Comments (4)
bowenc0221
commented on July 19, 2024
You only have 1 class and the model will have 100% accuracy by always predicting that class.
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sergiev
commented on July 19, 2024
@bowenc0221 what is the proper way to train single class (except background, of course) semantic segmentation model?
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lxr-1204
commented on July 19, 2024
I often encounter this problem, do you have any solutions? i will be very grateful to you
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AlphonsG
commented on July 19, 2024
@lxr-1204 hello, I stopped using this repo but it was a very long time ago, not sure how to fix
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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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