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MultiTemporal Crop Classification Example shown a really bad result. #8
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Thanks @realleewq for the feedback. The issue was due to an incorrect mode="min" in the ModelCheckpoint, which was corrected to mode="max". After updating the experiment, we achieved an f1-score of ~0.62. While this is a notable improvement, the results, and particularly the predict mask, could likely improve further with more than 30 epochs, as time constraints limited the training duration. |
@PedroConrado Could the images in the example_multitemporalcrop.ipynb please be updated to match results obtained when using the mode="max" ModelCheckpoint? Current segmentation results are so bad that it doesn't inspire confidence in the utility of the Prithvi-EO-2.0 foundation model. |
The notebook has been updated and now shows the correct predictions. |
Thanks @daniszw |
The MultiTemporalCropClassification experiment’s acc and f1-score is only 0.31, which is a really bad result. The graphical predict mask seem to be completely inconsistent with GT,
What went wrong with this experiment?
The text was updated successfully, but these errors were encountered: