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fix seeds in train.py and test.py to make results perfectly reproducible on a single GPU - enhances the robustness of results
Investment: Highhow long it takes to do a work itemhow long it takes to do a work itemInvestment: Mediumhow long it takes to do a work itemhow long it takes to do a work itemType: EnhancementThis an enhancement to an existing featureThis an enhancement to an existing featureStatus: Open.add a clean-up job to remove output directories from build VM
Type: EnhancementThis an enhancement to an existing featureThis an enhancement to an existing featureStatus: Open.cache Penbscot and Dutch F3 data on build VM and download weekly
Type: EnhancementThis an enhancement to an existing featureThis an enhancement to an existing featureStatus: Open.- Status: Open.
- Status: Open.
Add data QC module
Investment: Lowhow long it takes to do a work itemhow long it takes to do a work itemType: FeatureNew feature or requestNew feature or requestStatus: Open.Dynamic global data information, reduces user-required specifications
Investment: Lowhow long it takes to do a work itemhow long it takes to do a work itemType: FeatureNew feature or requestNew feature or requestStatus: Open.add pre-trained models to test section of the HRNet notebooks - facilitates faster onboarding with more pre-trained models
Type: EnhancementThis an enhancement to an existing featureThis an enhancement to an existing featureStatus: Open.add UNet pre-trained model - facilitates faster onboarding with UNet model
Type: EnhancementThis an enhancement to an existing featureThis an enhancement to an existing featureStatus: Open.make pre-run notebooks for segyconverter utility and SEResNet available in main README - facilitates faster quick-start experience
Type: EnhancementThis an enhancement to an existing featureThis an enhancement to an existing featureType: GapNot feature but a missing item to an existing featureNot feature but a missing item to an existing featureStatus: Open.