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Save detection inference logs to file (#12042)

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* Save detection inference logs to file

* Minor fix on save_log_path

* Formatted with black

* If logger is None: get_logger()
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Alex Pasquali 2024-05-29 05:19:47 +02:00 committed by GitHub
parent 92c59844f7
commit 6e7a1b871d
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1 changed files with 15 additions and 5 deletions
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20
tools/infer/predict_det.py
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@ -32,11 +32,11 @@ from ppocr.data import create_operators, transform
from ppocr.postprocess import build_post_process from ppocr.postprocess import build_post_process
import json import json
logger = get_logger()
class TextDetector(object): class TextDetector(object):
def __init__(self, args): def __init__(self, args, logger=None):
if logger is None:
logger = get_logger()
self.args = args self.args = args
self.det_algorithm = args.det_algorithm self.det_algorithm = args.det_algorithm
self.use_onnx = args.use_onnx self.use_onnx = args.use_onnx
@ -158,7 +158,7 @@ class TextDetector(object):
model_precision=args.precision, model_precision=args.precision,
batch_size=1, batch_size=1,
data_shape="dynamic", data_shape="dynamic",
save_path=None, save_path=None, # not used if logger is not None
inference_config=self.config, inference_config=self.config,
pids=pid, pids=pid,
process_name=None, process_name=None,
@ -398,11 +398,21 @@ class TextDetector(object):
if __name__ == "__main__": if __name__ == "__main__":
args = utility.parse_args() args = utility.parse_args()
image_file_list = get_image_file_list(args.image_dir) image_file_list = get_image_file_list(args.image_dir)
text_detector = TextDetector(args)
total_time = 0 total_time = 0
draw_img_save_dir = args.draw_img_save_dir draw_img_save_dir = args.draw_img_save_dir
os.makedirs(draw_img_save_dir, exist_ok=True) os.makedirs(draw_img_save_dir, exist_ok=True)
# logger
log_file = args.save_log_path
if os.path.isdir(args.save_log_path) or (
not os.path.exists(args.save_log_path) and args.save_log_path.endswith("/")
):
log_file = os.path.join(log_file, "benchmark_detection.log")
logger = get_logger(log_file=log_file)
# create text detector
text_detector = TextDetector(args, logger)
if args.warmup: if args.warmup:
img = np.random.uniform(0, 255, [640, 640, 3]).astype(np.uint8) img = np.random.uniform(0, 255, [640, 640, 3]).astype(np.uint8)
for i in range(2): for i in range(2):