Comments (1)
The image that you showed is a bit different from KITTI dataset, so the metric depth for the objects in your image might not be as accurate as for test images in KITTI. Training from your own dataset will always produce better results. Lastly, keep in mind that this codebase license does not permit commercial use.
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Related Issues (20)
- Network inference time problem
- The requested array has an inhomogeneous shape after 1 dimensions. HOT 5
- Write split file HOT 2
- obtained some very strange depth maps HOT 4
- The difference in the intrinsic matrix affects the results
- Question about image resolution
- question for the Data Preparation
- Why is smooth_loss divided by 2**scale?
- Questions about the meaning of grid in the F.grid_sample function
- the eval file about 'gt_depths.npz'
- Run on Google Colab,
- Run on Google Colab, but out of System RAM
- The new constraint about pose is not useful?
- RuntimeError: CuDNN error: CUDNN_STATUS_SUCCESS HOT 2
- How to obtain reconstructed image and loss for a single demo image
- How to setup already trained computer vision model Ultralytics YOLOv8 with monodepth2 HOT 1
- Questions about pose estimation HOT 1
- Different evaluation criteria for Monodepth2 M and S
- Regarding the patent and license HOT 1
- RuntimeError: The size of tensor a (319) must match the size of tensor b (639) at non-singleton dimension 3
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