kuldeepbrd1

It is a common practice to compensate for the quantization effect. Since the landmark is encoded in a heatmap of lower resolution (generally 1/4th) than the original image, when recovering...

> Hi，thanks for the reference. Why do we need to shift 0.5 pixel in[ here](https://github.com/HRNet/HRNet-Facial-Landmark-Detection/blob/f776dbe8eb6fec831774a47209dae5547ae2cda5/lib/core/evaluation.py#L77) ? @MengHao666 The 1/4 offset is made from the center of the heatmap pixel. The...

I posted a short snippet for quick inference, if you're still looking for a solution. Hope it helps! :) https://github.com/HRNet/Lite-HRNet/issues/23#issuecomment-841660213

I adapted this simple snippet from `tools/test.py` and mmpose api for inference. Hope this helps. ``` import matplotlib.pyplot as plt from mmpose.apis.inference import init_pose_model, inference_top_down_pose_model model = init_pose_model(config_path, ckpt_path, device=device)...

I think I figured out how to freeze stages now and it runs! **But, how do I verify formally that it is successfully freezing the weights?** FYI I've added a...

For the sake of completeness, I have included all the elements in a basic point cloud rendering script in the following gist for future wanderers to this issue. Hope it...

@TheCamusean In the diff for the changed files, you will also see that there are lots of formatting changes (indentation, terminal spaces, linebreaks etc). These were automatically included in the...

Thanks for this clarification @Nik-V9 and your work. I added simple backward gradient computation for pose (atm using overparameterized pose matrix elements) https://github.com/graphdeco-inria/gaussian-splatting/issues/629 Does this make sense? I have not...

I was able to get gradients w.r.t position and quaternion and they seem to work. Just needed to use the 3x3 gradients from $dL/dT_{cw}$ and compute Frobenius product $$, for...