parent
debea63ea7
commit
bfbb4b6e99
deploy/cpp_infer
doc
doc_ch
doc_en
ppocr/data
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@ -208,7 +208,7 @@ Execute the built executable file:
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./build/ppocr [--param1] [--param2] [...]
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```
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**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.
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**Note**:ppocr uses the `PP-OCRv3` model by default, and the input shape used by the recognition model is `3, 48, 320`, if you want to use the old version model, you should add the parameter `--rec_img_h=32`.
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Specifically,
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@ -222,7 +222,6 @@ Specifically,
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--det=true \
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--rec=true \
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--cls=true \
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--rec_img_h=48\
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```
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##### 2. det+rec:
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@ -234,7 +233,6 @@ Specifically,
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--det=true \
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--rec=true \
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--cls=false \
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--rec_img_h=48\
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```
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##### 3. det
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@ -254,7 +252,6 @@ Specifically,
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--det=false \
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--rec=true \
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--cls=true \
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--rec_img_h=48\
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```
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##### 5. rec
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@ -265,7 +262,6 @@ Specifically,
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--det=false \
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--rec=true \
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--cls=false \
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--rec_img_h=48\
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```
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##### 6. cls
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@ -330,7 +326,7 @@ More parameters are as follows,
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|rec_model_dir|string|-|Address of recognition inference model|
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|rec_char_dict_path|string|../../ppocr/utils/ppocr_keys_v1.txt|dictionary file|
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|rec_batch_num|int|6|batch size of recognition|
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|rec_img_h|int|32|image height of recognition|
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|rec_img_h|int|48|image height of recognition|
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|rec_img_w|int|320|image width of recognition|
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* Multi-language inference is also supported in PaddleOCR, you can refer to [recognition tutorial](../../doc/doc_en/recognition_en.md) for more supported languages and models in PaddleOCR. Specifically, if you want to infer using multi-language models, you just need to modify values of `rec_char_dict_path` and `rec_model_dir`.
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@ -213,7 +213,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
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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。
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**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。
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**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`, 如需使用旧版本的PP-OCR模型,则需要设置参数`--rec_img_h=32`。
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运行方式:
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@ -232,7 +232,6 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
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--det=true \
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--rec=true \
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--cls=true \
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--rec_img_h=48\
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```
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##### 2. 检测+识别:
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@ -244,7 +243,6 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
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--det=true \
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--rec=true \
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--cls=false \
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--rec_img_h=48\
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```
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##### 3. 检测:
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@ -264,7 +262,6 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
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--det=false \
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--rec=true \
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--cls=true \
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--rec_img_h=48\
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```
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##### 5. 识别:
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@ -275,7 +272,6 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
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--det=false \
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--rec=true \
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--cls=false \
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--rec_img_h=48\
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```
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##### 6. 分类:
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@ -339,7 +335,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
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|rec_model_dir|string|-|识别模型inference model地址|
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|rec_char_dict_path|string|../../ppocr/utils/ppocr_keys_v1.txt|字典文件|
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|rec_batch_num|int|6|识别模型batchsize|
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|rec_img_h|int|32|识别模型输入图像高度|
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|rec_img_h|int|48|识别模型输入图像高度|
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|rec_img_w|int|320|识别模型输入图像宽度|
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@ -47,7 +47,7 @@ DEFINE_string(rec_model_dir, "", "Path of rec inference model.");
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DEFINE_int32(rec_batch_num, 6, "rec_batch_num.");
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DEFINE_string(rec_char_dict_path, "../../ppocr/utils/ppocr_keys_v1.txt",
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"Path of dictionary.");
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DEFINE_int32(rec_img_h, 32, "rec image height");
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DEFINE_int32(rec_img_h, 48, "rec image height");
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DEFINE_int32(rec_img_w, 320, "rec image width");
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// ocr forward related
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@ -132,7 +132,9 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
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paddle_infer::Config config;
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config.SetModel(model_dir + "/inference.pdmodel",
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model_dir + "/inference.pdiparams");
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std::cout << "In PP-OCRv3, default rec_img_h is 48,"
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<< "if you use other model, you should set the param rec_img_h=32"
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<< std::endl;
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if (this->use_gpu_) {
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config.EnableUseGpu(this->gpu_mem_, this->gpu_id_);
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if (this->use_tensorrt_) {
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@ -101,8 +101,17 @@ cd /path/to/ppocr_img
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['韩国小馆', 0.994467]
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```
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**版本说明**
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paddleocr默认使用PP-OCRv3模型(`--ocr_version PP-OCRv3`),如需使用其他版本可通过设置参数`--ocr_version`,具体版本说明如下:
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| 版本名称 | 版本说明 |
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| --- | --- |
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| PP-OCRv3 | 支持中、英文检测和识别,方向分类器,支持多语种识别 |
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| PP-OCRv2 | 支持中英文的检测和识别,方向分类器,多语言暂未更新 |
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| PP-OCR | 支持中、英文检测和识别,方向分类器,支持多语种识别 |
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如需使用2.0模型,请指定参数`--ocr_version PP-OCR`,paddleocr默认使用PP-OCRv3模型(`--ocr_version PP-OCRv3`)。更多whl包使用可参考[whl包文档](./whl.md)
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如需新增自己训练的模型,可以在[paddleocr](../../paddleocr.py)中增加模型链接和字段,重新编译即可。
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更多whl包使用可参考[whl包文档](./whl.md)
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<a name="212"></a>
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@ -119,7 +119,18 @@ If you do not use the provided test image, you can replace the following `--imag
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['PAIN', 0.9934559464454651]
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```
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If you need to use the 2.0 model, please specify the parameter `--ocr_version PP-OCR`, paddleocr uses the PP-OCRv3 model by default(`--ocr_version PP-OCRv3`). More whl package usage can be found in [whl package](./whl_en.md)
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**Version**
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paddleocr uses the PP-OCRv3 model by default(`--ocr_version PP-OCRv3`). If you want to use other versions, you can set the parameter `--ocr_version`, the specific version description is as follows:
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| version name | description |
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| --- | --- |
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| PP-OCRv3 | support Chinese and English detection and recognition, direction classifier, support multilingual recognition |
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| PP-OCRv2 | only supports Chinese and English detection and recognition, direction classifier, multilingual model is not updated |
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| PP-OCR | support Chinese and English detection and recognition, direction classifier, support multilingual recognition |
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If you want to add your own trained model, you can add model links and keys in [paddleocr](../../paddleocr.py) and recompile.
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More whl package usage can be found in [whl package](./whl_en.md)
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<a name="212-multi-language-model"></a>
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#### 2.1.2 Multi-language Model
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@ -154,7 +154,13 @@ MODEL_URLS = {
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'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar',
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'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
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}
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}
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},
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'cls': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
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}
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},
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},
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'PP-OCR': {
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'det': {
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@ -33,7 +33,7 @@ class SimpleDataSet(Dataset):
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self.delimiter = dataset_config.get('delimiter', '\t')
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label_file_list = dataset_config.pop('label_file_list')
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data_source_num = len(label_file_list)
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ratio_list = dataset_config.get("ratio_list", [1.0])
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ratio_list = dataset_config.get("ratio_list", 1.0)
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if isinstance(ratio_list, (float, int)):
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ratio_list = [float(ratio_list)] * int(data_source_num)
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