Moved image normalization into onnx models.

extras/easypose/README.md

@@ -2,8 +2,17 @@
 
 Code files originally from: https://github.com/Dominic23331/EasyPose.git
 
+<br>
+
 ```bash
 docker build --progress=plain -f extras/easypose/dockerfile -t rpt_easypose .
 
 ./extras/easypose/run_container.sh
 ```
+
+```bash
+export CUDA_VISIBLE_DEVICES=0
+
+python3 /RapidPoseTriangulation/scripts/test_triangulate.py
+python3 /RapidPoseTriangulation/scripts/test_skelda_dataset.py
+```

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

extras/easypose/pose.py

@@ -43,16 +43,9 @@ class SimCC(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):
         tensor, self.dx, self.dy, self.scale = image, 0, 0, 1
         tensor = tensor.astype(np.float32, copy=False)
-        tensor += self.norm_mean
-        tensor *= self.norm_std
         tensor = np.expand_dims(tensor, axis=0).transpose((0, 3, 1, 2))
         return tensor