Comments (2)
marius10p
commented on September 26, 2024
1
I see, that makes sense, thanks so much for explaining.
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Lee-Gihun
commented on September 26, 2024
Oh, we hadn't even noticed that! Regarding your question, the current MEDIAR weights are exactly the same as the ones submitted to the challenge.
However, for the version of the prediction submitted, we limited the overlap size between patches and excluded TTA and ensembling for some images due to the time efficiency metric of the challenge evaluation. This was to ensure the running time met the time constraints. I think this might be the reason the score differs.
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Related Issues (19)
- Running on large jp2 WSI files HOT 6
- ERROR: Could not find a version that satisfies the requirement MEDIAR HOT 1
- KeyError: 'medair'
- RuntimeError: Found no NVIDIA driver on your system. HOT 1
- ModuleNotFoundError: No module named 'train_tools' HOT 2
- Running the predict.py code does not produce segmentation results. HOT 1
- requirements.txt has package version "0.0" for skimage HOT 1
- Please retain the Cellpose copyright as required by the BSD-3 license HOT 7
- Finetuing the "finetuned" model on custom dataset HOT 2
- Access to data used for inference HOT 1
- Train on custom dataset HOT 2
- Parameter name mismatches and other issues HOT 2
- Public dataset preprocessing and public data selection strategy for pretraining HOT 4
- What is "classes" parameter in config? HOT 2
- Poor Performance - is my input correctly formated?
- MEDIAR package HOT 1
- Fine-tuning issues HOT 10
- knn classifier HOT 1
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