Comments (2)
Hi @yassine9666 ,
Thank you for the interest! As mentioned in the implementation details of the method section, you would need to initialize the discriminator with pretrained segmenter weights. The pretrained UperNet weights are uploaded here, which are originally from semantic-segmentation-pytorch with semantic classes re-matched based on the training dataset
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Hi @yassine9666 , I have also updated README here. Hopefully, it can provide some guidelines regarding training on a new dataset.
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Related Issues (14)
- Evaluation Metrics. HOT 3
- Fine-tuning for my own dataset HOT 2
- Cannot Training with Released Code HOT 7
- optimizer_idx HOT 4
- Training code / weight for COCO HOT 6
- How to warm up the segmentation model upper-net? HOT 2
- Out-of-distribution generation HOT 2
- Need for captions for new dataset? HOT 1
- Training on new data guidance
- got an unexpected keyword argument 'is_inference' HOT 3
- Manual definition of classes for new dataset HOT 1
- IndexError: index out of range in self HOT 1
- Inquiry about GPU Training Time HOT 2
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