fix rec trt
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5f7d4b9fe1
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@ -277,7 +277,7 @@ def main(args):
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if args.warmup:
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img = np.random.uniform(0, 255, [32, 320, 3]).astype(np.uint8)
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for i in range(2):
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res = text_recognizer([img])
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res = text_recognizer([img] * int(args.rec_batch_num))
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for image_file in image_file_list:
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img, flag = check_and_read_gif(image_file)
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@ -231,13 +231,13 @@ def create_predictor(args, mode, logger):
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max_input_shape.update(max_pact_shape)
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opt_input_shape.update(opt_pact_shape)
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elif mode == "rec":
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min_input_shape = {"x": [1, 3, 32, 10]}
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min_input_shape = {"x": [args.rec_batch_num, 3, 32, 10]}
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max_input_shape = {"x": [args.rec_batch_num, 3, 32, 2000]}
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opt_input_shape = {"x": [512, 3, 32, 320]}
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opt_input_shape = {"x": [args.rec_batch_num, 3, 32, 320]}
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elif mode == "cls":
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min_input_shape = {"x": [1, 3, 48, 10]}
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min_input_shape = {"x": [args.rec_batch_num, 3, 48, 10]}
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max_input_shape = {"x": [args.rec_batch_num, 3, 48, 2000]}
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opt_input_shape = {"x": [512, 3, 48, 320]}
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opt_input_shape = {"x": [args.rec_batch_num, 3, 48, 320]}
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else:
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min_input_shape = {"x": [1, 3, 10, 10]}
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max_input_shape = {"x": [1, 3, 1000, 1000]}
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