We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
将yolox利用onnxruntime推理时模型输出后结果需要利用下面代码映射到原图上,但是直接利用pth进行推理时,没有看到这一步,这个是为什么? def demo_postprocess(outputs, img_size, p6=False): grids = [] expanded_strides = [] if not p6: strides = [8, 16, 32] else: strides = [8, 16, 32, 64] hsizes = [img_size[0] // stride for stride in strides] wsizes = [img_size[1] // stride for stride in strides] for hsize, wsize, stride in zip(hsizes, wsizes, strides): xv, yv = np.meshgrid(np.arange(wsize), np.arange(hsize)) grid = np.stack((xv, yv), 2).reshape(1, -1, 2) grids.append(grid) shape = grid.shape[:2] expanded_strides.append(np.full((*shape, 1), stride)) grids = np.concatenate(grids, 1) expanded_strides = np.concatenate(expanded_strides, 1) outputs[..., :2] = (outputs[..., :2] + grids) * expanded_strides outputs[..., 2:4] = np.exp(outputs[..., 2:4]) * expanded_strides return outputs
The text was updated successfully, but these errors were encountered:
No branches or pull requests
将yolox利用onnxruntime推理时模型输出后结果需要利用下面代码映射到原图上,但是直接利用pth进行推理时,没有看到这一步,这个是为什么?
def demo_postprocess(outputs, img_size, p6=False):
grids = []
expanded_strides = []
if not p6:
strides = [8, 16, 32]
else:
strides = [8, 16, 32, 64]
hsizes = [img_size[0] // stride for stride in strides]
wsizes = [img_size[1] // stride for stride in strides]
for hsize, wsize, stride in zip(hsizes, wsizes, strides):
xv, yv = np.meshgrid(np.arange(wsize), np.arange(hsize))
grid = np.stack((xv, yv), 2).reshape(1, -1, 2)
grids.append(grid)
shape = grid.shape[:2]
expanded_strides.append(np.full((*shape, 1), stride))
grids = np.concatenate(grids, 1)
expanded_strides = np.concatenate(expanded_strides, 1)
outputs[..., :2] = (outputs[..., :2] + grids) * expanded_strides
outputs[..., 2:4] = np.exp(outputs[..., 2:4]) * expanded_strides
return outputs
The text was updated successfully, but these errors were encountered: