Comments (4)
bowenc0221
commented on August 20, 2024
You can use the demo to visualize VIS predictions: https://github.com/facebookresearch/Mask2Former/tree/main/demo_video
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XiongweiWu
commented on August 20, 2024
@bowenc0221 Hi, how do you visualize the gt as the figures in your appendix? I use the default script (visualize_data.py) of detection2 but the color of prediction and gt seems different. I learn from the tutorial that the ColorMode matters, and thus do you use the ColorMode as SEGMENTATION in your paper?
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wjn922
commented on August 20, 2024
Got it. Thanks.
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bowenc0221
commented on August 20, 2024
@XiongweiWu Figures in my paper are generated with customized code. You can use overlay_instances in https://github.com/facebookresearch/detectron2/blob/cb92ae1763cd7d3777c243f07749574cdaec6cb8/detectron2/utils/visualizer.py#L607 to control the color.
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Related Issues (20)
- Installation expects CUDA_HOME on Apple Silicon Macs HOT 1
- How to understand the output of different tasks
- Using ground truth masks instead of the predicted ones
- No module named 'MultiScaleDeformableAttention', Please compile MultiScaleDeformableAttention CUDA op HOT 2
- As for training, how long does it take?
- HAVE ANYONE MEET SUCH ERROR WHEN TRAINING ON OWN DATASET HOT 1
- batch_size doesn't affect evaluation
- how use custom pre-trained backbone in mask2former HOT 1
- why swin accept different input size
- loading swintransformer
- Ambiguous checkpoint key error when running train_net.py HOT 1
- difference among different mode
- Prebuilt wheels provided via 3rd party repository
- Using COCO for the dataset, what is the appropriate adjustment for learning rate if using a single GPU
- Run in colab seems that there's a ModuleNotFoundError related to the MultiScaleDeformableAttention module.
- Poor Output image quality
- Mask loss with soft labels
- Custom dataset registration to use a model trained on Cityscapes for semantic segmentation.
- How should I fix the input size during testing? HOT 3
- Could you please let me know if anyone has successfully trained using the YouTube VIS 2021 dataset? How should the dataset be formatted?
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