104 lines
7.3 KiB
Markdown
104 lines
7.3 KiB
Markdown
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# Quick start of Chinese OCR model
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## 1. Prepare for the environment
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Please refer to [quick installation](./installation_en.md) to configure the PaddleOCR operating environment.
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* Note: Support the use of PaddleOCR through whl package installation，pelease refer [PaddleOCR Package](./whl_en.md).
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## 2.inference models
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The detection and recognition models on the mobile and server sides are as follows. For more models (including multiple languages), please refer to [PP-OCR v2.0 series model list](../doc_ch/models_list.md)
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| Model introduction | Model name | Recommended scene | Detection model | Direction Classifier | Recognition model |
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| ------------ | --------------- | ----------------|---- | ---------- | -------- |
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| Ultra-lightweight Chinese OCR model (8.1M) | ch_ppocr_mobile_v2.0_xx |Mobile-side/Server-side|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar)|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_pre.tar) |
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| Universal Chinese OCR model (143M) | ch_ppocr_server_v2.0_xx |Server-side |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar) |[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar) / [pretrained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_pre.tar) |
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* If `wget` is not installed in the windows environment, you can copy the link to the browser to download when downloading the model, then uncompress it and place it in the corresponding directory.
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Copy the download address of the `inference model` for detection and recognition in the table above, and uncompress them.
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```
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mkdir inference && cd inference
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# Download the detection model and unzip
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wget {url/of/detection/inference_model} && tar xf {name/of/detection/inference_model/package}
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# Download the recognition model and unzip
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wget {url/of/recognition/inference_model} && tar xf {name/of/recognition/inference_model/package}
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# Download the direction classifier model and unzip
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wget {url/of/classification/inference_model} && tar xf {name/of/classification/inference_model/package}
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cd ..
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```
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Take the ultra-lightweight model as an example:
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```
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mkdir inference && cd inference
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# Download the detection model of the ultra-lightweight Chinese OCR model and uncompress it
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wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_det_infer.tar
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# Download the recognition model of the ultra-lightweight Chinese OCR model and uncompress it
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wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar
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# Download the angle classifier model of the ultra-lightweight Chinese OCR model and uncompress it
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wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar && tar xf ch_ppocr_mobile_v2.0_cls_infer.tar
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cd ..
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```
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After decompression, the file structure should be as follows:
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```
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├── ch_ppocr_mobile_v2.0_cls_infer
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│ ├── inference.pdiparams
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│ ├── inference.pdiparams.info
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│ └── inference.pdmodel
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├── ch_ppocr_mobile_v2.0_det_infer
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│ ├── inference.pdiparams
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│ ├── inference.pdiparams.info
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│ └── inference.pdmodel
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├── ch_ppocr_mobile_v2.0_rec_infer
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├── inference.pdiparams
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├── inference.pdiparams.info
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└── inference.pdmodel
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```
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## 3. Single image or image set prediction
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* The following code implements text detection、angle class and recognition process. When performing prediction, you need to specify the path of a single image or image set through the parameter `image_dir`, the parameter `det_model_dir` specifies the path to detect the inference model, the parameter `rec_model_dir` specifies the path to identify the inference model, the parameter `use_angle_cls` specifies whether to use the direction classifier, the parameter `cls_model_dir` specifies the path to identify the direction classifier model, the parameter `use_space_char` specifies whether to predict the space char. The visual results are saved to the `./inference_results` folder by default.
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```bash
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# Predict a single image specified by image_dir
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python3 tools/infer/predict_system.py --image_dir="./doc/imgs/11.jpg" --det_model_dir="./inference/ch_ppocr_mobile_v2.0_det_infer/" --rec_model_dir="./inference/ch_ppocr_mobile_v2.0_rec_infer/" --cls_model_dir="./inference/ch_ppocr_mobile_v2.0_cls_infer/" --use_angle_cls=True --use_space_char=True
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# Predict imageset specified by image_dir
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python3 tools/infer/predict_system.py --image_dir="./doc/imgs/" --det_model_dir="./inference/ch_ppocr_mobile_v2.0_det_infer/" --rec_model_dir="./inference/ch_ppocr_mobile_v2.0_rec_infer/" --cls_model_dir="./inference/ch_ppocr_mobile_v2.0_cls_infer/" --use_angle_cls=True --use_space_char=True
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# If you want to use the CPU for prediction, you need to set the use_gpu parameter to False
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python3 tools/infer/predict_system.py --image_dir="./doc/imgs/11.jpg" --det_model_dir="./inference/ch_ppocr_mobile_v2.0_det_infer/" --rec_model_dir="./inference/ch_ppocr_mobile_v2.0_rec_infer/" --cls_model_dir="./inference/ch_ppocr_mobile_v2.0_cls_infer/" --use_angle_cls=True --use_space_char=True --use_gpu=False
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```
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- Universal Chinese OCR model
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Please follow the above steps to download the corresponding models and update the relevant parameters, The example is as follows.
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```
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# Predict a single image specified by image_dir
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python3 tools/infer/predict_system.py --image_dir="./doc/imgs/11.jpg" --det_model_dir="./inference/ch_ppocr_server_v2.0_det_infer/" --rec_model_dir="./inference/ch_ppocr_server_v2.0_rec_infer/" --cls_model_dir="./inference/ch_ppocr_mobile_v2.0_cls_infer/" --use_angle_cls=True --use_space_char=True
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```
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* Note
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- If you want to use the recognition model which does not support space char recognition, please update the source code to the latest version and add parameters `--use_space_char=False`.
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- If you do not want to use direction classifier, please update the source code to the latest version and add parameters `--use_angle_cls=False`.
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For more text detection and recognition tandem reasoning, please refer to the document tutorial
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: [Inference with Python inference engine](./inference_en.md)。
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In addition, the tutorial also provides other deployment methods for the Chinese OCR model:
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- [Server-side C++ inference](../../deploy/cpp_infer/readme_en.md)
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- [Service deployment](../../deploy/hubserving)
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- [End-to-end deployment](https://github.com/PaddlePaddle/PaddleOCR/tree/develop/deploy/lite)
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