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A cross platform OCR Library based on OnnxRuntime.

Project description

rapidocr-onnxruntime Package

1. Install package by pypi.

$ pip install rapidocr-onnxruntime

2. Use.

  • Run by script.

    import cv2
    from rapidocr_onnxruntime import RapidOCR
    
    rapid_ocr = RapidOCR()
    
    img_path = 'tests/test_files/ch_en_num.jpg'
    
    # Support:Union[str, np.ndarray, bytes, Path]
    # str
    result, elapse = rapid_ocr(img_path)
    
    # np.ndarray
    img = cv2.imread('tests/test_files/ch_en_num.jpg')
    result, elapse = rapid_ocr(img)
    
    # bytes
    with open(img_path, 'rb') as f:
        result, elapse = rapid_ocr(f.read())
    
    # Path
    result, elapse = rapid_ocr(Path(img_path))
    print(result)
    
    # result: [[dt_boxes], txt, score]
    # e.g.:[[left-top, right-top, right-down, left-top], '小明', '0.99']
    
    # elapse: [det_elapse, cls_elapse, rec_elapse]
    # all_elapse = det_elapse + cls_elapse + rec_elapse
    
    # If without valid texts, result: (None, None )
    
  • Run by command line.

    $ rapidocr_onnxruntime -h
    usage: rapidocr_onnxruntime [-h] -img IMG_PATH [-p] [--text_score TEXT_SCORE]
                                [--use_angle_cls USE_ANGLE_CLS]
                                [--use_text_det USE_TEXT_DET]
                                [--print_verbose PRINT_VERBOSE]
                                [--min_height MIN_HEIGHT]
                                [--width_height_ratio WIDTH_HEIGHT_RATIO]
                                [--det_use_cuda DET_USE_CUDA]
                                [--det_model_path DET_MODEL_PATH]
                                [--det_limit_side_len DET_LIMIT_SIDE_LEN]
                                [--det_limit_type {max,min}]
                                [--det_thresh DET_THRESH]
                                [--det_box_thresh DET_BOX_THRESH]
                                [--det_unclip_ratio DET_UNCLIP_RATIO]
                                [--det_use_dilation DET_USE_DILATION]
                                [--det_score_mode {slow,fast}]
                                [--cls_use_cuda CLS_USE_CUDA]
                                [--cls_model_path CLS_MODEL_PATH]
                                [--cls_image_shape CLS_IMAGE_SHAPE]
                                [--cls_label_list CLS_LABEL_LIST]
                                [--cls_batch_num CLS_BATCH_NUM]
                                [--cls_thresh CLS_THRESH]
                                [--rec_use_cuda REC_USE_CUDA]
                                [--rec_model_path REC_MODEL_PATH]
                                [--rec_img_shape REC_IMAGE_SHAPE]
                                [--rec_batch_num REC_BATCH_NUM]
    
    optional arguments:
    -h, --help            show this help message and exit
    -img IMG_PATH, --img_path IMG_PATH MUST
    -p, --print_cost
    
    Global:
    --text_score TEXT_SCORE
    --use_angle_cls USE_ANGLE_CLS
    --use_text_det USE_TEXT_DET
    --print_verbose PRINT_VERBOSE
    --min_height MIN_HEIGHT
    --width_height_ratio WIDTH_HEIGHT_RATIO
    
    Det:
    --det_use_cuda DET_USE_CUDA
    --det_model_path DET_MODEL_PATH
    --det_limit_side_len DET_LIMIT_SIDE_LEN
    --det_limit_type {max,min}
    --det_thresh DET_THRESH
    --det_box_thresh DET_BOX_THRESH
    --det_unclip_ratio DET_UNCLIP_RATIO
    --det_use_dilation DET_USE_DILATION
    --det_score_mode {slow,fast}
    
    Cls:
    --cls_use_cuda CLS_USE_CUDA
    --cls_model_path CLS_MODEL_PATH
    --cls_image_shape CLS_IMAGE_SHAPE
    --cls_label_list CLS_LABEL_LIST
    --cls_batch_num CLS_BATCH_NUM
    --cls_thresh CLS_THRESH
    
    Rec:
    --rec_use_cuda REC_USE_CUDA
    --rec_model_path REC_MODEL_PATH
    --rec_img_shape REC_IMAGE_SHAPE
    --rec_batch_num REC_BATCH_NUM
    
    $ rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg
    

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