```bash
predict img: ../../doc/imgs/12.jpg
../../doc/imgs/12.jpg
0 det boxes: [[79,553],[399,541],[400,573],[80,585]] rec text: 打浦路252935号 rec score: 0.933757
1 det boxes: [[31,509],[510,488],[511,529],[33,549]] rec text: 绿洲仕格维花园公寓 rec score: 0.951745
2 det boxes: [[181,456],[395,448],[396,480],[182,488]] rec text: 打浦路15号 rec score: 0.91956
3 det boxes: [[43,413],[480,391],[481,428],[45,450]] rec text: 上海斯格威铂尔多大酒店 rec score: 0.915914
0 det boxes: [[74,553],[427,542],[428,571],[75,582]] rec text: 打浦路252935号 rec score: 0.947724
1 det boxes: [[23,507],[513,488],[515,529],[24,548]] rec text: 绿洲仕格维花园公寓 rec score: 0.993728
2 det boxes: [[187,456],[399,448],[400,480],[188,488]] rec text: 打浦路15号 rec score: 0.964994
3 det boxes: [[42,413],[483,391],[484,428],[43,450]] rec text: 上海斯格威铂尔大酒店 rec score: 0.980086
The detection visualized image saved in ./output//12.jpg
```
......
......@@ -19,9 +19,9 @@
```
# 下载超轻量中文检测模型:
wget https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar
tar xf ch_PP-OCRv2_det_infer.tar
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv2_det_infer/"
wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar
tar xf ch_PP-OCRv3_det_infer.tar
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/"
```
......@@ -40,13 +40,13 @@ python3 tools/infer/predict_det.py --image_dir="./doc/imgs/00018069.jpg" --det_m
如果输入图片的分辨率比较大,而且想使用更大的分辨率预测,可以设置det_limit_side_len 为想要的值,比如1216:
```
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --det_limit_type=max --det_limit_side_len=1216
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/" --det_limit_type=max --det_limit_side_len=1216
```
如果想使用CPU进行预测,执行命令如下
```
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --use_gpu=False
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/" --use_gpu=False
```
......@@ -59,13 +59,15 @@ python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_di
### 2.1 超轻量中文识别模型推理
**注意** `PP-OCRv3`的识别模型使用的输入shape为`3,48,320`, 需要添加参数`--rec_image_shape=3,48,320`,如果不使用`PP-OCRv3`的识别模型,则无需设置该参数。
超轻量中文识别模型推理,可以执行如下命令:
```
# 下载超轻量中文识别模型:
wget https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar
tar xf ch_PP-OCRv2_rec_infer.tar
python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/ch/word_4.jpg" --rec_model_dir="./ch_PP-OCRv2_rec_infer/"
wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar
tar xf ch_PP-OCRv3_rec_infer.tar
python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/ch/word_4.jpg" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --rec_image_shape=3,48,320
```
![](../imgs_words/ch/word_4.jpg)
......@@ -73,7 +75,7 @@ python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/ch/word_4.jpg"
执行命令后,上面图像的预测结果(识别的文本和得分)会打印到屏幕上,示例如下:
```bash
Predicts of ./doc/imgs_words/ch/word_4.jpg:('实力活力', 0.98458153)
Predicts of ./doc/imgs_words/ch/word_4.jpg:('实力活力', 0.9956803321838379)
```
<a name="多语言模型的推理"></a>
......@@ -119,17 +121,19 @@ Predicts of ./doc/imgs_words/ch/word_4.jpg:['0', 0.9999982]
## 4. 文本检测、方向分类和文字识别串联推理
**注意** `PP-OCRv3`的识别模型使用的输入shape为`3,48,320`, 需要添加参数`--rec_image_shape=3,48,320`,如果不使用`PP-OCRv3`的识别模型,则无需设置该参数。
以超轻量中文OCR模型推理为例,在执行预测时,需要通过参数`image_dir`指定单张图像或者图像集合的路径、参数`det_model_dir`,`cls_model_dir``rec_model_dir`分别指定检测,方向分类和识别的inference模型路径。参数`use_angle_cls`用于控制是否启用方向分类模型。`use_mp`表示是否使用多进程。`total_process_num`表示在使用多进程时的进程数。可视化识别结果默认保存到 ./inference_results 文件夹里面。
```shell
# 使用方向分类器
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --cls_model_dir="./inference/cls/" --rec_model_dir="./inference/ch_PP-OCRv2_rec_infer/" --use_angle_cls=true
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/" --cls_model_dir="./cls/" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --use_angle_cls=true --rec_image_shape=3,48,320
# 不使用方向分类器
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --rec_model_dir="./inference/ch_PP-OCRv2_rec_infer/" --use_angle_cls=false
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --use_angle_cls=false --rec_image_shape=3,48,320
# 使用多进程
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --rec_model_dir="./inference/ch_PP-OCRv2_rec_infer/" --use_angle_cls=false --use_mp=True --total_process_num=6
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --use_angle_cls=false --use_mp=True --total_process_num=6 --rec_image_shape=3,48,320
```
执行命令后,识别结果图像如下:
![](../imgs_results/system_res_00018069.jpg)
![](../imgs_results/system_res_00018069_v3.jpg)
......@@ -59,21 +59,21 @@ cd /path/to/ppocr_img
如果不使用提供的测试图片,可以将下方`--image_dir`参数替换为相应的测试图片路径。
**注意** whl包默认使用`PP-OCRv3`模型,识别模型使用的输入shape为`3,48,320`, 因此如果使用识别功能,需要添加参数`--rec_image_shape 3,48,320`,如果不使用默认的`PP-OCRv3`模型,则无需设置该参数。
<a name="211"></a>
#### 2.1.1 中英文模型
* 检测+方向分类器+识别全流程:`--use_angle_cls true`设置使用方向分类器识别180度旋转文字,`--use_gpu false`设置不使用GPU
```bash
paddleocr --image_dir ./imgs/11.jpg --use_angle_cls true --use_gpu false
paddleocr --image_dir ./imgs/11.jpg --use_angle_cls true --use_gpu false --rec_image_shape 3,48,320
```
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]]
[[[28.0, 37.0], [302.0, 39.0], [302.0, 72.0], [27.0, 70.0]], ('纯臻营养护发素', 0.9658738374710083)]
......
```
......@@ -86,35 +86,34 @@ cd /path/to/ppocr_img
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]]
[[27.0, 459.0], [136.0, 459.0], [136.0, 479.0], [27.0, 479.0]]
[[28.0, 429.0], [372.0, 429.0], [372.0, 445.0], [28.0, 445.0]]
......
```
- 单独使用识别:设置`--det``false`
```bash
paddleocr --image_dir ./imgs_words/ch/word_1.jpg --det false
paddleocr --image_dir ./imgs_words/ch/word_1.jpg --det false --rec_image_shape 3,48,320
```
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]
['韩国小馆', 0.994467]
```
如需使用2.0模型,请指定参数`--version PP-OCR`,paddleocr默认使用2.1模型(`--versioin PP-OCRv2`)。更多whl包使用可参考[whl包文档](./whl.md)
如需使用2.0模型,请指定参数`--version PP-OCR`,paddleocr默认使用PP-OCRv3模型(`--versioin PP-OCRv3`)。更多whl包使用可参考[whl包文档](./whl.md)
<a name="212"></a>
#### 2.1.2 多语言模型
Paddleocr目前支持80个语种,可以通过修改`--lang`参数进行切换,对于英文模型,指定`--lang=en`
Paddleocr目前支持80个语种,可以通过修改`--lang`参数进行切换,对于英文模型,指定`--lang=en`, PP-OCRv3目前只支持中文和英文模型,其他多语言模型会陆续更新
``` bash
paddleocr --image_dir ./imgs_en/254.jpg --lang=en
paddleocr --image_dir ./imgs_en/254.jpg --lang=en --rec_image_shape 3,48,320
```
<div align="center">
......@@ -125,13 +124,9 @@ paddleocr --image_dir ./imgs_en/254.jpg --lang=en
结果是一个list,每个item包含了文本框,文字和识别置信度
```text
[('PHO CAPITAL', 0.95723116), [[66.0, 50.0], [327.0, 44.0], [327.0, 76.0], [67.0, 82.0]]]
[('107 State Street', 0.96311164), [[72.0, 90.0], [451.0, 84.0], [452.0, 116.0], [73.0, 121.0]]]
[('Montpelier Vermont', 0.97389287), [[69.0, 132.0], [501.0, 126.0], [501.0, 158.0], [70.0, 164.0]]]
[('8022256183', 0.99810505), [[71.0, 175.0], [363.0, 170.0], [364.0, 202.0], [72.0, 207.0]]]
[('REG 07-24-201706:59 PM', 0.93537045), [[73.0, 299.0], [653.0, 281.0], [654.0, 318.0], [74.0, 336.0]]]
[('045555', 0.99346405), [[509.0, 331.0], [651.0, 325.0], [652.0, 356.0], [511.0, 362.0]]]
[('CT1', 0.9988654), [[535.0, 367.0], [654.0, 367.0], [654.0, 406.0], [535.0, 406.0]]]
[[[67.0, 51.0], [327.0, 46.0], [327.0, 74.0], [68.0, 80.0]], ('PHOCAPITAL', 0.9944712519645691)]
[[[72.0, 92.0], [453.0, 84.0], [454.0, 114.0], [73.0, 122.0]], ('107 State Street', 0.9744491577148438)]
[[[69.0, 135.0], [501.0, 125.0], [501.0, 156.0], [70.0, 165.0]], ('Montpelier Vermont', 0.9357033967971802)]
......
```
......@@ -181,9 +176,7 @@ 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]]
[[[28.0, 37.0], [302.0, 39.0], [302.0, 72.0], [27.0, 70.0]], ('纯臻营养护发素', 0.9658738374710083)]
......
```
......
......@@ -199,46 +199,44 @@ for line in result:
paddleocr -h
```
**注意** whl包默认使用`PP-OCRv3`模型,识别模型使用的输入shape为`3,48,320`, 因此如果使用识别功能,需要添加参数`--rec_image_shape 3,48,320`,如果不使用默认的`PP-OCRv3`模型,则无需设置该参数。
* 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
paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --use_angle_cls true --rec_image_shape 3,48,320
```
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]]µ
[[[28.0, 37.0], [302.0, 39.0], [302.0, 72.0], [27.0, 70.0]], ('纯臻营养护发素', 0.9658738374710083)]
......
```
* 检测+识别
```bash
paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg
paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --rec_image_shape 3,48,320
```
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]]
[[[28.0, 37.0], [302.0, 39.0], [302.0, 72.0], [27.0, 70.0]], ('纯臻营养护发素', 0.9658738374710083)]
......
```
* 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
paddleocr --image_dir PaddleOCR/doc/imgs_words/ch/word_1.jpg --use_angle_cls true --det false --rec_image_shape 3,48,320
```
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]
['韩国小馆', 0.994467]
```
* 单独执行检测
......@@ -250,22 +248,21 @@ 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]]
[[128.0, 397.0], [273.0, 397.0], [273.0, 414.0], [128.0, 414.0]]
[[27.0, 459.0], [136.0, 459.0], [136.0, 479.0], [27.0, 479.0]]
[[28.0, 429.0], [372.0, 429.0], [372.0, 445.0], [28.0, 445.0]]
......
```
* 单独执行识别
```bash
paddleocr --image_dir PaddleOCR/doc/imgs_words/ch/word_1.jpg --det false
paddleocr --image_dir PaddleOCR/doc/imgs_words/ch/word_1.jpg --det false --rec_image_shape 3,48,320
```
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]
['韩国小馆', 0.994467]
```
* 单独执行方向分类器
......@@ -419,5 +416,4 @@ im_show.save('result.jpg')
| cls | 前向时是否启动分类 (命令行模式下使用use_angle_cls控制前向是否启动分类) | FALSE |
| show_log | 是否打印logger信息 | FALSE |
| type | 执行ocr或者表格结构化, 值可选['ocr','structure'] | ocr |
| ocr_version | OCR模型版本,可选PP-OCRv2, PP-OCR。PP-OCRv2 目前仅支持中文的检测和识别模型,PP-OCR支持中文的检测,识别,多语种识别,方向分类器等模型 | PP-OCRv2 |
| structure_version | 表格结构化模型版本,可选 STRUCTURE。STRUCTURE支持表格结构化模型 | STRUCTURE |
| ocr_version | OCR模型版本,可选PP-OCRv3, PP-OCRv2, PP-OCR。PP-OCRv3 目前仅支持中、英文的检测和识别模型,方向分类器模型;PP-OCRv2 目前仅支持中文的检测和识别模型;PP-OCR支持中文的检测,识别,多语种识别,方向分类器等模型 | PP-OCRv3 |
......@@ -20,10 +20,10 @@ The default configuration is based on the inference setting of the DB text detec
```
# download DB text detection inference model
wget https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar
tar xf ch_PP-OCRv2_det_infer.tar
wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar
tar xf ch_PP-OCRv3_det_infer.tar
# run inference
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv2_det_infer.tar/"
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/"
```
The visual text detection results are saved to the ./inference_results folder by default, and the name of the result file is prefixed with 'det_res'. Examples of results are as follows:
......@@ -40,12 +40,12 @@ Set as `limit_type='min', det_limit_side_len=960`, it means that the shortest si
If the resolution of the input picture is relatively large and you want to use a larger resolution prediction, you can set det_limit_side_len to the desired value, such as 1216:
```
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --det_limit_type=max --det_limit_side_len=1216
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/" --det_limit_type=max --det_limit_side_len=1216
```
If you want to use the CPU for prediction, execute the command as follows
```
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --use_gpu=False
python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/" --use_gpu=False
```
<a name="RECOGNITION_MODEL_INFERENCE"></a>
......@@ -56,14 +56,17 @@ python3 tools/infer/predict_det.py --image_dir="./doc/imgs/1.jpg" --det_model_di
<a name="LIGHTWEIGHT_RECOGNITION"></a>
### 1. Lightweight Chinese Recognition Model Inference
**Note**: The input shape used by the recognition model of `PP-OCRv3` is `3,48,320`, and the parameter `--rec_image_shape=3,48,320` needs to be added. If the recognition model of `PP-OCRv3` is not used, this parameter does not need to be set.
For lightweight Chinese recognition model inference, you can execute the following commands:
```
# download CRNN text recognition inference model
wget https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar
tar xf ch_PP-OCRv2_rec_infer.tar
wget https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar
tar xf ch_PP-OCRv3_rec_infer.tar
# run inference
python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/ch/word_4.jpg" --rec_model_dir="./ch_PP-OCRv2_rec_infer/"
python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_10.png" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --rec_image_shape=3,48,320
```
![](../imgs_words_en/word_10.png)
......@@ -71,7 +74,7 @@ python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/ch/word_4.jpg"
After executing the command, the prediction results (recognized text and score) of the above image will be printed on the screen.
```bash
Predicts of ./doc/imgs_words_en/word_10.png:('PAIN', 0.9897658)
Predicts of ./doc/imgs_words_en/word_10.png:('PAIN', 0.988671)
```
<a name="MULTILINGUAL_MODEL_INFERENCE"></a>
......@@ -117,20 +120,22 @@ After executing the command, the prediction results (classification angle and sc
<a name="CONCATENATION"></a>
## Text Detection Angle Classification and Recognition Inference Concatenation
**Note**: The input shape used by the recognition model of `PP-OCRv3` is `3,48,320`, and the parameter `--rec_image_shape=3,48,320` needs to be added. If the recognition model of `PP-OCRv3` is not used, this parameter does not need to be set.
When performing prediction, you need to specify the path of a single image or a folder of images through the parameter `image_dir`, the parameter `det_model_dir` specifies the path to detect the inference model, the parameter `cls_model_dir` specifies the path to angle classification inference model and the parameter `rec_model_dir` specifies the path to identify the inference model. The parameter `use_angle_cls` is used to control whether to enable the angle classification model. The parameter `use_mp` specifies whether to use multi-process to infer `total_process_num` specifies process number when using multi-process. The parameter . The visualized recognition results are saved to the `./inference_results` folder by default.
```shell
# use direction classifier
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --cls_model_dir="./inference/cls/" --rec_model_dir="./inference/ch_PP-OCRv2_rec_infer/" --use_angle_cls=true
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv3_det_infer/" --cls_model_dir="./cls/" --rec_model_dir="./ch_PP-OCRv2_rec_infer/" --use_angle_cls=true --rec_image_shape=3,48,320
# not use use direction classifier
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --rec_model_dir="./inference/ch_PP-OCRv2_rec_infer/" --use_angle_cls=false
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv2_det_infer/" --rec_model_dir="./ch_PP-OCRv2_rec_infer/" --use_angle_cls=false --rec_image_shape=3,48,320
# use multi-process
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./inference/ch_PP-OCRv2_det_infer/" --rec_model_dir="./inference/ch_PP-OCRv2_rec_infer/" --use_angle_cls=false --use_mp=True --total_process_num=6
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_PP-OCRv2_det_infer/" --rec_model_dir="./ch_PP-OCRv2_rec_infer/" --use_angle_cls=false --use_mp=True --total_process_num=6 --rec_image_shape=3,48,320
```
After executing the command, the recognition result image is as follows:
![](../imgs_results/system_res_00018069.jpg)
![](../imgs_results/system_res_00018069_v3.jpg)
......@@ -73,6 +73,8 @@ cd /path/to/ppocr_img
If you do not use the provided test image, you can replace the following `--image_dir` parameter with the corresponding test image path
**Note**: The whl package uses the `PP-OCRv3` model by default, and the input shape used by the recognition model is `3,48,320`, so if you use the recognition function, you need to add the parameter `--rec_image_shape 3,48,320`, if you do not use the default `PP- OCRv3` model, you do not need to set this parameter.
<a name="211-english-and-chinese-model"></a>
#### 2.1.1 Chinese and English Model
......@@ -80,15 +82,15 @@ If you do not use the provided test image, you can replace the following `--imag
* Detection, direction classification and recognition: set the parameter`--use_gpu false` to disable the gpu device
```bash
paddleocr --image_dir ./imgs_en/img_12.jpg --use_angle_cls true --lang en --use_gpu false
paddleocr --image_dir ./imgs_en/img_12.jpg --use_angle_cls true --lang en --use_gpu false --rec_image_shape 3,48,320
```
Output will be a list, each item contains bounding box, text and recognition confidence
```bash
[[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]]
[[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]]
[[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]]
[[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
[[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
[[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
......
```
......@@ -101,33 +103,33 @@ If you do not use the provided test image, you can replace the following `--imag
Output will be a list, each item only contains bounding box
```bash
[[756.0, 812.0], [805.0, 812.0], [805.0, 830.0], [756.0, 830.0]]
[[820.0, 803.0], [1085.0, 801.0], [1085.0, 836.0], [820.0, 838.0]]
[[393.0, 801.0], [715.0, 805.0], [715.0, 839.0], [393.0, 836.0]]
[[397.0, 802.0], [1092.0, 802.0], [1092.0, 841.0], [397.0, 841.0]]
[[397.0, 750.0], [1211.0, 750.0], [1211.0, 789.0], [397.0, 789.0]]
[[397.0, 702.0], [1209.0, 698.0], [1209.0, 734.0], [397.0, 738.0]]
......
```
* Only recognition: set `--det` to `false`
```bash
paddleocr --image_dir ./imgs_words_en/word_10.png --det false --lang en
paddleocr --image_dir ./imgs_words_en/word_10.png --det false --lang en --rec_image_shape 3,48,320
```
Output will be a list, each item contains text and recognition confidence
```bash
['PAIN', 0.990372]
['PAIN', 0.9934559464454651]
```
If you need to use the 2.0 model, please specify the parameter `--version PP-OCR`, paddleocr uses the 2.1 model by default(`--versioin PP-OCRv2`). More whl package usage can be found in [whl package](./whl_en.md)
If you need to use the 2.0 model, please specify the parameter `--version PP-OCR`, paddleocr uses the PP-OCRv3 model by default(`--versioin PP-OCRv3`). More whl package usage can be found in [whl package](./whl_en.md)
<a name="212-multi-language-model"></a>
#### 2.1.2 Multi-language Model
Paddleocr currently supports 80 languages, which can be switched by modifying the `--lang` parameter.
Paddleocr currently supports 80 languages, which can be switched by modifying the `--lang` parameter. PP-OCRv3 currently only supports Chinese and English models, and other multilingual models will be updated one after another.
``` bash
paddleocr --image_dir ./doc/imgs_en/254.jpg --lang=en
paddleocr --image_dir ./doc/imgs_en/254.jpg --lang=en --rec_image_shape 3,48,320
```
<div align="center">
......@@ -137,13 +139,9 @@ paddleocr --image_dir ./doc/imgs_en/254.jpg --lang=en
The result is a list, each item contains a text box, text and recognition confidence
```text
[('PHO CAPITAL', 0.95723116), [[66.0, 50.0], [327.0, 44.0], [327.0, 76.0], [67.0, 82.0]]]
[('107 State Street', 0.96311164), [[72.0, 90.0], [451.0, 84.0], [452.0, 116.0], [73.0, 121.0]]]
[('Montpelier Vermont', 0.97389287), [[69.0, 132.0], [501.0, 126.0], [501.0, 158.0], [70.0, 164.0]]]
[('8022256183', 0.99810505), [[71.0, 175.0], [363.0, 170.0], [364.0, 202.0], [72.0, 207.0]]]
[('REG 07-24-201706:59 PM', 0.93537045), [[73.0, 299.0], [653.0, 281.0], [654.0, 318.0], [74.0, 336.0]]]
[('045555', 0.99346405), [[509.0, 331.0], [651.0, 325.0], [652.0, 356.0], [511.0, 362.0]]]
[('CT1', 0.9988654), [[535.0, 367.0], [654.0, 367.0], [654.0, 406.0], [535.0, 406.0]]]
[[[67.0, 51.0], [327.0, 46.0], [327.0, 74.0], [68.0, 80.0]], ('PHOCAPITAL', 0.9944712519645691)]
[[[72.0, 92.0], [453.0, 84.0], [454.0, 114.0], [73.0, 122.0]], ('107 State Street', 0.9744491577148438)]
[[[69.0, 135.0], [501.0, 125.0], [501.0, 156.0], [70.0, 165.0]], ('Montpelier Vermont', 0.9357033967971802)]
......
```
......@@ -234,10 +232,10 @@ im_show.save('result.jpg')
Output will be a list, each item contains bounding box, text and recognition confidence
```bash
[[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]]
[[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]]
[[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]]
......
[[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
[[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
[[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
......
```
Visualization of results
......
......@@ -172,40 +172,42 @@ show help information
paddleocr -h
```
**Note**: The whl package uses the `PP-OCRv3` model by default, and the input shape used by the recognition model is `3,48,320`, so if you use the recognition function, you need to add the parameter `--rec_image_shape 3,48,320`, if you do not use the default `PP- OCRv3` model, you do not need to set this parameter.
* detection classification and recognition
```bash
paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --use_angle_cls true --lang en
paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --use_angle_cls true --lang en --rec_image_shape 3,48,320
```
Output will be a list, each item contains bounding box, text and recognition confidence
```bash
[[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]]
[[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]]
[[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]]
[[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
[[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
[[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
......
```
* detection and recognition
```bash
paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --lang en
paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --lang en --rec_image_shape 3,48,320
```
Output will be a list, each item contains bounding box, text and recognition confidence
```bash
[[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]]
[[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]]
[[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]]
[[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
[[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
[[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
......
```
* classification and recognition
```bash
paddleocr --image_dir PaddleOCR/doc/imgs_words_en/word_10.png --use_angle_cls true --det false --lang en
paddleocr --image_dir PaddleOCR/doc/imgs_words_en/word_10.png --use_angle_cls true --det false --lang en --rec_image_shape 3,48,320
```
Output will be a list, each item contains text and recognition confidence
```bash
['PAIN', 0.990372]
['PAIN', 0.9934559464454651]
```
* only detection
......@@ -215,20 +217,20 @@ paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --rec false
Output will be a list, each item only contains bounding box
```bash
[[756.0, 812.0], [805.0, 812.0], [805.0, 830.0], [756.0, 830.0]]
[[820.0, 803.0], [1085.0, 801.0], [1085.0, 836.0], [820.0, 838.0]]
[[393.0, 801.0], [715.0, 805.0], [715.0, 839.0], [393.0, 836.0]]
[[397.0, 802.0], [1092.0, 802.0], [1092.0, 841.0], [397.0, 841.0]]
[[397.0, 750.0], [1211.0, 750.0], [1211.0, 789.0], [397.0, 789.0]]
[[397.0, 702.0], [1209.0, 698.0], [1209.0, 734.0], [397.0, 738.0]]
......
```
* only recognition
```bash
paddleocr --image_dir PaddleOCR/doc/imgs_words_en/word_10.png --det false --lang en
paddleocr --image_dir PaddleOCR/doc/imgs_words_en/word_10.png --det false --lang en --rec_image_shape 3,48,320
```
Output will be a list, each item contains text and recognition confidence
```bash
['PAIN', 0.990372]
['PAIN', 0.9934559464454651]
```
* only classification
......@@ -366,5 +368,4 @@ im_show.save('result.jpg')
| cls | Enable classification when `ppocr.ocr` func exec((Use use_angle_cls in command line mode to control whether to start classification in the forward direction) | FALSE |
| show_log | Whether to print log| FALSE |
| type | Perform ocr or table structuring, the value is selected in ['ocr','structure'] | ocr |
| ocr_version | OCR Model version number, the current model support list is as follows: PP-OCRv2 support Chinese detection and recognition model, PP-OCR support Chinese detection, recognition and direction classifier, multilingual recognition model | PP-OCRv2 |
| structure_version | table structure Model version number, the current model support list is as follows: STRUCTURE support english table structure model | STRUCTURE |
| ocr_version | OCR Model version number, the current model support list is as follows: PP-OCRv3 support Chinese and English detection and recognition model and direction classifier model, PP-OCRv2 support Chinese detection and recognition model, PP-OCR support Chinese detection, recognition and direction classifier, multilingual recognition model | PP-OCRv3 |
......@@ -47,16 +47,46 @@ __all__ = [
]
SUPPORT_DET_MODEL = ['DB']
VERSION = '2.5'
VERSION = '2.5.0.1'
SUPPORT_REC_MODEL = ['CRNN']
BASE_DIR = os.path.expanduser("~/.paddleocr/")
DEFAULT_OCR_MODEL_VERSION = 'PP-OCR'
SUPPORT_OCR_MODEL_VERSION = ['PP-OCR', 'PP-OCRv2']
DEFAULT_STRUCTURE_MODEL_VERSION = 'STRUCTURE'
SUPPORT_STRUCTURE_MODEL_VERSION = ['STRUCTURE']
DEFAULT_OCR_MODEL_VERSION = 'PP-OCRv3'
SUPPORT_OCR_MODEL_VERSION = ['PP-OCR', 'PP-OCRv2', 'PP-OCRv3']
DEFAULT_STRUCTURE_MODEL_VERSION = 'PP-STRUCTURE'
SUPPORT_STRUCTURE_MODEL_VERSION = ['PP-STRUCTURE']
MODEL_URLS = {
'OCR': {
'PP-OCRv3': {
'det': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar',
},
'en': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar',
},
},
'rec': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
},
'en': {
'url':
'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar',
'dict_path': './ppocr/utils/en_dict.txt'
},
},
'cls': {
'ch': {
'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
}
},
},
'PP-OCRv2': {
'det': {
'ch': {
......@@ -72,7 +102,7 @@ MODEL_URLS = {
}
}
},
DEFAULT_OCR_MODEL_VERSION: {
'PP-OCR': {
'det': {
'ch': {
'url':
......@@ -173,7 +203,7 @@ MODEL_URLS = {
}
},
'STRUCTURE': {
DEFAULT_STRUCTURE_MODEL_VERSION: {
'PP-STRUCTURE': {
'table': {
'en': {
'url':
......@@ -198,16 +228,17 @@ def parse_args(mMain=True):
"--ocr_version",
type=str,
choices=SUPPORT_OCR_MODEL_VERSION,
default='PP-OCRv2',
default='PP-OCRv3',
help='OCR Model version, the current model support list is as follows: '
'1. PP-OCRv2 Support Chinese detection and recognition model. '
'2. PP-OCR support Chinese detection, recognition and direction classifier and multilingual recognition model.'
'1. PP-OCRv3 Support Chinese and English detection and recognition model, and direction classifier model'
'2. PP-OCRv2 Support Chinese detection and recognition model. '
'3. PP-OCR support Chinese detection, recognition and direction classifier and multilingual recognition model.'
)
parser.add_argument(
"--structure_version",
type=str,
choices=SUPPORT_STRUCTURE_MODEL_VERSION,
default='STRUCTURE',
default='PP-STRUCTURE',
help='Model version, the current model support list is as follows:'
' 1. STRUCTURE Support en table structure model.')
......
......@@ -194,5 +194,6 @@ dict 里各个字段说明如下
| layout | 前向中是否执行版面分析 | True |
| table | 前向中是否执行表格识别 | True |
| ocr | 对于版面分析中的非表格区域,是否执行ocr。当layout为False时会被自动设置为False | True |
| structure_version | 表格结构化模型版本,可选 PP-STRUCTURE。PP-STRUCTURE支持表格结构化模型 | PP-STRUCTURE |
大部分参数和PaddleOCR whl包保持一致,见 [whl包文档](../../doc/doc_ch/whl.md)
......@@ -194,5 +194,5 @@ Please refer to: [Documentation Visual Q&A](../vqa/README.md) .
| layout | Whether to perform layout analysis in forward | True |
| table | Whether to perform table recognition in forward | True |
| ocr | Whether to perform ocr for non-table areas in layout analysis. When layout is False, it will be automatically set to False | True |
| structure_version | table structure Model version number, the current model support list is as follows: PP-STRUCTURE support english table structure model | PP-STRUCTURE |
Most of the parameters are consistent with the PaddleOCR whl package, see [whl package documentation](../../doc/doc_en/whl.md)
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