* fix tiler

* deprecate random tile locations

* restore random tiling in tile method

* check tiling section in config

* disable tiling for ganomalu

* pad -> padding

…#1389)

* Non-mandatory early stopping

* Added conv4 and bn4 to OCBE

* Loss as in the official code (flattened arrays)

* Added comment on how to use torchvision model as an encoder to reproduce results in the paper

* Remove early stop from config, change default anomaly_map_mode to add

* pre-commit fix

* Updated results

* Update src/anomalib/models/reverse_distillation/README.md

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Update src/anomalib/models/reverse_distillation/README.md

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Update src/anomalib/models/reverse_distillation/README.md

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Remove early_stopping

* Update src/anomalib/models/reverse_distillation/lightning_model.py

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Easier to read code

---------

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

…t#1386)

* Fix WinError183 (Windows Error)

* Add commentary of the change

---------

Co-authored-by: Youho99 <gaylord.giret@viacesi.fr>

* added license, init.py and draft readme

* added draft DSR files

* minor comment update

* Implemented dsr model + comments

* added dsr discrete model

* added defect generation in torch model + dsr to list of existing methods in init.py

* fixed torch model, started implementing lightning model, implemented anomaly generator

* added loss file for DSR

* Added loss, improved lightning module

* Finished up global implementation of DSR second phase

* minor fixes

* Bugfixes

* Fixed DSR loss calculation

* on_training_start -> on_train_start

* pre-commit run

* updated DSR documentation

* reset config file

* added automatic pretraining weight download

* testing pretrained weights. fixed embedding size in upsampling module and image recon module, to be fixed in original branch

* successful testing on pretrained dsr weights

* checked test quality with pretrained weights, fixed anomaly score calculation

* training is functional

* Fixed training procedure

* test still working

* working upsampling module training and testing

* fixed minor bugs

* updated documentation

* added tests and doc

* adapted learning schedule to steps

* Update src/anomalib/models/dsr/anomaly_generator.py

Co-authored-by: Ashwin Vaidya <ashwinnitinvaidya@gmail.com>

* Apply suggestions from code review

Co-authored-by: Samet Akcay <samet.akcay@intel.com>
Co-authored-by: Ashwin Vaidya <ashwinnitinvaidya@gmail.com>

* refactored outputs into dicts

* remove super() args

* changed downloading weights from anomalib releases + minor fixes

* pre commit hooks + minor fixes

* removed configurable ckpt path refs + default iteration nb from paper

* cleaned up dsr.rst and turned exceptions into RuntimeErrors

* Added upsampling ratio parameter to set third training phase epochs

* Added batched evalaution + minor code simplification

* pre commit hooks

* squeeze output image score tensor

* readded new path check in efficient ad

* fixed double step count with manual optimization

* fixed trailing whitespace

* Fix black issues

* Apply suggestions from code review

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* review suggestions

* updated architecture image links

* Address mypy

* changed output types for dsr model

* readded dict outputs, adapted to TorchInferencer

* fixed error in output dict

* removed default imagenet norm

---------

Co-authored-by: Samet Akcay <samet.akcay@intel.com>
Co-authored-by: Ashwin Vaidya <ashwinnitinvaidya@gmail.com>

* fix unexpected key pixel_metrics.AUPRO.fpr_limit

Signed-off-by: FanJiangIntel <fan.jiang@intel.com>

* load AUPRO before create_metric_collection

Signed-off-by: FanJiangIntel <fan.jiang@intel.com>

* code refine

Signed-off-by: FanJiangIntel <fan.jiang@intel.com>

* fix comment

Signed-off-by: FanJiangIntel <fan.jiang@intel.com>

* fix

Signed-off-by: FanJiangIntel <fan.jiang@intel.com>

* Support test

Signed-off-by: Kang Wenjing <wenjing.kang@intel.com>

* Update test

Signed-off-by: Kang Wenjing <wenjing.kang@intel.com>

* Update test

Signed-off-by: Kang Wenjing <wenjing.kang@intel.com>

---------

Signed-off-by: FanJiangIntel <fan.jiang@intel.com>
Signed-off-by: Kang Wenjing <wenjing.kang@intel.com>
Co-authored-by: FanJiangIntel <fan.jiang@intel.com>
Co-authored-by: Samet Akcay <samet.akcay@intel.com>

…kit#1457)

…pre-commit hooks on previous contribution. (openvinotoolkit#1424)

* testing upstream switch

* picked up on stale OpenCV `setup.py` issue openvinotoolkit#1041

* Fix metadata path

* Ignore hidden directories in folder dataset

* Add check for mask_dir for segmentation tasks in Folder dataset

* Limit the gradio version to <4

)

* Normalize anomaly maps before every validation

* Remove print statement

---------

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Fix beta in augmenter

* Add scheduler

* Change normalization to none

* Replace two lr schedulers with MultiStepLR

* Revert change to beta

* Disable early stopping default

* Format config

* Add opacity parameter beta to config

* Added uflow model

* Added documentation (README) for uflow model

* Added uflow to the list of available models, and main README updated

* Added missing images for the documentation

* Update src/anomalib/models/uflow/anomaly_map.py

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Update src/anomalib/models/uflow/anomaly_map.py

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Update src/anomalib/models/uflow/feature_extraction.py

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Update src/anomalib/models/uflow/torch_model.py

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Added uflow to the reference guide in docs

* Added uflow to the pre-merge tests

* removed the _step function, and merged the code with training_step

* added as a comment the values used in the paper

* re-factorized feature extractors to use the TimmFeatureExtractor class

* added annotations for some functions, where the flow graph is created

* updated readme to fix images loading

* Added link in the README to the original code for reproducing the results

* Removed unused kwargs

* Added docstrigs with args explanations to UFlow classes

* Added models in a github release, and linked here

* Passing all pre-commit checks

* Changed freia's AllInOneBlock by Anomalib's version, and converted the subnet contructor to a Class, in order to be pickable, that is needed to export the model to torch

---------

Co-authored-by: Samet Akcay <samet.akcay@intel.com>

* Fix metadata path

* Ignore hidden directories in folder dataset

* Add check for mask_dir for segmentation tasks in Folder dataset

* Limit the gradio version to <4

* Announce anomalib v1 on readme

* Add the installation instructions and update the documentation link

* fixed DSR squeeze bug

* added comment

* Explanation how to use extension names in the config file

* Added information about extensions to the error message and control of the user input

* Easier to read code

* Replacing assert with raise

Update pull_request_template.md

…n/merge_main

…nvinotoolkit#1537)

* Fixed shape error, allowing arbitrary image sizes. Replaced integer parsing by floor operation

* Replaced calculation by ceil operation. Solution of shape error is to round up and not down for the last upsample layer

* Add comment for ceil oepration

* Formatting with pre-commit hook

…merge_main

…b into ashwin/merge_main