Save recognition inference logs to file (#12542)
* Save recognition inference logs to file * Formatted code with blackpull/12565/head
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@ -37,7 +37,9 @@ logger = get_logger()
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class TextRecognizer(object):
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def __init__(self, args):
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def __init__(self, args, logger=None):
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if logger is None:
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logger = get_logger()
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self.rec_image_shape = [int(v) for v in args.rec_image_shape.split(",")]
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self.rec_batch_num = args.rec_batch_num
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self.rec_algorithm = args.rec_algorithm
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@ -157,7 +159,7 @@ class TextRecognizer(object):
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model_precision=args.precision,
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batch_size=args.rec_batch_num,
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data_shape="dynamic",
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save_path=None, # args.save_log_path,
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save_path=None, # not used if logger is not None
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inference_config=self.config,
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pids=pid,
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process_name=None,
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@ -701,14 +703,25 @@ class TextRecognizer(object):
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def main(args):
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image_file_list = get_image_file_list(args.image_dir)
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text_recognizer = TextRecognizer(args)
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valid_image_file_list = []
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img_list = []
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# logger
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log_file = args.save_log_path
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if os.path.is_dir(args.save_log_path) or (
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not os.path.exists(args.save_log_path) and args.save_log_path.endswith("/")
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):
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log_file = os.path.join(log_file, "benchmark_recognition.log")
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logger = get_logger(log_file=log_file)
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# create text recognizer
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text_recognizer = TextRecognizer(args)
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logger.info(
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"In PP-OCRv3, rec_image_shape parameter defaults to '3, 48, 320', "
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"if you are using recognition model with PP-OCRv2 or an older version, please set --rec_image_shape='3,32,320"
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)
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# warmup 2 times
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if args.warmup:
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img = np.random.uniform(0, 255, [48, 320, 3]).astype(np.uint8)
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