Moved image normalization into onnx models.

extras/easypose/detection.py

@@ -19,19 +19,12 @@ class RTMDet(BaseModel):
         self.dy = 0
         self.scale = 0
 
-        norm_mean = -1 * np.array([123.675, 116.28, 103.53])
-        norm_std = 1.0 / np.array([58.395, 57.12, 57.375])
-        self.norm_mean = np.reshape(norm_mean, (1, 1, 3)).astype(np.float32)
-        self.norm_std = np.reshape(norm_std, (1, 1, 3)).astype(np.float32)
-
     def preprocess(self, image: np.ndarray):
         th, tw = self.input_shape[2:]
         tensor, self.dx, self.dy, self.scale = letterbox(
             image, (tw, th), fill_value=114
         )
         tensor = tensor.astype(np.float32, copy=False)
-        tensor += self.norm_mean
-        tensor *= self.norm_std
         tensor = tensor[..., ::-1]
         tensor = np.expand_dims(tensor, axis=0).transpose((0, 3, 1, 2))
         return tensor