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Original classes baseline #23
Original classes baseline #23
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…asses used in the marida paper
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some smaller comments
Also, probably you will want to merge this into main not the other branch, I suspect? 🤔 |
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I presume it's ok but I can't really give feedback because I don't know the intent of the changes. Would advocate for shorter-lived, smaller PRs with clear relationship between
<what_was_the_goal> <-> <what_changed_in_the_code>
(only looked at changes since last review given size ✌️)
…n evaluating on test set
…hange intensity only as first augmentation (to avoid changing intensity of padding pixels). Remove the application of augmentations that change intensity of pixels to pseudo labels.
…ing sets setting. Still todo for one training set setting
… training as padding pixles
…works with 0.0 because on the logits of the strongly aug-img I ignore I ignore the padding pixels based on the logits of the weakly aug-img, which has not cutout applied
…Focal loss in the unsup component of the ssl loss. Update descriptions.
…ility of using Cross Entropy in the unsupervised component of the ssl loss
… the loss when using semi-supervised learning
Grad lu fix
Softmax and augmentations fixes
Small fixes
Channel importance
Log val miou
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review is ok
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ok
I created a branch to train a model on the original 11 classes used in MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data, and also with the original 15 classes of the dataset. Now it is possible to train with:
The classes that correspond to each of the above configuration ca be seen in the
assets.py
file