未验证 提交 cdd98d08 编写于 作者: D Double_V 提交者: GitHub

Update predict_det.py

上级 e4d49819
...@@ -174,8 +174,9 @@ class TextDetector(object): ...@@ -174,8 +174,9 @@ class TextDetector(object):
data = {'image': img} data = {'image': img}
st = time.time() st = time.time()
self.autolog.times.start() if args.benchmark:
self.autolog.times.start()
data = transform(data, self.preprocess_op) data = transform(data, self.preprocess_op)
img, shape_list = data img, shape_list = data
...@@ -185,7 +186,8 @@ class TextDetector(object): ...@@ -185,7 +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() if args.benchmark:
self.autolog.times.stamp()
self.input_tensor.copy_from_cpu(img) self.input_tensor.copy_from_cpu(img)
self.predictor.run() self.predictor.run()
...@@ -193,8 +195,8 @@ class TextDetector(object): ...@@ -193,8 +195,8 @@ class TextDetector(object):
for output_tensor in self.output_tensors: for output_tensor in self.output_tensors:
output = output_tensor.copy_to_cpu() output = output_tensor.copy_to_cpu()
outputs.append(output) outputs.append(output)
if args.benchmark:
self.autolog.times.stamp() self.autolog.times.stamp()
preds = {} preds = {}
if self.det_algorithm == "EAST": if self.det_algorithm == "EAST":
...@@ -218,7 +220,8 @@ class TextDetector(object): ...@@ -218,7 +220,8 @@ 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) if args.benchmark:
self.autolog.times.end(stamp=True)
et = time.time() et = time.time()
return dt_boxes, et - st return dt_boxes, et - st
...@@ -259,6 +262,7 @@ if __name__ == "__main__": ...@@ -259,6 +262,7 @@ if __name__ == "__main__":
"det_res_{}".format(img_name_pure)) "det_res_{}".format(img_name_pure))
cv2.imwrite(img_path, src_im) cv2.imwrite(img_path, src_im)
logger.info("The visualized image saved in {}".format(img_path)) logger.info("The visualized image saved in {}".format(img_path))
text_detector.autolog.report() if args.benchmark:
text_detector.autolog.report()
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