DLMBL 2024 notebook #114
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DLMBL 2024 notebook #114
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- adding evaluation of pretrained vs course trained model - saving of the predictions - saving of the pixl based metrics and segmentation metrics
- evaluation metrics pixel and segmentation - saving predictions for further evaluation
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this PR should be merged before #119. |
edyoshikun
commented
Aug 2, 2024
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I am also updating cellpose to |
mattersoflight
approved these changes
Aug 7, 2024
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@edyoshikun I suggest that you improve the organization of files and documentation of demos (DL@MBL exercise, inference demos, instructions on how to run training with data/config/scripts we share) first. We can then iterate on the exercise.
* first draft of contrastive learning model * fixed stem and projection head, drafted lightning module * Contrastive_dataloader (#99) * initial dataloader.py * Update dataloader_test.py * Update dataloader_test.py * Update dataloader_test.py * Update dataloader_test.py * rename training script * move contrastive network to viscy.representation module * Update hcs.py * refactored class names * correct imports * cleaner names for model arch and module * new imports * Fixed epoch loss logging and WandB integration in ContrastiveModule * updated training_script.py * Update hcs.py * contrastive.py * engine.py * script to test data i/o speed from different filesystems * moved applications folder to viscy.applications so that pip install -e . works. * add resnet50 to ContrastiveEncoder * rename training_script.py to training_script_resnet.py * test dataloader on lustre and vast * move training_script_resnet to viscy.applications so that `pip install -e .` works * refined the tests for contrastive dataloader * sbatch script for dataloader * delete redundant module * nits: updated the model construction of contrastive resnet encoder. * Updated training script, HCS data handling, engine, and contrastive representation * Fix normalization, visualization issues, logging and multi-channel prediction * updated training and prediction * update training and prediction script * formatting * combine the application directories * lint * replace notebook with script * format script * rename scripts conflicting with pytest * lint application scripts * do not filter all warnings * log instead of print * split data modules by task * clean up imports * update typing * use pathlib * remove redundant file * updated predict.py * better typing * wip: triplet dataset * avoid forward ref this might increase code analysis time a tiny bit but should not have any effect at runtime * check that z range is valid and fix indexing * clean up and explain random sampling * sample dict instead of tuple and include track index * take out generic HCS methods for reuse * implement TripletDataModule * use new batch type in engine * better typing * read normalization metadata * docstring for data module * drop normalization metadata after transformation * remove unused import * fix initial crop size * Infection state (#118) * updated prediction code * updated predict code * updated code * fixed the stem and forward pass (#115) * fixed the stem and forward pass * update forward calls to encoder * self.encoder -> self.model * nits * l2 normalize projections * black compliance * black compliance * WIP: Save progress before merging * updated contrastive.py * stem update * updated predict code * Delete viscy/applications/contrastive_phenotyping/PCA.ipynb * pushing dataloader test updated * pca deleted * training and dataloader test * updated structure * deleted files * updated training merged files * removed commented code * removed uneeded code * removed uneeded code * removed comments * snake_case * fixed CI issues * removed num_fovs --------- Co-authored-by: Shalin Mehta <[email protected]> --------- Co-authored-by: Shalin Mehta <[email protected]> Co-authored-by: Alishba Imran <[email protected]> Co-authored-by: Alishba Imran <[email protected]> Co-authored-by: Alishba Imran <[email protected]> Co-authored-by: Duo Peng <[email protected]>
* wip: use lightning's tensorboard logger instead of wandb * private logging methods * log center slice only * fix tensor cloning * only log metrics on epoch * add simple demo training script * fix flaky test * log graph + profiling * switch to simple profiler --------- Co-authored-by: Shalin Mehta <[email protected]>
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@ziw-liu merging this. |
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This PR adds the exercise for the DL@MBL 2024 course (Part 1) for the image translation.
It also reorganizes the demo folders for clearer organization for the #119 wiki.
Major changes to our img2img translation example: