Major release with lots of new functionality

What's Changed

• updated version for development by @sarthakpati in #259
• Fix for get_final_layer use in GANDLF.utils by @sarthakpati in #260
• Add functionality to save training patches by @sarthakpati in #263
• Updates to integrate new OPM APIs by @sarthakpati in #261
• Added option to print per-label segmentation scores by @sarthakpati in #264
• updated initialization for dicts by @sarthakpati in #267
• Motion artifact separated by @sarthakpati in #270
• added black and opencv-python as an explicit requirements by @sarthakpati in #271
• Bump numpy from 1.19.2 to 1.21.0 by @dependabot in #272
• Added capability to use InstanceNorm in DenseNet by @sarthakpati in #274
• Updated implementations of VGG and DenseNet to use ModelBase for consistency by @sarthakpati in #276
• Added git hash to model save by @sarthakpati in #277
• Added FAQ by @sarthakpati in #279
• Update to how git_hash is saved by @sarthakpati in #280
• Documentation updated for new module structure by @sarthakpati in #283
• Accuracy is now standardized from torchmetrics by @sarthakpati in #287
• Adding automated linting check for black by @sarthakpati in #284
• Post-processing module added by @sarthakpati in #289
• Added a GANDLF.anonymize module by @sarthakpati in #291
• Updated documentation (faq and usage) by @sarthakpati in #294
• Git submodule update is now integrate in setup by @sarthakpati in #296
• Ensure colorjitter works with defaults by @sarthakpati in #297
• More progress bars for better feedback by @sarthakpati in #301
• Update usage.md - plot final results by @anishshriram in #305
• Using Resample and Resize from TorchIO by @Geeks-Sid in #293
• Ensure hole filling output is int by @sarthakpati in #306
• Added instructions for dependency management by @sarthakpati in #307
• Minor fix for reset_prev by @sarthakpati in #310
• added captk and fets links by @sarthakpati in #311
• Updates documentation based on SB's notes by @sarthakpati in #313
• Added script to verify installation by @sarthakpati in #315
• Added ability to save preprocessed files with data augmentation by @sarthakpati in #317
• Added ResNet with multiple configurations by @Sofia-Mouchtaris in #319
• Bug fix in parameters for gandlf_collectStats by @dlang95 in #321
• Resample_Min added to ensure a baseline resolution for all images getting processed by @sarthakpati in #325
• Added final predictions for classification by @sarthakpati in #328
• Ensuring cropping zero planes are applied for preprocessing by @sarthakpati in #329
• Typo fixed for hd95 by @sarthakpati in #331
• Using TiffSlide instead of OpenSlide for a better deployment by @sarthakpati in #303
• Histology anonymization added by @Geeks-Sid in #281
• Bug fix for gandlf_collectStats by @sarthakpati in #335
• Adding resize_image as a separate option as compared to resize_patch by @sarthakpati in #337
• Sanity checking is now softer with a threshold by @sarthakpati in #340
• Added ability to resume with and without updating parameters and/or data by @sarthakpati in #344
• Reverse one-hot logic is now updated to output unique labels by @sarthakpati in #342
• Added EfficientNet with multiple configurations by @Sofia-Mouchtaris in #327
• Links added for current networks by @sarthakpati in #346
• Add Dockerfiles and Docker Hub CI by @AlexanderGetka-cbica in #353
• Add GitHub Packages upload step, refine Docker CI further by @AlexanderGetka-cbica in #355
• Added Docker Image builds by @sarthakpati in #354
• docker ci badge position change by @sarthakpati in #356
• Docker CI: Fix login requirement -- no need to log in for PRs (oops!) by @AlexanderGetka-cbica in #359
• Added some checks for inference mode by @sarthakpati in #358
• Fix for invalid classification accuracy in training by @orhunguley in #361
• Post-training optimization using OpenVINO added by @junwenwu in #312
• Enabling inference without having access to the ground truth by @sarthakpati in #363
• Ensure ONNX-related print only happens once during training by @sarthakpati in #364
• Fixed issue with balanced_accuracy parsing by @sarthakpati in #366
• Hard requirement of PyTorch to LTS by @sarthakpati in #369
• Added post-processing step to map predicted labels to new values by @sarthakpati in #367
• Fix Docker CI on PRs again (meta information missing causing a rebuild -> out of space) by @AlexanderGetka-cbica in #371
• Fixing docker builds by @sarthakpati in #372
• ROCm Docker builds are no longer valid since we are only supporting PyTorch LTS by @sarthakpati in #370
• Custom inference loop added for histo classification by @sarthakpati in #374
• UNet and Light UNet with varying depth by @Sofia-Mouchtaris in #357
• Create codacy-coverage-reporter.yml by @sarthakpati in #368
• added a comment about padding options by @sarthakpati in #376
• Improved penalty calculation and added ImageNet-specific VGG by @Geeks-Sid in #365
• Error checks added to ImageNet VGG by @sarthakpati in #377
• updated config comment for num_channels by @sarthakpati in #378
• Logic fixed for step scheduler by @sarthakpati in #379
• Add option to save model at every epoch by @sarthakpati in #381
• Added note for classification/regression tasks by @sarthakpati in #385
• Added RGBA to RGB conversion in preprocessing by @sarthakpati in #384
• Improved default step_size calculation by @sarthakpati in #386
• Added a key for exp scheduler by @sarthakpati in #387
• Documentation updates by @sarthakpati in #388
• Fixing tests on named venv by @sarthakpati in #382
• Fixing pytorch version dependency for macOS by @sarthakpati in #390
• Add option to strategize the final aggregation for segmentation by @sarthakpati in #392
• Fixing per-label metrics display by @sarthakpati in #393
• Added submodule to hand template-matching based normalization by @sarthakpati in #394
• Added RGB to RGBA conversion for preprocessing by @sarthakpati in #397
• A new transformer-based segmentation arch (UNetR) has been added by @Sofia-Mouchtaris in #398
• Fixing different device issue on multi-layer UNet and UNETR by @sarthakpati in #399
• Added sigmoid multiplier for UNet model output by @sarthakpati in #400
• Documentation update for installation by @sarthakpati in #403
• More inference mode options added by @sarthakpati in #405
• Update one_hot and reverse_one_hot logic for succinctness by @sarthakpati in #404
• moving get_final_layer method functionality to GANDLF.utils to avoid by @brandon-edwards in #407
• API updates to make GaNDLF's compute objects callable outside the tool by @sarthakpati in #401
• Added memory usage for cuda under verbose by @sarthakpati in #409
• Fixes to model getting sent to device twice by @sarthakpati in #411
• Upgrade to OpenVINO 2022.1 by @junwenwu in #410
• Model device location fixed for inference by @sarthakpati in #412
• Fixed type passed to get_class_imbalance_weights by @psfoley in #414
• Updated OpenVINO installation for CI by @sarthakpati in #415
• Reducing dataframe iteration by @sarthakpati in #416
• Documentation update to use pip instead of conda, per our CI by @sarthakpati in #419
• Taking care of case where 0 is absent from class_list for segmentation by @sarthakpati in #418
• Providing train/val split should not result in another training by @sarthakpati in #420
• Fix typo torch summary by @katesedykh in #421
• Added a preprocessing dict for resize_image by @sarthakpati in #423
• Create pytorch objects inference fix by @psfoley in #422
• Figure added from manuscript by @sarthakpati in #426
• Checking dimensionality of computations and raising run-time error by @sarthakpati in #429
• Supporting JPG for writing segmentation output by @sarthakpati in #432
• Histology inference logic updated by @Geeks-Sid in #433
• Bug fix for OpenVINO iGPU model craching by @junwenwu in #436
• Simplified logic for histology inference by @sarthakpati in #435
• Links updated to remove redundant highlights by @sarthakpati in #440
• Trying to fix Out-of-Memory on unit tests (with TransNet changes) by @AlexanderGetka-cbica in #444
• Improving code coverage by reducing number of lines of code by @sarthakpati in #446
• Enable patch size calculation in microns for histology images by @sarthakpati in #439
• Improved masking functionality for histology inference by @Geeks-Sid in #448
• version update for tagging by @sarthakpati in #449

New Contributors

• @dependabot made their first contribution in #272
• @anishshriram made their first contribution in #305
• @Sofia-Mouchtaris made their first contribution in #319
• @dlang95 made their first contribution in #321
• @AlexanderGetka-cbica made their first contribution in #353
• @brandon-edwards made their first contribution in #407
• @psfoley made their first contribution in #414
• @katesedykh made their first contribution in #421

Full Changelog: 0.0.13...0.0.14