The visual text detection results are saved to the ./inference_results folder by default, and the name of the result file is prefixed with'det_res'. Examples of results are as follows:
The visual text detection results are saved to the ./inference_results folder by default, and the name of the result file is prefixed with'det_res'. Examples of results are as follows:
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@@ -42,12 +42,12 @@ Set as `limit_type='min', det_limit_side_len=960`, it means that the shortest si
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@@ -42,12 +42,12 @@ Set as `limit_type='min', det_limit_side_len=960`, it means that the shortest si
If the resolution of the input picture is relatively large and you want to use a larger resolution prediction, you can set det_limit_side_len to the desired value, such as 1216:
If the resolution of the input picture is relatively large and you want to use a larger resolution prediction, you can set det_limit_side_len to the desired value, such as 1216:
@@ -78,10 +79,12 @@ Predicts of ./doc/imgs_words_en/word_10.png:('PAIN', 0.9897658)
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@@ -78,10 +79,12 @@ Predicts of ./doc/imgs_words_en/word_10.png:('PAIN', 0.9897658)
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### 2. Multilingaul Model Inference
### 2. Multilingaul Model Inference
If you need to predict other language models, when using inference model prediction, you need to specify the dictionary path used by `--rec_char_dict_path`. At the same time, in order to get the correct visualization results,
If you need to predict [other language models](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.3/doc/doc_ch/models_list.md#%E5%A4%9A%E8%AF%AD%E8%A8%80%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B), when using inference model prediction, you need to specify the dictionary path used by `--rec_char_dict_path`. At the same time, in order to get the correct visualization results,
You need to specify the visual font path through `--vis_font_path`. There are small language fonts provided by default under the `doc/fonts` path, such as Korean recognition:
You need to specify the visual font path through `--vis_font_path`. There are small language fonts provided by default under the `doc/fonts` path, such as Korean recognition: