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Merge pull request #7217 from andyjpaddle/fix_sar_export
fix sar export
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commit
8210d717ff
@ -79,7 +79,7 @@ python3 tools/export_model.py -c configs/rec/rec_r31_sar.yml -o Global.pretraine
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SAR文本识别模型推理,可以执行如下命令:
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```
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python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/en/word_1.png" --rec_model_dir="./inference/rec_sar/" --rec_image_shape="3, 48, 48, 160" --rec_char_type="ch" --rec_algorithm="SAR" --rec_char_dict_path="ppocr/utils/dict90.txt" --max_text_length=30 --use_space_char=False
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python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/en/word_1.png" --rec_model_dir="./inference/rec_sar/" --rec_image_shape="3, 48, 48, 160" --rec_algorithm="SAR" --rec_char_dict_path="ppocr/utils/dict90.txt" --max_text_length=30 --use_space_char=False
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```
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<a name="4-2"></a>
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@ -79,7 +79,7 @@ python3 tools/export_model.py -c configs/rec/rec_r31_sar.yml -o Global.pretraine
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For SAR text recognition model inference, the following commands can be executed:
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```
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python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/en/word_1.png" --rec_model_dir="./inference/rec_sar/" --rec_image_shape="3, 48, 48, 160" --rec_char_type="ch" --rec_algorithm="SAR" --rec_char_dict_path="ppocr/utils/dict90.txt" --max_text_length=30 --use_space_char=False
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python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/en/word_1.png" --rec_model_dir="./inference/rec_sar/" --rec_image_shape="3, 48, 48, 160" --rec_algorithm="SAR" --rec_char_dict_path="ppocr/utils/dict90.txt" --max_text_length=30 --use_space_char=False
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```
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<a name="4-2"></a>
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@ -58,6 +58,8 @@ def export_single_model(model,
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other_shape = [
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paddle.static.InputSpec(
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shape=[None, 3, 48, 160], dtype="float32"),
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[paddle.static.InputSpec(
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shape=[None], dtype="float32")]
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]
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model = to_static(model, input_spec=other_shape)
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elif arch_config["algorithm"] == "SVTR":
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@ -232,4 +234,4 @@ def main():
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if __name__ == "__main__":
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main()
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main()
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@ -439,7 +439,8 @@ class TextRecognizer(object):
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valid_ratios = np.concatenate(valid_ratios)
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inputs = [
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norm_img_batch,
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valid_ratios,
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np.array(
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[valid_ratios], dtype=np.float32),
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]
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if self.use_onnx:
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input_dict = {}
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