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Fix bugs and Update README

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# Contributors
None
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Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
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README.md
View file @ 01ae9eae
......@@ -13,44 +13,89 @@ https://arxiv.org/pdf/2205.00159.pdf
cls模型用mobilenetv3实现通用分类，参考论文如下：
https://arxiv.org/pdf/1905.02244.pdf
## 模型结构
det:
定位模型：
<div align=center>
<img src="./configs/det/dbnet-arc.png"/>
</div>
![image](https://developer.sourcefind.cn/codes/modelzoo/paddleocr/-/raw/main/configs/det/dbnet-arc.png)
识别模型:
<div align=center>
<img src="./configs/rec/SVTR-arc.png"/>
</div>
rec:
分类模型：
<div align=center>
<img src="./configs/cls/mobilenetv3-arc.png"/>
</div>
![image](https://developer.sourcefind.cn/codes/modelzoo/paddleocr/-/raw/main/configs/rec/SVTR-arc.png)
## 算法原理
cls:
<div align=center>
<img src="./configs/ocr.png"/>
</div>
![image](https://developer.sourcefind.cn/codes/modelzoo/paddleocr/-/raw/main/configs/cls/mobilenetv3-arc.png)
## 算法原理
![image](https://developer.sourcefind.cn/codes/modelzoo/paddleocr/-/raw/main/configs/ocr.png)
## 环境配置
在[光源](https://sourcefind.cn/#/main-page)可拉取训练以及推理的docker镜像，在[光合开发者社区](https://cancon.hpccube.com:65024/4/main/)可下载paddle、onnxruntime安装包。PaddleOCR推荐的镜像如下：
```
```bash
docker pull image.sourcefind.cn:5000/dcu/admin/base/paddlepaddle:2.5.2-ubuntu20.04-dtk24.04.1-py3.8
docker run -d -t --privileged --device=/dev/kfd --device=/dev/dri/ --shm-size 64g --network=host -v `pwd`:/挂在目录 -v /opt/hyhal:/opt/hyhal:ro --group-add video --name paddleocr-test image.sourcefind.cn:5000/dcu/admin/base/paddlepaddle:2.5.2-ubuntu20.04-dtk24.04.1-py3.8
docker exec -it paddleocr-test bash
pip3 install -r requirements.txt
pip3 install onnxruntime-1.15.0+das1.1.git739f24d.abi1.dtk2404-cp38-cp38-manylinux_2_31_x86_64.whl
pip3 install numpy==1.23.4
pip3 install numpy==1.23.4
wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/pretrained/MobileNetV3_large_x0_5_pretrained.pdparams
wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar
```
## 数据集
推荐使用icdar2015数据集[icdar2015](https://rrc.cvc.uab.es/?ch=4&com=downloads)。
检测模型训练集文件结构
```
/PaddleOCR/train_data/icdar2015/text_localization/
└─ icdar_c4_train_imgs/ Training data of icdar dataset
└─ ch4_test_images/ Testing data of icdar dataset
### 检测模型数据集
label数据准备有以下两个方法，二选一即可
```bash
cd train_data/icdar2015/text_localization/
# 方法一：label数据下载
wget -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/train_icdar2015_label.txt
wget -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/test_icdar2015_label.txt
# 方法二：将官网下载的标签文件转换为 train_icdar2015_label.txt、test_icdar2015_label.txt
python ppocr/utils/gen_label.py --mode="det" --root_path="/path/to/ch4_training_images/" \
--input_path="/path/to/ch4_training_localization_transcription_gt" \
--output_label="train_data/icdar2015/text_localization/train_icdar2015_label.txt"
python ppocr/utils/gen_label.py --mode="det" --root_path="/path/to/ch4_test_images/" \
--input_path="/path/to/Challenge4_Test_Task1_GT" \
--output_label="train_data/icdar2015/text_localization/test_icdar2015_label.txt"
```
准备完成的数据目录结构如下:
```
|-train_data/icdar2015/text_localization/
|- ch4_training_images/ Training data of icdar dataset
|- ch4_test_images/ Testing data of icdar dataset
└─ train_icdar2015_label.txt Training annotation of icdar dataset
└─ test_icdar2015_label.txt Test annotation of icdar dataset
```
识别模型训练集文件结构
### 识别模型数据集
label数据准备有以下两个方法，二选一即可
```bash
cd train_data/rec
# 方法一：label数据下载
# 训练集标签
wget -P ./train_data/rec https://paddleocr.bj.bcebos.com/dataset/rec_gt_train.txt
# 测试集标签
wget -P ./train_data/rec https://paddleocr.bj.bcebos.com/dataset/rec_gt_test.txt
# 方法二：将官网下载的标签文件转换为 rec_gt_train.txt、rec_gt_test.txt
python ppocr/utils/gen_label.py --mode="rec" --input_path="{path/of/train/label}" --output_label="rec_gt_train.txt"
python ppocr/utils/gen_label.py --mode="rec" --input_path="{path/of/test/label}" --output_label="rec_gt_test.txt"
```
准备完成的数据目录结构如下:
```
|-train_data
|-rec
......@@ -60,82 +105,97 @@ wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_P
|- word_002.jpg
|- word_003.jpg
| ...
|-ic15_data
|- rec_gt_test.txt
|- test
|- word_001.jpg
|- word_002.jpg
|- word_003.jpg
| ...
|- rec_gt_test.txt
|- test
|- word_001.jpg
|- word_002.jpg
|- word_003.jpg
| ...
```
## 训练
> 数据路径请根据实际准备数据路径修改`config`下的`yml`文件
检测模型
### 检测模型
```
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/train.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
```
识别模型
### 识别模型
```
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/train.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pretrained_model=./pretrain_models/en_PP-OCRv3_rec_train/best_accuracy
```
### 测试
### 测试(paddle)
检测模型
#### 检测模型
- Paddle
```
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/eval.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./output/db_mv3/best_accuracy.pdparams
```
识别模型
- ort
```
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/eval.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pretrained_model=./output/v3_en_mobile/best_accuracy.pdparams
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/eval.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det.onnx --use_onnx=true
```
### 测试(ort)
检测模型
#### 识别模型
- Paddle
```
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/eval.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det.onnx --use_onnx=true
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/eval.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pretrained_model=./output/v3_en_mobile/best_accuracy.pdparams
```
识别模型
- ort
```
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/eval.py -c configs/rec/PP-OCRv3/ch_PP-OCRv3_rec.yml -o Global.pretrained_model=./ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec.onnx --use_onnx=true
```
## 推理
### 推理(paddle)
```
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/" --det_model_dir="./ch_PP-OCRv3_det_infer/" --cls_model_dir="./ch_ppocr_mobile_v2.0_cls_infer/" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --use_angle_cls=true --rec_image_shape=3,48,320 --warmup=1
```
### 推理(ort)
### paddle
```bash
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/" --det_model_dir="./ch_PP-OCRv3_det_infer/" --cls_model_dir="./ch_ppocr_mobile_v2.0_cls_infer/" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --use_angle_cls=true --rec_image_shape=3,48,320 --warmup=1
```
### ort
```bash
python3 tools/infer/predict_system.py --image_dir="./doc/imgs/" --det_model_dir="./ch_PP-OCRv3_det_infer/ch_PP-OCRv3_det.onnx" --cls_model_dir="./ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.onnx" --rec_model_dir="./ch_PP-OCRv3_rec_infer/ch_PP-OCRv3_rec.onnx" --use_onnx=true --use_angle_cls=true --rec_image_shape=3,48,320 --warmup=1
```
## result
![image](https://developer.sourcefind.cn/codes/modelzoo/paddleocr/-/raw/main/inference_results/08.jpg)
### 精度
<div align=center>
<img src="./inference_results/08.jpg"/>
</div>
检测模型测试
### 精度
#### paddle
- 检测模型测试
| Model | Precision | Recall |
| :------: | :------: |:------: |
| det | 0.7054 | 0.7193 |
识别模型测试
| Model | Acc |
- 识别模型测试
| Model | Acc |
| :------: | :------: |
| rec | 0.6490 |
| rec | 0.6490 |
检测模型测试(ort)
#### ort
- 检测模型测试
| Model | Precision | Recall |
| :------: | :------: |:------: |
| det | 0.5097 | 0.4068 |
识别模型测试(ort)
| Model | Acc |
- 识别模型测试
| Model | Acc |
| :------: | :------: |
| rec | 0.6076 |
| rec | 0.6076 |
## 应用场景
### 算法类别
ocr
OCR
### 热点应用行业
制造,金融,交通,教育,医疗
`制造,金融,交通,教育,医疗`
## 源码仓库及问题反馈
https://developer.sourcefind.cn/codes/modelzoo/paddleocr
## 参考资料
* [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)
- https://developer.sourcefind.cn/codes/modelzoo/paddleocr
## 参考资料
- https://github.com/PaddlePaddle/PaddleOCR
configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml
View file @ 01ae9eae
......@@ -65,7 +65,7 @@ Loss:
- CTCLoss:
- SARLoss:
PostProcess:
PostProcess:
name: CTCLabelDecode
Metric:
......@@ -107,9 +107,9 @@ Train:
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/rec/ic15_data/
data_dir: ./train_data/rec/
label_file_list:
- ./train_data/rec/ic15_data/rec_gt_test.txt
- ./train_data/rec/rec_gt_test.txt
transforms:
- DecodeImage:
img_mode: BGR
......
model.properties
View file @ 01ae9eae
# 模型唯一标识
modelCode = 205
modelCode=205
# 模型名称
modelName=PaddleOCR_paddle_onnxruntime
# 模型描述
modelDescription=paddleocr_paddle_onnxruntime是一个实现字符检测和识别的模型
modelDescription=paddleocr_paddle_onnxruntime是一个实现字符检测和识别的模型。
# 应用场景
appScenario=推理,训练,OCR,制造,金融,交通,教育,医疗
# 框架类型
frameType=paddle,onnxruntime
# 加速卡类型
accelerateType=K100AI
\ No newline at end of file
ppocr/utils/gen_label.py 0 → 100644
View file @ 01ae9eae
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import argparse
import json
def gen_rec_label(input_path, out_label):
with open(out_label, 'w') as out_file:
with open(input_path, 'r') as f:
for line in f.readlines():
tmp = line.strip('\n').replace(" ", "").split(',')
img_path, label = tmp[0], tmp[1]
label = label.replace("\"", "")
out_file.write(img_path + '\t' + label + '\n')
def gen_det_label(root_path, input_dir, out_label):
with open(out_label, 'w') as out_file:
for label_file in os.listdir(input_dir):
img_path = root_path + label_file[3:-4] + ".jpg"
label = []
with open(
os.path.join(input_dir, label_file), 'r',
encoding='utf-8-sig') as f:
for line in f.readlines():
tmp = line.strip("\n\r").replace("\xef\xbb\xbf",
"").split(',')
points = tmp[:8]
s = []
for i in range(0, len(points), 2):
b = points[i:i + 2]
b = [int(t) for t in b]
s.append(b)
result = {"transcription": tmp[8], "points": s}
label.append(result)
out_file.write(img_path + '\t' + json.dumps(
label, ensure_ascii=False) + '\n')
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
'--mode',
type=str,
default="rec",
help='Generate rec_label or det_label, can be set rec or det')
parser.add_argument(
'--root_path',
type=str,
default=".",
help='The root directory of images.Only takes effect when mode=det ')
parser.add_argument(
'--input_path',
type=str,
default=".",
help='Input_label or input path to be converted')
parser.add_argument(
'--output_label',
type=str,
default="out_label.txt",
help='Output file name')
args = parser.parse_args()
if args.mode == "rec":
print("Generate rec label")
gen_rec_label(args.input_path, args.output_label)
elif args.mode == "det":
gen_det_label(args.root_path, args.input_path, args.output_label)
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