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weighted segmentation loss added #60
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kamil-kaczmarek
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Apr 4, 2018
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@kdziedzic66 thanks Krzychu! Awesome working with you on DSB'18 :)
(@jakubczakon)
kamil-kaczmarek
pushed a commit
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Jul 19, 2018
* added parametrized loss weights * Update pipelines.py random code was pasted in pipelines * Update postprocessing.py bug-fix in crop/pad * Update postprocessing.py * two_unets * Update neptune.yaml dropped local data paths * pull request fixes * two specialist unets pipeline added * Update neptune.yaml * two unets pipeline added * Update pipeline_config.py added globals for specialists * corrections in the neptune.yaml * fixes for unet_specialists * Improve scoring (#54) * propose new (faster hopefully) method of counting score * Update metrics.py * corrections * Update callbacks.py hot-fixed averager update bug * Update utils.py submission generation fix * Bug fix in pipelines, assertion that checks outputs length added. (#62) * Bug fix in pipelines, assertion that checks outputs length added. * assertion message corrected * corrected order of elements in assertion * weighted segmentation loss added (#60) * weighted segmentation loss added * weighted segmentation loss added * formatting * Update neptune.yaml * Update pipeline_config.py * Update validation.py * names refactor * namig refactor * Update models.py * refactor * removed specialists, dropped contour_touching * dropped specialists and contour-touching * Update models.py * Dev patching (#61) * init * added new postpro * local * patching works * added test time augmentation * cropping bugs fixed * fixed callbacks volatile error, updated config, dropped debug from main * dropped loader pickling * added pad if smaller * added more augmentation to the patching seq * added mosaic padding to loaders updated augmentations * added dev mode, updated config, added specialists with patching * fixed mosaic loader bug * Update main.py dropped debug saving * updated postprocessing, added fixes to patching * updated postprocessing, added devmode, fixed loaders, changed mask preprocessing to get full masks and internal contours * fixed mosaic for larger patches, adjusted min blob size in postpro * pipelines with specialists and mulit with patching are working, dropped 0 channel load from loaders, minor fixes in loss def * added small random crop/pads, fixed pipelines for no patching mode, added simple validation mode * added artifact images to train * added global seeding * fixed checkersboard effect * added normalization * added blur to augmentations, added wireframe of scaling pipeline, reverted to vanila postprocessing * added trainable rescaling loop * fixed contour regeneration bug * refactored contour generation, upgraded contour generation in rescaling, cleaned pipelines * added dev and simple cv models, added caching to inference pipeline * added stain deconvolution * fixed image loading for grey images * fixed normalization of patches * moved stand alone notebooks to dir, dropped specialists, refactored pipelines * fixed pipelines updated configs * added kaggle notebooks, small refactor in pipelines, preprocessing clean up * Update augmentation.py * corrections in configs * imports optimized, removed plot_list function from utils.py * corrections * bug fix * added color_seq_RGB * Update neptune.yaml * drop_big_artifacts (#67) * Dev external data (#68) * init * added new postpro * local * patching works * added test time augmentation * cropping bugs fixed * fixed callbacks volatile error, updated config, dropped debug from main * dropped loader pickling * added pad if smaller * added more augmentation to the patching seq * added mosaic padding to loaders updated augmentations * added dev mode, updated config, added specialists with patching * fixed mosaic loader bug * Update main.py dropped debug saving * updated postprocessing, added fixes to patching * updated postprocessing, added devmode, fixed loaders, changed mask preprocessing to get full masks and internal contours * fixed mosaic for larger patches, adjusted min blob size in postpro * pipelines with specialists and mulit with patching are working, dropped 0 channel load from loaders, minor fixes in loss def * added small random crop/pads, fixed pipelines for no patching mode, added simple validation mode * added artifact images to train * added global seeding * fixed checkersboard effect * added normalization * added blur to augmentations, added wireframe of scaling pipeline, reverted to vanila postprocessing * added trainable rescaling loop * fixed contour regeneration bug * refactored contour generation, upgraded contour generation in rescaling, cleaned pipelines * added dev and simple cv models, added caching to inference pipeline * added stain deconvolution * fixed image loading for grey images * fixed normalization of patches * moved stand alone notebooks to dir, dropped specialists, refactored pipelines * fixed pipelines updated configs * added kaggle notebooks, small refactor in pipelines, preprocessing clean up * added generation of matadata and corresponding target masks for external datasets, updated configs * updated augmentation * fixed train valid split for vgg clustering version * fixed train valid split on clusters with external * optimized imports, dropped plot_list() from utils.py * added color_seq_RGB * corrected best_configs * bug fix * added dummy load save to base transformer and dropped redundant stuff… (#69) * added dummy load save to base transformer and dropped redundant stuff, added chunking * Update postprocessing.py * Update preprocessing.py * Dev stage2 (#74) * added run end to end with configs, addec competition_stage parameter * added postpro dev to pipeline * Update neptune_rescaled_patched.yaml * Update neptune_rescaled_patched.yaml * Update neptune_rescaled_patched.yaml * Update neptune_size_estimator.yaml * Update run_end_to_end.sh
kamil-kaczmarek
pushed a commit
that referenced
this pull request
Jul 19, 2018
* added parametrized loss weights * Update pipelines.py random code was pasted in pipelines * Update postprocessing.py bug-fix in crop/pad * Update postprocessing.py * two_unets * Update neptune.yaml dropped local data paths * pull request fixes * two specialist unets pipeline added * Update neptune.yaml * two unets pipeline added * Update pipeline_config.py added globals for specialists * corrections in the neptune.yaml * fixes for unet_specialists * Improve scoring (#54) * propose new (faster hopefully) method of counting score * Update metrics.py * corrections * Update callbacks.py hot-fixed averager update bug * Update utils.py submission generation fix * Bug fix in pipelines, assertion that checks outputs length added. (#62) * Bug fix in pipelines, assertion that checks outputs length added. * assertion message corrected * corrected order of elements in assertion * weighted segmentation loss added (#60) * weighted segmentation loss added * weighted segmentation loss added * formatting * Update neptune.yaml * Update pipeline_config.py * Update validation.py * names refactor * namig refactor * Update models.py * refactor * removed specialists, dropped contour_touching * dropped specialists and contour-touching * Update models.py * Dev patching (#61) * init * added new postpro * local * patching works * added test time augmentation * cropping bugs fixed * fixed callbacks volatile error, updated config, dropped debug from main * dropped loader pickling * added pad if smaller * added more augmentation to the patching seq * added mosaic padding to loaders updated augmentations * added dev mode, updated config, added specialists with patching * fixed mosaic loader bug * Update main.py dropped debug saving * updated postprocessing, added fixes to patching * updated postprocessing, added devmode, fixed loaders, changed mask preprocessing to get full masks and internal contours * fixed mosaic for larger patches, adjusted min blob size in postpro * pipelines with specialists and mulit with patching are working, dropped 0 channel load from loaders, minor fixes in loss def * added small random crop/pads, fixed pipelines for no patching mode, added simple validation mode * added artifact images to train * added global seeding * fixed checkersboard effect * added normalization * added blur to augmentations, added wireframe of scaling pipeline, reverted to vanila postprocessing * added trainable rescaling loop * fixed contour regeneration bug * refactored contour generation, upgraded contour generation in rescaling, cleaned pipelines * added dev and simple cv models, added caching to inference pipeline * added stain deconvolution * fixed image loading for grey images * fixed normalization of patches * moved stand alone notebooks to dir, dropped specialists, refactored pipelines * fixed pipelines updated configs * added kaggle notebooks, small refactor in pipelines, preprocessing clean up * Update augmentation.py * corrections in configs * imports optimized, removed plot_list function from utils.py * corrections * bug fix * added color_seq_RGB * Update neptune.yaml * drop_big_artifacts (#67) * Dev external data (#68) * init * added new postpro * local * patching works * added test time augmentation * cropping bugs fixed * fixed callbacks volatile error, updated config, dropped debug from main * dropped loader pickling * added pad if smaller * added more augmentation to the patching seq * added mosaic padding to loaders updated augmentations * added dev mode, updated config, added specialists with patching * fixed mosaic loader bug * Update main.py dropped debug saving * updated postprocessing, added fixes to patching * updated postprocessing, added devmode, fixed loaders, changed mask preprocessing to get full masks and internal contours * fixed mosaic for larger patches, adjusted min blob size in postpro * pipelines with specialists and mulit with patching are working, dropped 0 channel load from loaders, minor fixes in loss def * added small random crop/pads, fixed pipelines for no patching mode, added simple validation mode * added artifact images to train * added global seeding * fixed checkersboard effect * added normalization * added blur to augmentations, added wireframe of scaling pipeline, reverted to vanila postprocessing * added trainable rescaling loop * fixed contour regeneration bug * refactored contour generation, upgraded contour generation in rescaling, cleaned pipelines * added dev and simple cv models, added caching to inference pipeline * added stain deconvolution * fixed image loading for grey images * fixed normalization of patches * moved stand alone notebooks to dir, dropped specialists, refactored pipelines * fixed pipelines updated configs * added kaggle notebooks, small refactor in pipelines, preprocessing clean up * added generation of matadata and corresponding target masks for external datasets, updated configs * updated augmentation * fixed train valid split for vgg clustering version * fixed train valid split on clusters with external * optimized imports, dropped plot_list() from utils.py * added color_seq_RGB * corrected best_configs * bug fix * added dummy load save to base transformer and dropped redundant stuff… (#69) * added dummy load save to base transformer and dropped redundant stuff, added chunking * Update postprocessing.py * Update preprocessing.py * Dev stage2 (#74) * added run end to end with configs, addec competition_stage parameter * added postpro dev to pipeline * Update neptune_rescaled_patched.yaml * Update neptune_rescaled_patched.yaml * Update neptune_rescaled_patched.yaml * Update neptune_size_estimator.yaml * Update run_end_to_end.sh * final solution init commit (#98)
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