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PaddleOCR
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enhance auto_log

This commit is contained in:
LDOUBLEV 2021-06-24 07:18:08 +00:00
parent 01c4ee5de0
commit ea60a03487
1 changed files with 29 additions and 1 deletions
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30
tools/infer/predict_det.py
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@ -34,6 +34,7 @@ from ppocr.postprocess import build_post_process
# import tools.infer.benchmark_utils as benchmark_utils # import tools.infer.benchmark_utils as benchmark_utils
logger = get_logger() logger = get_logger()
import auto_log
class TextDetector(object): class TextDetector(object):
@ -100,6 +101,22 @@ class TextDetector(object):
self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor( self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor(
args, 'det', logger) args, 'det', logger)
pid = os.getpid()
self.autolog = auto_log.AutoLogger(
model_name="det",
model_precision="fp32",
batch_size=1,
data_shape="dynamic",
save_path="./output/auto_log.lpg",
inference_config=self.config,
pids=pid,
process_name=None,
gpu_ids=0,
time_keys=[
'preprocess_time', 'inference_time', 'postprocess_time'
],
warmup=10)
def order_points_clockwise(self, pts): def order_points_clockwise(self, pts):
""" """
reference from: https://github.com/jrosebr1/imutils/blob/master/imutils/perspective.py reference from: https://github.com/jrosebr1/imutils/blob/master/imutils/perspective.py
@ -158,6 +175,9 @@ class TextDetector(object):
data = {'image': img} data = {'image': img}
st = time.time() st = time.time()
self.autolog.times.start()
data = transform(data, self.preprocess_op) data = transform(data, self.preprocess_op)
img, shape_list = data img, shape_list = data
if img is None: if img is None:
@ -166,6 +186,8 @@ class TextDetector(object):
shape_list = np.expand_dims(shape_list, axis=0) shape_list = np.expand_dims(shape_list, axis=0)
img = img.copy() img = img.copy()
self.autolog.times.stamp()
self.input_tensor.copy_from_cpu(img) self.input_tensor.copy_from_cpu(img)
self.predictor.run() self.predictor.run()
outputs = [] outputs = []
@ -173,6 +195,8 @@ class TextDetector(object):
output = output_tensor.copy_to_cpu() output = output_tensor.copy_to_cpu()
outputs.append(output) outputs.append(output)
self.autolog.times.stamp()
preds = {} preds = {}
if self.det_algorithm == "EAST": if self.det_algorithm == "EAST":
preds['f_geo'] = outputs[0] preds['f_geo'] = outputs[0]
@ -195,7 +219,9 @@ class TextDetector(object):
else: else:
dt_boxes = self.filter_tag_det_res(dt_boxes, ori_im.shape) dt_boxes = self.filter_tag_det_res(dt_boxes, ori_im.shape)
self.autolog.times.end(stamp=True)
et = time.time() et = time.time()
self.autolog.get_avg_mem_mb()
return dt_boxes, et - st return dt_boxes, et - st
@ -212,7 +238,7 @@ if __name__ == "__main__":
for i in range(10): for i in range(10):
res = text_detector(img) res = text_detector(img)
cpu_mem, gpu_mem, gpu_util = 0, 0, 0 text_detector.autolog.mem_info._start_subprocess()
if not os.path.exists(draw_img_save): if not os.path.exists(draw_img_save):
os.makedirs(draw_img_save) os.makedirs(draw_img_save)
@ -237,3 +263,5 @@ if __name__ == "__main__":
"det_res_{}".format(img_name_pure)) "det_res_{}".format(img_name_pure))
logger.info("The visualized image saved in {}".format(img_path)) logger.info("The visualized image saved in {}".format(img_path))
text_detector.autolog.report()