Comments (3)
cdoersch
commented on July 28, 2024
Yes, TAPIR can be run on any resolution; internally it will perform its initialization on 256x256 and then refine on progressively higher resolution. It should work out-of-the-box in our colab demo.
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vrk7
commented on July 28, 2024
My issue is, i have annotation of segments in COCO format. When i converted this into 2D points, should I have the points according to the original frame or reduced frame?
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cdoersch
commented on July 28, 2024
They should be scaled relative to the size of the video that you input into TAPIR. I.e. if its 512x512, your points should be in the range [0,512].
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Related Issues (20)
- OnnxExporterError: Unsupported: ONNX export of operator GridSample with 5D volumetric input. HOT 5
- ValueError: All `hk.Module`s must be initialized inside an `hk.transform` HOT 12
- ValueError: converting frame count is not supported. HOT 8
- robotap's query points selection question HOT 5
- Torchscript compatibility HOT 6
- Has anyone implemented it with tensorrt? HOT 1
- None of the algorithms provided by cuDNN heuristics worked; trying fallback algorithms HOT 2
- Pytorch <2.1.0 can't load the checkpoints correctly HOT 1
- Pretrained Weights for Pytorch Version of Online Tapir/BootsTapir HOT 2
- IndexError: boolean index did not match indexed array along dimension 1; dimension is 256 but corresponding boolean dimension is 990 HOT 2
- Training TAPIR PyTorch version script? HOT 7
- BootsTAP Training Dataset HOT 1
- `plot_tracks_v2` has bug when plotting with `trackgroup` argument. HOT 2
- KeyError: 'global_step' When I load the weight of TAPIR HOT 5
- CUDA out of memory issue when using PyTorch weights instead of JAX weights. HOT 2
- pytorch version TAPIR 's training file HOT 1
- Annotation Tool for TAP-VID HOT 2
- TAPIR PyTorch checkpoint size mismatch with model HOT 5
- TAPIR training time stats HOT 2
- TAPIR performance degradation with cudnn9 HOT 3
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