@@ -190,7 +146,7 @@ Output will be a list, each item contains text and recognition confidence
| gpu_mem | GPU memory size used for initialization | 8000M |
| image_dir | The images path or folder path for predicting when used by the command line | |
| det_algorithm | Type of detection algorithm selected | DB |
| det_model_name | There are two ways to use: 1. The name of the detection algorithm which must be in the support list(only ch_det_mv3_db is built in currently), and the supported list will be displayed when the wrong parameter is passed in. 2. The path of the inference model that has been converted by yourself. At this time, the model path must contains model and params files. When choosing this method, you need to give the name of det_algorithm | ch_det_mv3_db |
| det_model_dir | the text detection inference model folder. There are two ways to transfer parameters, 1. None: Automatically download the built-in model to `~/.paddleocr/det`; 2. The path of the inference model converted by yourself, the model and params files must be included in the model path | None |
| det_max_side_len | The maximum size of the long side of the image. When the long side exceeds this value, the long side will be resized to this size, and the short side will be scaled proportionally | 960 |
| det_db_thresh | Binarization threshold value of DB output map | 0.3 |
| det_db_box_thresh | The threshold value of the DB output box. Boxes score lower than this value will be discarded | 0.5 |
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@@ -199,13 +155,13 @@ Output will be a list, each item contains text and recognition confidence
| det_east_cover_thresh | The threshold value of the EAST output box. Boxes score lower than this value will be discarded | 0.1 |
| det_east_nms_thresh | The NMS threshold value of EAST model output box | 0.2 |
| rec_algorithm | Type of recognition algorithm selected | CRNN |
| rec_model_name | There are two ways to use: 1. The name of the recognition algorithm which must be in the support list(only supports CRNN, Rosetta, STAR, RARE and other algorithms currently, but only ch_rec_mv3_crnn_enhance is built-in), and the supported list will be displayed when the wrong parameter is passed in. 2. The path of the inference model that has been converted by yourself. At this time, the model path must contains model and params files. When choosing this method, you need to give the name of rec_algorithm | ch_rec_mv3_crnn_enhance |
| rec_model_dir | the text recognition inference model folder. There are two ways to transfer parameters, 1. None: Automatically download the built-in model to `~/.paddleocr/rec`; 2. The path of the inference model converted by yourself, the model and params files must be included in the model path | None |
| rec_char_type | Character type of recognition algorithm, Chinese (ch) or English (en) | ch |
| rec_batch_num | When performing recognition, the batchsize of forward images | 30 |
| rec_char_dict_path | the alphabet path which needs to be modified to your own path when `rec_model_Name` use mode 2 | |
| max_text_length | The maximum text length that the recognition algorithm can recognize | 25 |
| rec_char_dict_path | the alphabet path which needs to be modified to your own path when `rec_model_Name` use mode 2 | ./ppocr/utils/ppocr_keys_v1.txt |
| use_space_char | Whether to recognize spaces | TRUE |
| enable_mkldnn | Whether to enable mkldnn | FALSE |
| model_storage_directory | Download model save path when det_model_name or rec_model_name use mode 1 | ～/.paddleocr |
| det | Enable detction when `ppocr.ocr` func exec | TRUE |
