5 def __init__(self, modelPath, labelPath, backendId=0, targetId=0):
18 self.
mean=[0.485, 0.456, 0.406]
19 self.
std=[0.229, 0.224, 0.225]
24 def _load_labels(self):
28 labels.append(line.strip())
33 return self.__class__.__name__
43 def _preprocess(self, image):
44 input_blob = (image / 255.0 - self.
mean) / self.
std
45 input_blob = input_blob.transpose(2, 0, 1)
46 input_blob = input_blob[np.newaxis, :, :, :]
47 input_blob = input_blob.astype(np.float32)
63 def _postprocess(self, output_blob):
66 class_id = np.argmax(o)
67 predicted_labels.append(self.
labels[class_id])
68 return predicted_labels