Comments (4)
Hi. It seems like a out-of-boundary index problem. Are you using my newest uploaded code for initialization loss? It has limited the index range.
from pytorch-hitnet-hierarchical-iterative-tile-refinement-network-for-real-time-stereo-matching.
I've reproduced this error on my machine and total_loss.py is updated now.
from pytorch-hitnet-hierarchical-iterative-tile-refinement-network-for-real-time-stereo-matching.
I've reproduced this error on my machine and total_loss.py is updated now.
Great update and I'll test also. Here are another 2 more questions:
- Do you have any plan to cuda-rized your code of the "tile-feature" or "tile hypothesis" part? I tested that part and it seems take around 0.5s which seems much longer than the paper mentioned.
- It seems a little bug about your disparity data but I cannot reproduce that right now. I'll let you know once I meet that again.
Great work again. Appreciate that!
from pytorch-hitnet-hierarchical-iterative-tile-refinement-network-for-real-time-stereo-matching.
Thank you!
Currently there is no plan for programming those parts in cuda
from pytorch-hitnet-hierarchical-iterative-tile-refinement-network-for-real-time-stereo-matching.
Related Issues (10)
- how to generate Slant parameter GT HOT 3
- I'm having trouble in inference
- The code for slant parameter generation is Require access rights HOT 1
- "maxdisp" in initialization_loss.py HOT 1
- Data inconsistency HOT 1
- Great work๏ผ The performance details HOT 2
- question in class DispUpsampleBySlantedPlane
- Pretrained models HOT 1
- request for video demonstration of paper
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