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@ -37,10 +37,10 @@ tar -xf inference.tar
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export PYTHONPATH=.
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# 预测image_dir指定的单张图像
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python tools/infer/predict_system.py --image_dir="/Demo.jpg" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/"
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python3 tools/infer/predict_system.py --image_dir="./demo.jpg" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/"
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# 预测image_dir指定的图像集合
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python tools/infer/predict_system.py --image_dir="/test_imgs/" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/"
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python3 tools/infer/predict_system.py --image_dir="./infer_imgs/" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/"
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```
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更多的文本检测、识别串联推理使用方式请参考文档教程中[基于推理引擎预测](./doc/inference.md)。
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@ -46,9 +46,11 @@ class DBPostProcess(object):
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bitmap = _bitmap
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height, width = bitmap.shape
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# img, contours, _ = cv2.findContours((bitmap * 255).astype(np.uint8), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
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contours, _ = cv2.findContours((bitmap * 255).astype(np.uint8),
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cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
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outs = cv2.findContours((bitmap * 255).astype(np.uint8), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
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if len(outs) == 3:
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img, contours, _ = outs[0], outs[1], outs[2]
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elif len(outs) == 2:
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contours, _ = outs[0], outs[1]
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num_contours = min(len(contours), self.max_candidates)
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boxes = np.zeros((num_contours, 4, 2), dtype=np.int16)
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@ -84,7 +84,7 @@ def sorted_boxes(dt_boxes):
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"""
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Sort text boxes in order from top to bottom, left to right
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args:
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dt_boxes(array):detected text boxes with shape [4, 2]
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dt_boxes(array):detected text boxes with shape [4, 2]
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return:
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sorted boxes(array) with shape [4, 2]
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"""
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@ -108,6 +108,7 @@ if __name__ == "__main__":
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is_visualize = True
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for image_file in image_file_list:
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img = cv2.imread(image_file)
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print(img.shape)
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if img is None:
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logger.info("error in loading image:{}".format(image_file))
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continue
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