crosstyan/RapidPoseTriangulation
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Speed up preprocessing.

Browse Source
This commit is contained in:
Daniel
2024-11-29 16:19:06 +01:00
parent 93d4611a91
commit 1b5e0c44e3
4 changed files with 24 additions and 21 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
extras/easypose/pose.py
View File

@ -43,13 +43,17 @@ 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 -= np.array((123.675, 116.28, 103.53))
tensor /= np.array((58.395, 57.12, 57.375))
tensor = (
np.expand_dims(tensor, axis=0).transpose((0, 3, 1, 2)).astype(np.float32)
)
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
def postprocess(self, tensor: List[np.ndarray]):