π Modify the PR template #1611
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ashwinvaidya17
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* Address tiler issues (#1411) * fix tiler * deprecate random tile locations * restore random tiling in tile method * check tiling section in config * disable tiling for ganomalu * pad -> padding * Refactor Reverse Distillation to match official code (#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 <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Remove early_stopping * Update src/anomalib/models/reverse_distillation/lightning_model.py Co-authored-by: Samet Akcay <[email protected]> * Easier to read code --------- Co-authored-by: Samet Akcay <[email protected]> * Patch for the WinError183 on the OpenVino export mode (#1386) * Fix WinError183 (Windows Error) * Add commentary of the change --------- Co-authored-by: Youho99 <[email protected]> * Add DSR model (#1142) * 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 <[email protected]> * Apply suggestions from code review Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * 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 <[email protected]> * 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 <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * Fix unexpected key pixel_metrics.AUPRO.fpr_limit (#1055) * fix unexpected key pixel_metrics.AUPRO.fpr_limit Signed-off-by: FanJiangIntel <[email protected]> * load AUPRO before create_metric_collection Signed-off-by: FanJiangIntel <[email protected]> * code refine Signed-off-by: FanJiangIntel <[email protected]> * fix comment Signed-off-by: FanJiangIntel <[email protected]> * fix Signed-off-by: FanJiangIntel <[email protected]> * Support test Signed-off-by: Kang Wenjing <[email protected]> * Update test Signed-off-by: Kang Wenjing <[email protected]> * Update test Signed-off-by: Kang Wenjing <[email protected]> --------- Signed-off-by: FanJiangIntel <[email protected]> Signed-off-by: Kang Wenjing <[email protected]> Co-authored-by: FanJiangIntel <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Improved speed and memory usage of mean+std calculation (#1457) * preexisting OpenCV version check added to `setup.py`, ran formatting pre-commit hooks on previous contribution. (#1424) * testing upstream switch * picked up on stale OpenCV `setup.py` issue #1041 * π Hotfix: Limit Gradio Version (#1458) * 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 * Fix/efficient ad normalize before every validation (#1441) * Normalize anomaly maps before every validation * Remove print statement --------- Co-authored-by: Samet Akcay <[email protected]> * Fix DRAEM (#1431) * 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 * Adding U-Flow method (#1415) * 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 <[email protected]> * Update src/anomalib/models/uflow/anomaly_map.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/uflow/feature_extraction.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/uflow/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * 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 <[email protected]> * Update README.md * π Announce anomalib v1 on the main `README.md` (#1542) * 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 (#1486) * fixed DSR squeeze bug * added comment * Refactor/extensions custom dataset (#1562) * 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 * π Modify the PR template (#1611) Update pull_request_template.md * Fix result image URLs (#1510) * Fix tests * refactor path + fix issues + fix linting issues * Migrate docs * fix typing * fix failing model tests * Fix tests * Address PR comments * Fixed shape error, allowing arbitary image sizes for EfficientAD (#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 * Clean up badge --------- Signed-off-by: FanJiangIntel <[email protected]> Signed-off-by: Kang Wenjing <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: abc-125 <[email protected]> Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: ggiret-thinkdeep <[email protected]> Co-authored-by: Youho99 <[email protected]> Co-authored-by: Philippe Carvalho <[email protected]> Co-authored-by: Wenjing Kang <[email protected]> Co-authored-by: FanJiangIntel <[email protected]> Co-authored-by: belfner <[email protected]> Co-authored-by: Abdulla Al Blooshi <[email protected]> Co-authored-by: BlaΕΎ Rolih <[email protected]> Co-authored-by: MatΓas Tailanian <[email protected]> Co-authored-by: Jan SchlΓΌter <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Christopher <[email protected]>
samet-akcay
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Jan 24, 2024
* Merge feature/lightning-version-upgrade to feature/custom-trainer (#1297) Upgrade to Lightning 2.0.5 (#1221) * Adapt code and configs to PL 2.0.5 * Pre-commit checks. * Fix a function call. * Fix function calls. * pytorch_lightning -> lightning.pytorch * Add lightning to requirements --------- Co-authored-by: Weilin Xu <[email protected]> Co-authored-by: Samet <[email protected]> * Partially restore tests (#1298) * Upgrade to Lightning 2.0.5 (#1221) * Adapt code and configs to PL 2.0.5 * Pre-commit checks. * Fix a function call. * Fix function calls. * pytorch_lightning -> lightning.pytorch * Add lightning to requirements --------- Co-authored-by: Samet <[email protected]> * partially restore tests * Address PR comments --------- Co-authored-by: Weilin Xu <[email protected]> Co-authored-by: Samet <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Remove future annotations (#1299) * remove __future__ * Update changelog --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Refactor postprocessing (#1302) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Remove handler * Address PR comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] refactor normalization callbacks (#1310) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Refactor normalization callback * Match convention * Refactor imports * Address PR comments * Fix path * Refactor callbacks * Fix module path --------- * [Custom Trainer] Refactor thresholding (#1311) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Refactor normalization callback * Refactor thresholding * Match convention * Refactor imports * Address PR comments * Fix path * Refactor callbacks * Fix module path * Address PR comments * Apply suggestions from code review Co-authored-by: Samet Akcay <[email protected]> --------- Co-authored-by: Samet Akcay <[email protected]> * [Custom Trainer] Refactor Metrics (#1312) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Refactor normalization callback * Refactor thresholding * Refactor metrics configuration * Match convention * Refactor imports * Address PR comments * Fix path * Refactor callbacks * Fix module path * Address PR comments * Address PR comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Refactor visualization callback (#1313) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Refactor normalization callback * Refactor thresholding * Refactor metrics configuration * Move visualizer callbacks into trainer * Match convention * Refactor imports * Address PR comments * Fix path * Refactor callbacks * Fix module path * Address PR comments * Remove comment --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Initial engine design (#1348) * Initial engine design * Address PR comments * Circular import + trainer->engine * Update src/anomalib/engine/engine.py * revert import in __init__ --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * [Custom Trainer] Partially fix tests (#1359) * Partially fix test * Address PR comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Add CLI support (#1381) * Support trainer methods * support yaml serialization * add hpo command * Add benchmark + train entrypoint * Add export arguments * Partially address PR comments * Add export subcommands + refactor * Address PR comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Partially restore tests (#1391) * Fix tests * Patch get experiment logger * Sort imports * Add stfpm config --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Add new ruff rules (#1390) * Add rules to pyproject.toml file * Only include padim and stfpm in tests * Fix notebook tests * Fix notebook tests * Code quality/enable rules (#1394) * pyflakes * pycodestyle * pep8-naming (`N`) * Enable Ruff rules - Part III (#1397) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * Enable Ruff Rules - Part 4 (#1402) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * [Custom Trainer] Switch to manual optimization for ganomaly (#1404) * implement manual optimizers for ganomaly * cleanup * Enable Ruff Rules - Part 5 (#1403) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * Update src/anomalib/models/components/flow/all_in_one_block.py Co-authored-by: Ashwin Vaidya <[email protected]> * addressed pr comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Add import checks (#1393) * Add checks * Add checks for wandb * move exception handling to method * fix pre-commit issue --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Remove max epochs > 1 (#1400) Remove max epochs>1 from default param list Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Add default values (#1395) * Add checks * Add default values to datasets + padim model * update default values * Remove merge artifact * Change gt path --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Enable Ruff Rules - Part 6 (#1407) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * Enable Ruff Rules - Part 7 (#1408) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * Fix random_split tests * Fix pre-commit * Fixed the logger test * Fix the typos in todos * Enable Ruff Rules - Part 8 (#1412) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * ignore ANN101 ANN102 and ANN103 * Fix random_split tests * Fix pre-commit * ANN partly done * Remove kwargs: Any * flake8-annotations (`ANN`) * Enabled tests * Revert padim configs * Enable Ruff Rules - Part 9 (#1419) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * ignore ANN101 ANN102 and ANN103 * Fix random_split tests * Fix pre-commit * ANN partly done * Remove kwargs: Any * flake8-annotations (`ANN`) * Enabled tests * Revert padim configs * Add auto fixes * Fix docstrings * Update src/anomalib/utils/metrics/binning.py Co-authored-by: Ashwin Vaidya <[email protected]> * Update src/anomalib/models/dfkde/lightning_model.py Co-authored-by: Ashwin Vaidya <[email protected]> * Update src/anomalib/models/rkde/feature_extractor.py Co-authored-by: Ashwin Vaidya <[email protected]> * Fixed pre-commit --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Merge main into feature/custom_trainer (#1420) * Address tiler issues (#1411) * fix tiler * deprecate random tile locations * restore random tiling in tile method * check tiling section in config * disable tiling for ganomalu * pad -> padding * Refactor Reverse Distillation to match official code (#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 <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Remove early_stopping * Update src/anomalib/models/reverse_distillation/lightning_model.py Co-authored-by: Samet Akcay <[email protected]> * Easier to read code --------- Co-authored-by: Samet Akcay <[email protected]> --------- Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: abc-125 <[email protected]> Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * Enable Ruff Rules - Part 10 (#1423) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * ignore ANN101 ANN102 and ANN103 * Fix random_split tests * Fix pre-commit * ANN partly done * Remove kwargs: Any * flake8-annotations (`ANN`) * Enabled tests * Revert padim configs * Add auto fixes * Fix docstrings * Enabled "PLW2901", # `for` loop variable `row` overwritten by assignment target * Enable Ruff Rules - Part 11 (#1425) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * ignore ANN101 ANN102 and ANN103 * Fix random_split tests * Fix pre-commit * ANN partly done * Remove kwargs: Any * flake8-annotations (`ANN`) * Enabled tests * Revert padim configs * Add auto fixes * Fix docstrings * Enabled "PLW2901", # `for` loop variable `row` overwritten by assignment target * Add google style to pydocstyle * Remove dashed line from Returns * Remove dashed line from Args * Remove dashed line from Example and Raises * Removed left-over dashed lines * Cleanup pyproject.toml file * [Custom Trainer] Add a verbose help output structure to the CLI (#1396) * Add Verbosity Help-Formatter class * Add Help-Formatter unit-tests * Fix some strings * Fix pre-commit ruff stuff * Fix help_formatter's pre-commit * Add new configs (#1418) * Add new configs * Add draem config * Fix docstring * Update src/anomalib/models/cflow/lightning_model.py Co-authored-by: Samet Akcay <[email protected]> * Linting * Remove --- from docstrings * Remove any from return type * Fix linting issues from feature/custom_trainer --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Add CLI Tests (#1426) * Add new configs * Add draem config * Stash cli tests * Stash cli tests with minor changes * Stash changes * Fix reverse distillation * Fix EfficientAD * Match ai_vad params to config params * Fix ucsd and ai_vad configs * Uncomment validation step * Refactor directory structure * Rename method * use uscd for aivad * fix ucsd path + modify model checkpoint callback for tests * fix dfkde config * Restructure tests + fix normalization test * Revert file * add v1 to tox * Skip testing ai_vad * Increase train and test size * use mvtec dataset --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Restructure test directories. (#1438) * Restructured the test directories * Fixed typo * Fix imports * Fix config path in export tests * Replace black with ruff formatter (#1439) * [Custom Trainer] Refactor export (#1440) * Refactor export * Fix entrypoint tests * remove match statements --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Add ruff checks to tests (#1455) * Fix tests + add ruff check to tests * Limit gradio version * Path->str --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Add dummy image dataset generator helper class (#1444) * Created tests/v1 directory * update license year * Add beantech generator * Refactor mvtec-ad and beantech * Add visa dataset generator * Add DummyImageGenerator * Use DummyImageGenerator in dummy mvtec dataset generator * Use DummyImageGenerator in dummy mvtec dataset generator * Use DummyImageGenerator in dummy mvtec3d dataset generator * Restructured the test directories * Fixed typo * Fix imports * Fix config path in export tests * Add kolektor dataset * add ucsdped generator * Fix tests * Revert conftest.py * add method for generating avenue dataset * Revert conftest.py * add method for generating shanghaitech dataset * swap order of typing for better parsing of normalization type * cleanup * Dynamically create DataFormat enum * Add examples to docstring * address pr comments and rename dataset.py to data.py * Fix pre-commit issues --------- Co-authored-by: Dick Ameln <[email protected]> * Remove configurable parameters (#1453) * Refactor export * Fix entrypoint tests * remove match statements * Fix tests + remove get_configurable_params + fix hpo,benchmarking * Path->str * Update src/anomalib/models/__init__.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/utils/sweep/config.py Co-authored-by: Samet Akcay <[email protected]> * Update tools/inference/README.md Co-authored-by: Samet Akcay <[email protected]> * Update tools/inference/README.md Co-authored-by: Samet Akcay <[email protected]> * str->Path * str->Path * Fix model checkpoint path * typing + path + test order * Update src/anomalib/utils/sweep/config.py Co-authored-by: Samet Akcay <[email protected]> * Mark tests as xfail * Fix notebook --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * [v1] - Tests: Add datamodule tests. (#1456) * Created tests/v1 directory * update license year * Add beantech generator * Refactor mvtec-ad and beantech * Add visa dataset generator * Add DummyImageGenerator * Use DummyImageGenerator in dummy mvtec dataset generator * Use DummyImageGenerator in dummy mvtec dataset generator * Use DummyImageGenerator in dummy mvtec3d dataset generator * Restructured the test directories * Fixed typo * Fix imports * Fix config path in export tests * Add kolektor dataset * add ucsdped generator * Fix tests * Revert conftest.py * add method for generating avenue dataset * Revert conftest.py * add method for generating shanghaitech dataset * swap order of typing for better parsing of normalization type * cleanup * create the data tests files * Dynamically create DataFormat enum * Add examples to docstring * add conftest.py * address pr comments and rename dataset.py to data.py * add some changes * Add test_datasets to the integration tests * Change order * Added datamodule tests * Format ruff * Address pre-commit issues * Fix video tests * Add the rest of the datamodule tests --------- Co-authored-by: Dick Ameln <[email protected]> * [Custom Trainer] Add train subcommand (#1465) Add train subcommand Co-authored-by: Ashwin Vaidya <[email protected]> * Refactor `Tensor` annotation to `torch.Tensor` (#1477) * Modify Tensor to torch.Tensor * list[Tensor] to list[torch.Tensor] * TODO: Fix formatting issues * torch_all to torch.all * Remove redundant import * Apply ruff format * Fix the tests * Refactor tests Part 1 (#1473) * Refactor CLI tests * Select a random model * Fix test for all the models --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Add API tests Part 2 (#1474) * Partially migrate unit tests Part 3 (#1480) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Address PR comments * Refactor ckpt_path fixture * Update conftest.py * Update __init__.py * Update __init__.py --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Reorg Part I: Data (#1483) * Update Anomalib data with the new structure * Update dataset imports and remove unused imports * ruff format in engine.py * Move TaskType to utils/types * Revert TaskType import from anomalib * Revert tox.ini * Refactor imports and fix import errors * Fix import errors and update type annotations * Fix imports in jupyter notebooks * Refactor import statements in test_visualizer.py * Reorg Part II: Remove `pre_processor` and `post_processor` subpackages (#1485) * Update Anomalib data with the new structure * Update dataset imports and remove unused imports * ruff format in engine.py * Move TaskType to utils/types * Revert TaskType import from anomalib * Revert tox.ini * Refactor imports and fix import errors * Fix import errors and update type annotations * Fix imports in jupyter notebooks * Remove pre-processor subpackage from anomalib * Remove unused imports and update import paths * Refactor import statements in test_visualizer.py * Remove unused code and deprecate Denormalize and ToNumpy classes * Remove empty code cell * Add a description why input image is read from path * Fix bug in superimpose * Migrate deploy tests Part 4 (#1481) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Migrate deploy tests * trained_padim_path->ckpt_path * Split normalization line * Fix normalization class path --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Migrate model components unit tests Part 5 (#1482) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Migrate deploy tests * Migrate model component tests * Migrate visualizer callback + cli tests * Fix lightning entrypoint test * trained_padim_path->ckpt_path * Add todo * Fix TaskType import * Apply suggestions from code review Co-authored-by: Samet Akcay <[email protected]> --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Reorg Part III: Move the main anomalib components from `anomalib.utils` to `anomalib` (#1487) * Update Anomalib data with the new structure * Update dataset imports and remove unused imports * ruff format in engine.py * Move TaskType to utils/types * Revert TaskType import from anomalib * Revert tox.ini * Refactor imports and fix import errors * Fix import errors and update type annotations * Fix imports in jupyter notebooks * Remove pre-processor subpackage from anomalib * Remove unused imports and update import paths * Refactor import statements in test_visualizer.py * Move callbacks from utils under anomalib * Fix import statements in benchmarking and CLI modules * Move CLI under anomalib * Add benchmark to pipelines * Move hpo to pipelines * Move sweep to pipelines * Move loggers to anomalib * Move metrics to anomalib * Move callbacks from utils to test/utils * Move config to anomalib.utils * Fix the metric imports * Remove unused code and deprecate Denormalize and ToNumpy classes * Remove empty code cell * Add a description why input image is read from path * Fix bug in superimpose * Move anomalib.utils.config.config to anomalib.utils.config * Fix config import * Merge feature/custom_trainer * Migrate tools test Part 6 (#1488) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Migrate deploy tests * Migrate model component tests * Migrate visualizer callback + cli tests * Fix lightning entrypoint test * trained_padim_path->ckpt_path * Migrate metrics tests * Migrate tools + remove nightly --------- Co-authored-by: Ashwin Vaidya <[email protected]> * π Refactor padim and patchcore models (#1300) * Fix metadata path * Ignore hidden directories in folder dataset * Add check for mask_dir for segmentation tasks in Folder dataset * add is_fitted * self.model._is_fitted to self.model.is_fitted * Format anomaly module * Remove on_save_checkpoint * Refactor padim * Add __repr__ to anomaly score threshold * Revert patchcore config * Add memory bank modules for anomaly detection * Add explanation to MemoryBankTorchModule docstring. * Update memory bank module imports and fix typo in Padim model * Rename Dynamic Buffer Module to Memory Bank Module in docstring. * Revert "Add explanation to MemoryBankTorchModule docstring." This reverts commit 44c991450f7c78eee2b0ceb0e7c855c3893a0801. * Refactor memory bank modules based on Dick's suggestion * Fix model attribute assignment in lightning models * Add MemoryBankMixin to anomaly detection models * revert padim and patchcore * Reorder inheritance in anomaly detection models --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Migrate unit tests Part 7 (#1490) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Migrate deploy tests * Migrate model component tests * Migrate visualizer callback + cli tests * Fix lightning entrypoint test * trained_padim_path->ckpt_path * Migrate metrics tests * Migrate tools + remove nightly * Increase coverage * Migrate remaining tests * Fix imports * Fix import * Update tests/unit/deploy/test_inferencer.py Co-authored-by: Samet Akcay <[email protected]> * Update test_get_logger.py --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Fix circular import in cdf normalizer (#1494) * fix circular import in cdf normalizer * fix pre-commit --------- Co-authored-by: Samet Akcay <[email protected]> * π οΈ Refactor: Split models to image and video (#1493) * Move AiVad to anomalib.video * Move cfa to models.image * Add Ganomaly model to image models * Add Fastflow model to image models * Add EfficientAd anomaly detection model to image models * Move dfm, dfkde and draem * Add CS-Flow model implementation for image-based defect detection * Add cflow to image models * Add padim to image models * Add patchcore to image models * Add Reverse distillation to image models. * Add rkde to image models * Add stfpm to image models. * Add image models for handling image datasets in anomalib * Update copyright year in model files * Update import statement for Fastflow model * Update image and video model documentation * Update src/anomalib/models/video/README.md Co-authored-by: Dick Ameln <[email protected]> * Update clip_length_in_frames parameter in AvenueDataset and Avenue classes * Remove folder references * Fix a typo in readme * Fix shape of image in batch * Update clip_length_in_frames parameter --------- Co-authored-by: Dick Ameln <[email protected]> * v1: Update the readme file (#1503) * Fix metadata path * Ignore hidden directories in folder dataset * Add check for mask_dir for segmentation tasks in Folder dataset * Replace docs * Add each inferencing scripts as a details section * update readme * Add training * modify getting started * Make getting started a subsection * tmp * Added inference section * Refactor Lightning inference code * Update entry point in setup.py * Add training api example to readme * Update training command in README * Fix bug in login functionality * Update HPO and Logging Documentation * refactor getting started section * Update HPO and benchmarking commands * Update the image * Update README.md Co-authored-by: Dick Ameln <[email protected]> * Update README.md Co-authored-by: Dick Ameln <[email protected]> * Remove getting started section * Update README.md Co-authored-by: Dick Ameln <[email protected]> * Update README.md Co-authored-by: Dick Ameln <[email protected]> * Address the reviewer comments --------- Co-authored-by: Dick Ameln <[email protected]> * Extend Engine Tests (#1509) * Add validate + predict * Add train * Add export tests + refactor export cli command * Fix tests * Fix jupyternotebook --------- Co-authored-by: Ashwin Vaidya <[email protected]> * v1: Create the new documentation via `sphinx-design` and `myst` (#1518) * removed docs * Created the new docs * Finished get started * Remove jupyter notebook from docs * Add mvtec to data * Add reference guide * Add section for each image datasets * Add base data modules and datasets * v1 - π Update and Enhance Docstrings (#1532) * removed docs * Created the new docs * Finished get started * Remove jupyter notebook from docs * Add mvtec to data * Add reference guide * initial commit * Remove subrocess from btech * Remove unused import and commented out code * Add section for each image datasets * Add base data modules and datasets * Refactor dataset classes and add docstrings * Add initial draft for backbone docs * Update the docstring in folder_3d * Update mvtec 3d docstring * Added feature extractor tutorial * Add a readme file to the docs * Update folder data docstring * Update kolektor docstrings * Update kolektor docstring * Update mvtec docstring * Update visa docstrings * Update avenue docstring * Update cfa docstring * Update cflow docstring * Update csflow docstring * Update csflow docstring * Update dfkde docstrings * Update dfm docstring * Update draem docstring * Update efficient ad docstring * Update ganomaly docstring * Update padim and patchcore docstrings * Update reverse distillation docstring * update rkde docstring * update stfpm docstring * Update ai-vad docstring * Update feature extractors * add docstring to sparse random projection * Update dimensionality reduction components * Exclude prompt from copying * Normalizing flow update * Add pro * Add feature extractor docs * update aupr * Update aupr * Update aupro * Update auroc * Update docs/source/markdown/guides/how_to/models/feature_extractors.md * Update f1 and manual thresholds * add minmax * add optimal f1 * update utils * update comet * add tensorboard * update wandb * Add callbacks * Update deploy docstrings * Fix pre-commit on Blasz changes * Change the requirement file in readthedocs config file * Partially address pr comments * Fix the model to padim for the cli integration tests --------- Co-authored-by: BlaΕΎ Rolih <[email protected]> Co-authored-by: Blaz Rolih <[email protected]> * Fix AI-VAD issues (#1524) * partially fix empty bbox issue * allow empty region detections * add torch implementation of gmm (WIP) * make knn mem bank persistent * set val_split_mode to same_as_test as default to enforce deterministicness * add unit tests and docstrings to gmm * improve typing of knn estimator * remove todo * update buffer name * fix minor mistakes in gmm implementation * remove unnecessary tensor conversion * fix visualization when predicting with video model * add __init__.py to components.cluster * check for empty bboxes in feature extractor * reduce default batch size * cast deep features to float * fix device issue * add unit tests for feature extractors * add license header * disable random model selection in integration tests * typing and docstrings * add test case for non-convergence warning * π v1 - Docs: Create a dedicated section for each model. (#1540) * Initial commit for model components * FIx the grid in model components * Add image models * Add video models * Fix titles and do some cleanup * reduce the sphinx version as it fails the readthedocs builds * Fix examples for reading transforms from albumentations Compose object and deserializing from a yaml file * Update __init__.py * OpenVINO NNCF updates (#1534) * Update versions of openvino and nncf * All export functions return the model path * Change default OV device to AUTO * Minor changes on openvino API * Fix pre-commit issues * Restored onnx dependency * Added OV export tests * Drop export tests * Rename path var * Renamed test paths * [Docs] Add average score to the FastFlow's performance results tables (#1587) Add average score in the tables of performance results * Update the paper title in CS-FLOW and CFLOW readme (#1579) * Fix csflow name in readme * Update cflow name in readme * v1 - [Refactor] Reflect the changes in #1562 into v1 (#1595) Reflect the changes in #1562 into v1 * βοΈ Refactor `ExportMode` to `ExportType` (#1594) * Update export_mode to export_type * Fix typo typel -> model * Revert the python version in the notebook * π v1 - Modify the PR template (#1596) * Modify the PR template * Update pull_request_template.md * added emojis to the checklist * [Bug] v1: Fix default input normalization method (#1583) Fix default input normalization method * Modify `Engine.predict` (#1514) * Add validate + predict * Add train * Add export tests + refactor export cli command * Fix tests * Fix jupyternotebook * Update engine.predict + expand tests * Fix lightning entrypoint test * Address PR comments * Use only Padim * Fix commands * Move padim to common args * Address 1st PR comment * Address PR comments * Fix aivad tests * Fix missing docstring * Rename config to args * Add missing ckpt_path warning in predict * Remove ckpt_path as required parameter * Add tests for image path in predict * Fix image path in predict * Address PR comments * Fix missing checkpoint path * Fix fastflow precommit issue * Fix tests * Fix test --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Fix issue with incorrect image save location (#1515) Co-authored-by: Ashwin Vaidya <[email protected]> * Upgrade gradio version to 4.x (#1608) * upgrade gradio version to 4.x * refactor variable names * refactor --------- Co-authored-by: Ashwin Vaidya <[email protected]> * β InferenceDataset->PredictDataset (#1544) * β InferenceDataset->PredictDataset * update predict dataset references * update predict dataset references * update predict dataset references * update predict dataset references * update predict dataset references * update notebook --------- Co-authored-by: Ashwin Vaidya <[email protected]> * `FeatureExtractor` -> `TimmFeatureExtractor` (#1543) Deprecate FeatureExtractor Co-authored-by: Ashwin Vaidya <[email protected]> * Add `LearningType` and refactor enums (#1598) * add LearningType and move enums to separate module * add enum definitions * move shared enums to root init * place version above enums * π Add custom data tutorial (#1571) * Add custom data tutorial * Add the custom data training instructions * Address PR comments * Start with a classification data * Release hazelnut toy dataset and refer to the link here. * Update docs/source/markdown/guides/how_to/data/custom_data.md Co-authored-by: Dick Ameln <[email protected]> * Update docs/source/markdown/guides/how_to/data/custom_data.md Co-authored-by: Dick Ameln <[email protected]> * Update docs/source/markdown/guides/how_to/data/custom_data.md Co-authored-by: Dick Ameln <[email protected]> * Remove no-val-test section from tutorials * Address PR comments --------- Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Add URL verification for downloading dataset (#1620) * add url path verification for dataset downloading module * specify node version to pre-commit-config * fix import errors on the notebooks * π v1 - Fix training with mps accelerator (#1618) * Convert mask to float32 in AnomalibDataset * Convert the tensor to cpu before convrting to numpy * replace np.float32 with np.single * Update Engine docstrings (#1549) Update docstrings Co-authored-by: Ashwin Vaidya <[email protected]> * Fixed shape error, allowing arbitary image sizes for EfficientAD * Revert the previous commit * Extend supported models in TimmFeatureExtractor (#1443) Extend Timm feature extractor for v1.0 * π v1 - Address security issues (#1637) * Address path traversal issues 1-3 * address traversal path 6 * Address traverse path 8 * modify the comment to make it more descriptive * π Fix mps float64 tensor conversion issue (#1644) Fix leftover * π Fix metadata_path arg to metadata in OpenVINO inferencer (#1648) Fix metadata_path arg to metadata in OpenVINO inferencer * π Address path traversal issues (#1643) * Address path traversal issues 1-3 * address traversal path 6 * Address traverse path 8 * modify the comment to make it more descriptive * Update get_image_filename function to enhance the input security * fix example * Fix incorrect default value assignment * Refactor project_path fixture to create temporary directory in the root directory of the project * Update .gitignore file to include test-related files and directories * Refactor get_image_filenames_from_dir to filter out non-image files * Add test case for path outside base directory * Add examples to get_filenames * Address PR comments. * Renamed the tmp dir * π Add `SECURITY.md` file (#1655) * Add SECURITY.md file * Add security item to the type of changes in the pull request template. * Update pr template * replace the security emoji * π Add zero-/few-shot model support and WinCLIP model implementation (#1575) * add clip normalization * initial commit for winclip * add cosine similarity computation * add multiscale score computation * simplify mask generation * add few-shot extension (unvalidated) * refactor * cleanup * add todo * formatting * minor refactor * add comment * expose optimal F1 metric * some cleanup * add ln_after_pool logic * remove final_ln_after_pool * update module docstring and remove comments * add typing and docstrings to torch model * cleanup lightning model * hardcode backbone * n_shot -> k_shot * add temperature as constant * minor bugfix * add typing and docstrings to utils * set class name dynamically * replace inf values in harmonic aggregation * run validate before test * set default class name to None * formatting * remove config * comments * minor bugfix * Revert "expose optimal F1 metric" This reverts commit e8e1ead9601d76c743af3678f26b1eb0e06d38fb. * more descriptive assert message * expose scales as configurable parameter and hardcode pretrained as constant * add readme * add images for readme * update docstrings * update license headers * ruff * add openclip as requirement * skip model tests for winclip * fix visualizer test * add example in docstring * fix typo in function name * typing * imports * docstrings * check if model has trainer attribute * remove pylint ignore statement * typing * docstring * improve tensor shape handling * refactor and rename class_scores function * add docstring example * commenting * Update src/anomalib/models/image/winclip/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/image/winclip/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/image/winclip/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * formatting * docstrings * docstrings * comment * typing * multiscale -> multi_scale * add winclip to docs * add few_shot_source parameter * use PredictDataset in WinCLIP implementation * add learning type to winclip lightning model * add custom model checkpoint callback to save at validation end * remove trainer arguments from winclip model * prune state dict for smaller model file * add learning type logic to engine.train * pass full path to model checkpoint * remove training step * enable integration tests for winclip * fix typo * index masks at 0 * formatting * simplify make_masks * validate inputs in make_masks * add unit tests for winclip utils * add default class_name to prompt ensemble * add unit tests for winclip prompt ensemble * add base class for normalization callback * add _should_run_validation check * add engine.model property * use custom modelcheckpoint in tests * update name in todos * fix predict tests * skip export tests for winclip * fix mistake in model retrieval from trainer * add model checks * fix checks * simplify model check * add todo for winclip export * add todo * add bufferlist mixin * update bufferlist docstring * add setup method and register buffers * import torch model in root of winclip module * add unit tests for bufferlist mixin * add unit tests for torch model * fix transform and update docstring * disable strict loading in export * initialize embeddings as tensors * add test to check if erors are raised * add todo * enable winclip export test * remove device references in torch model * restore frozen weights in load_state_dict * make embedding collection methods private * move state dict handling to winclip from base * fix typo * make generate_masks private * increase onnx opset version * remove future import * update docstring * Update src/anomalib/callbacks/normalization/__init__.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/callbacks/normalization/cdf_normalization.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/callbacks/normalization/min_max_normalization.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * typing in docstrings * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * use exception instead of assert * update license header * docstrings * bufferlist -> buffer_list --------- Co-authored-by: Samet Akcay <[email protected]> * WinCLIP attribution (#1662) give credit to related works * π Merge main to v1 (#1652) * Address tiler issues (#1411) * fix tiler * deprecate random tile locations * restore random tiling in tile method * check tiling section in config * disable tiling for ganomalu * pad -> padding * Refactor Reverse Distillation to match official code (#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 <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Remove early_stopping * Update src/anomalib/models/reverse_distillation/lightning_model.py Co-authored-by: Samet Akcay <[email protected]> * Easier to read code --------- Co-authored-by: Samet Akcay <[email protected]> * Patch for the WinError183 on the OpenVino export mode (#1386) * Fix WinError183 (Windows Error) * Add commentary of the change --------- Co-authored-by: Youho99 <[email protected]> * Add DSR model (#1142) * 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 <[email protected]> * Apply suggestions from code review Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * 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 <[email protected]> * 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 <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * Fix unexpected key pixel_metrics.AUPRO.fpr_limit (#1055) * fix unexpected key pixel_metrics.AUPRO.fpr_limit Signed-off-by: FanJiangIntel <[email protected]> * load AUPRO before create_metric_collection Signed-off-by: FanJiangIntel <[email protected]> * code refine Signed-off-by: FanJiangIntel <[email protected]> * fix comment Signed-off-by: FanJiangIntel <[email protected]> * fix Signed-off-by: FanJiangIntel <[email protected]> * Support test Signed-off-by: Kang Wenjing <[email protected]> * Update test Signed-off-by: Kang Wenjing <[email protected]> * Update test Signed-off-by: Kang Wenjing <[email protected]> --------- Signed-off-by: FanJiangIntel <[email protected]> Signed-off-by: Kang Wenjing <[email protected]> Co-authored-by: FanJiangIntel <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Improved speed and memory usage of mean+std calculation (#1457) * preexisting OpenCV version check added to `setup.py`, ran formatting pre-commit hooks on previous contribution. (#1424) * testing upstream switch * picked up on stale OpenCV `setup.py` issue #1041 * π Hotfix: Limit Gradio Version (#1458) * 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 * Fix/efficient ad normalize before every validation (#1441) * Normalize anomaly maps before every validation * Remove print statement --------- Co-authored-by: Samet Akcay <[email protected]> * Fix DRAEM (#1431) * 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 * Adding U-Flow method (#1415) * 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 <[email protected]> * Update src/anomalib/models/uflow/anomaly_map.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/uflow/feature_extraction.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/uflow/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * 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 <[email protected]> * Update README.md * π Announce anomalib v1 on the main `README.md` (#1542) * 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 (#1486) * fixed DSR squeeze bug * added comment * Refactor/extensions custom dataset (#1562) * 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 * π Modify the PR template (#1611) Update pull_request_template.md * Fix result image URLs (#1510) * Fix tests * refactor path + fix issues + fix linting issues * Migrate docs * fix typing * fix failing model tests * Fix tests * Address PR comments * Fixed shape error, allowing arbitary image sizes for EfficientAD (#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 * Clean up badge --------- Signed-off-by: FanJiangIntel <[email protected]> Signed-off-by: Kang Wenjing <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: abc-125 <[email protected]> Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: ggiret-thinkdeep <[email protected]> Co-authored-by: Youho99 <[email protected]> Co-authored-by: Philippe Carvalho <[email protected]> Co-authored-by: Wenjing Kang <[email protected]> Co-authored-by: FanJiangIntel <[email protected]> Co-authored-by: belfner <[email protected]> Co-authored-by: Abdulla Al Blooshi <[email protected]> Co-authored-by: BlaΕΎ Rolih <[email protected]> Co-authored-by: MatΓas Tailanian <[email protected]> Co-authored-by: Jan SchlΓΌter <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Christopher <[email protected]> * Update license headers --------- Signed-off-by: FanJiangIntel <[email protected]> Signed-off-by: Kang Wenjing <[email protected]> Co-authored-by: Weilin Xu <[email protected]> Co-authored-by: Samet <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: abc-125 <[email protected]> Co-authored-by: Harim Kang <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: BlaΕΎ Rolih <[email protected]> Co-authored-by: Blaz Rolih <[email protected]> Co-authored-by: Adrian Boguszewski <[email protected]> Co-authored-by: Willy Fitra Hendria <[email protected]> Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Yunchu Lee <[email protected]> Co-authored-by: ggiret-thinkdeep <[email protected]> Co-authored-by: Youho99 <[email protected]> Co-authored-by: Philippe Carvalho <[email protected]> Co-authored-by: Wenjing Kang <[email protected]> Co-authored-by: FanJiangIntel <[email protected]> Co-authored-by: belfner <[email protected]> Co-authored-by: Abdulla Al Blooshi <[email protected]> Co-authored-by: MatΓas Tailanian <[email protected]> Co-authored-by: Jan SchlΓΌter <[email protected]> Co-authored-by: Christopher <[email protected]>
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* Merge feature/lightning-version-upgrade to feature/custom-trainer (#1297) Upgrade to Lightning 2.0.5 (#1221) * Adapt code and configs to PL 2.0.5 * Pre-commit checks. * Fix a function call. * Fix function calls. * pytorch_lightning -> lightning.pytorch * Add lightning to requirements --------- Co-authored-by: Weilin Xu <[email protected]> Co-authored-by: Samet <[email protected]> * Partially restore tests (#1298) * Upgrade to Lightning 2.0.5 (#1221) * Adapt code and configs to PL 2.0.5 * Pre-commit checks. * Fix a function call. * Fix function calls. * pytorch_lightning -> lightning.pytorch * Add lightning to requirements --------- Co-authored-by: Samet <[email protected]> * partially restore tests * Address PR comments --------- Co-authored-by: Weilin Xu <[email protected]> Co-authored-by: Samet <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Remove future annotations (#1299) * remove __future__ * Update changelog --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Refactor postprocessing (#1302) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Remove handler * Address PR comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] refactor normalization callbacks (#1310) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Refactor normalization callback * Match convention * Refactor imports * Address PR comments * Fix path * Refactor callbacks * Fix module path --------- * [Custom Trainer] Refactor thresholding (#1311) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Refactor normalization callback * Refactor thresholding * Match convention * Refactor imports * Address PR comments * Fix path * Refactor callbacks * Fix module path * Address PR comments * Apply suggestions from code review Co-authored-by: Samet Akcay <[email protected]> --------- Co-authored-by: Samet Akcay <[email protected]> * [Custom Trainer] Refactor Metrics (#1312) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Refactor normalization callback * Refactor thresholding * Refactor metrics configuration * Match convention * Refactor imports * Address PR comments * Fix path * Refactor callbacks * Fix module path * Address PR comments * Address PR comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Refactor visualization callback (#1313) * remove __future__ * Update changelog * π Trainer -> AnomalibTrainer * add post-processor * Refactor callback * Refactor normalization callback * Refactor thresholding * Refactor metrics configuration * Move visualizer callbacks into trainer * Match convention * Refactor imports * Address PR comments * Fix path * Refactor callbacks * Fix module path * Address PR comments * Remove comment --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Initial engine design (#1348) * Initial engine design * Address PR comments * Circular import + trainer->engine * Update src/anomalib/engine/engine.py * revert import in __init__ --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * [Custom Trainer] Partially fix tests (#1359) * Partially fix test * Address PR comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Add CLI support (#1381) * Support trainer methods * support yaml serialization * add hpo command * Add benchmark + train entrypoint * Add export arguments * Partially address PR comments * Add export subcommands + refactor * Address PR comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Partially restore tests (#1391) * Fix tests * Patch get experiment logger * Sort imports * Add stfpm config --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Add new ruff rules (#1390) * Add rules to pyproject.toml file * Only include padim and stfpm in tests * Fix notebook tests * Fix notebook tests * Code quality/enable rules (#1394) * pyflakes * pycodestyle * pep8-naming (`N`) * Enable Ruff rules - Part III (#1397) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * Enable Ruff Rules - Part 4 (#1402) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * [Custom Trainer] Switch to manual optimization for ganomaly (#1404) * implement manual optimizers for ganomaly * cleanup * Enable Ruff Rules - Part 5 (#1403) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * Update src/anomalib/models/components/flow/all_in_one_block.py Co-authored-by: Ashwin Vaidya <[email protected]> * addressed pr comments --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Add import checks (#1393) * Add checks * Add checks for wandb * move exception handling to method * fix pre-commit issue --------- Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Remove max epochs > 1 (#1400) Remove max epochs>1 from default param list Co-authored-by: Ashwin Vaidya <[email protected]> * [Custom Trainer] Add default values (#1395) * Add checks * Add default values to datasets + padim model * update default values * Remove merge artifact * Change gt path --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Enable Ruff Rules - Part 6 (#1407) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * Enable Ruff Rules - Part 7 (#1408) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * Fix random_split tests * Fix pre-commit * Fixed the logger test * Fix the typos in todos * Enable Ruff Rules - Part 8 (#1412) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * ignore ANN101 ANN102 and ANN103 * Fix random_split tests * Fix pre-commit * ANN partly done * Remove kwargs: Any * flake8-annotations (`ANN`) * Enabled tests * Revert padim configs * Enable Ruff Rules - Part 9 (#1419) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * ignore ANN101 ANN102 and ANN103 * Fix random_split tests * Fix pre-commit * ANN partly done * Remove kwargs: Any * flake8-annotations (`ANN`) * Enabled tests * Revert padim configs * Add auto fixes * Fix docstrings * Update src/anomalib/utils/metrics/binning.py Co-authored-by: Ashwin Vaidya <[email protected]> * Update src/anomalib/models/dfkde/lightning_model.py Co-authored-by: Ashwin Vaidya <[email protected]> * Update src/anomalib/models/rkde/feature_extractor.py Co-authored-by: Ashwin Vaidya <[email protected]> * Fixed pre-commit --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Merge main into feature/custom_trainer (#1420) * Address tiler issues (#1411) * fix tiler * deprecate random tile locations * restore random tiling in tile method * check tiling section in config * disable tiling for ganomalu * pad -> padding * Refactor Reverse Distillation to match official code (#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 <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Remove early_stopping * Update src/anomalib/models/reverse_distillation/lightning_model.py Co-authored-by: Samet Akcay <[email protected]> * Easier to read code --------- Co-authored-by: Samet Akcay <[email protected]> --------- Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: abc-125 <[email protected]> Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * Enable Ruff Rules - Part 10 (#1423) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * ignore ANN101 ANN102 and ANN103 * Fix random_split tests * Fix pre-commit * ANN partly done * Remove kwargs: Any * flake8-annotations (`ANN`) * Enabled tests * Revert padim configs * Add auto fixes * Fix docstrings * Enabled "PLW2901", # `for` loop variable `row` overwritten by assignment target * Enable Ruff Rules - Part 11 (#1425) * pyflakes * pycodestyle * pep8-naming (`N`) * pyupgrade (`UP`) * flake8-bandit (`S`) * Enabled UP, ANN, S, BLE, FBT, B * Fix typo * Revert F1AdaptiveThreshold parent classes * Fix some of the tests * ignore boolean-positional-value-in-call (FBT003) * Addressed pr comments * Remove duplicated lines * flake8-builtins (`A`) and flake8-commas (`COM`) * flake8-comprehensions (`C4`) * flake8-datatimez (`DTZ`), flake8-debugger (`T10`), flake8-errmsg (`EM`) * flake8-pie (`PIE`) * flake8-raise (`RSE`) * flake8-return (`RET`) * flake8-self (`SLF`) * flake8-simplify (`SIM`) * flake8-unsused-arguments (`ARG`) * flake8-use-pathlib (`PTH`) * eradicate (`ERA`) * pylint (`PL`) * tryceratos (`TRY`), flynt (`FLY`), Perflint (`PERF`) * NumPy-specific rules (`NPY`) * Ruff-specific rules (`RUF`) * Remove pylint ignore comments * Fix tests * Fix tests * mccabe (`C90`) * pygrep-hooks (`PGH`) * flake8-todos (`TD`) * flake8-fixme (`FIX`) * pandas-vet (`PD`) * ignore ANN101 ANN102 and ANN103 * Fix random_split tests * Fix pre-commit * ANN partly done * Remove kwargs: Any * flake8-annotations (`ANN`) * Enabled tests * Revert padim configs * Add auto fixes * Fix docstrings * Enabled "PLW2901", # `for` loop variable `row` overwritten by assignment target * Add google style to pydocstyle * Remove dashed line from Returns * Remove dashed line from Args * Remove dashed line from Example and Raises * Removed left-over dashed lines * Cleanup pyproject.toml file * [Custom Trainer] Add a verbose help output structure to the CLI (#1396) * Add Verbosity Help-Formatter class * Add Help-Formatter unit-tests * Fix some strings * Fix pre-commit ruff stuff * Fix help_formatter's pre-commit * Add new configs (#1418) * Add new configs * Add draem config * Fix docstring * Update src/anomalib/models/cflow/lightning_model.py Co-authored-by: Samet Akcay <[email protected]> * Linting * Remove --- from docstrings * Remove any from return type * Fix linting issues from feature/custom_trainer --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Add CLI Tests (#1426) * Add new configs * Add draem config * Stash cli tests * Stash cli tests with minor changes * Stash changes * Fix reverse distillation * Fix EfficientAD * Match ai_vad params to config params * Fix ucsd and ai_vad configs * Uncomment validation step * Refactor directory structure * Rename method * use uscd for aivad * fix ucsd path + modify model checkpoint callback for tests * fix dfkde config * Restructure tests + fix normalization test * Revert file * add v1 to tox * Skip testing ai_vad * Increase train and test size * use mvtec dataset --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Restructure test directories. (#1438) * Restructured the test directories * Fixed typo * Fix imports * Fix config path in export tests * Replace black with ruff formatter (#1439) * [Custom Trainer] Refactor export (#1440) * Refactor export * Fix entrypoint tests * remove match statements --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Add ruff checks to tests (#1455) * Fix tests + add ruff check to tests * Limit gradio version * Path->str --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Add dummy image dataset generator helper class (#1444) * Created tests/v1 directory * update license year * Add beantech generator * Refactor mvtec-ad and beantech * Add visa dataset generator * Add DummyImageGenerator * Use DummyImageGenerator in dummy mvtec dataset generator * Use DummyImageGenerator in dummy mvtec dataset generator * Use DummyImageGenerator in dummy mvtec3d dataset generator * Restructured the test directories * Fixed typo * Fix imports * Fix config path in export tests * Add kolektor dataset * add ucsdped generator * Fix tests * Revert conftest.py * add method for generating avenue dataset * Revert conftest.py * add method for generating shanghaitech dataset * swap order of typing for better parsing of normalization type * cleanup * Dynamically create DataFormat enum * Add examples to docstring * address pr comments and rename dataset.py to data.py * Fix pre-commit issues --------- Co-authored-by: Dick Ameln <[email protected]> * Remove configurable parameters (#1453) * Refactor export * Fix entrypoint tests * remove match statements * Fix tests + remove get_configurable_params + fix hpo,benchmarking * Path->str * Update src/anomalib/models/__init__.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/utils/sweep/config.py Co-authored-by: Samet Akcay <[email protected]> * Update tools/inference/README.md Co-authored-by: Samet Akcay <[email protected]> * Update tools/inference/README.md Co-authored-by: Samet Akcay <[email protected]> * str->Path * str->Path * Fix model checkpoint path * typing + path + test order * Update src/anomalib/utils/sweep/config.py Co-authored-by: Samet Akcay <[email protected]> * Mark tests as xfail * Fix notebook --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * [v1] - Tests: Add datamodule tests. (#1456) * Created tests/v1 directory * update license year * Add beantech generator * Refactor mvtec-ad and beantech * Add visa dataset generator * Add DummyImageGenerator * Use DummyImageGenerator in dummy mvtec dataset generator * Use DummyImageGenerator in dummy mvtec dataset generator * Use DummyImageGenerator in dummy mvtec3d dataset generator * Restructured the test directories * Fixed typo * Fix imports * Fix config path in export tests * Add kolektor dataset * add ucsdped generator * Fix tests * Revert conftest.py * add method for generating avenue dataset * Revert conftest.py * add method for generating shanghaitech dataset * swap order of typing for better parsing of normalization type * cleanup * create the data tests files * Dynamically create DataFormat enum * Add examples to docstring * add conftest.py * address pr comments and rename dataset.py to data.py * add some changes * Add test_datasets to the integration tests * Change order * Added datamodule tests * Format ruff * Address pre-commit issues * Fix video tests * Add the rest of the datamodule tests --------- Co-authored-by: Dick Ameln <[email protected]> * [Custom Trainer] Add train subcommand (#1465) Add train subcommand Co-authored-by: Ashwin Vaidya <[email protected]> * Refactor `Tensor` annotation to `torch.Tensor` (#1477) * Modify Tensor to torch.Tensor * list[Tensor] to list[torch.Tensor] * TODO: Fix formatting issues * torch_all to torch.all * Remove redundant import * Apply ruff format * Fix the tests * Refactor tests Part 1 (#1473) * Refactor CLI tests * Select a random model * Fix test for all the models --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Add API tests Part 2 (#1474) * Partially migrate unit tests Part 3 (#1480) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Address PR comments * Refactor ckpt_path fixture * Update conftest.py * Update __init__.py * Update __init__.py --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Reorg Part I: Data (#1483) * Update Anomalib data with the new structure * Update dataset imports and remove unused imports * ruff format in engine.py * Move TaskType to utils/types * Revert TaskType import from anomalib * Revert tox.ini * Refactor imports and fix import errors * Fix import errors and update type annotations * Fix imports in jupyter notebooks * Refactor import statements in test_visualizer.py * Reorg Part II: Remove `pre_processor` and `post_processor` subpackages (#1485) * Update Anomalib data with the new structure * Update dataset imports and remove unused imports * ruff format in engine.py * Move TaskType to utils/types * Revert TaskType import from anomalib * Revert tox.ini * Refactor imports and fix import errors * Fix import errors and update type annotations * Fix imports in jupyter notebooks * Remove pre-processor subpackage from anomalib * Remove unused imports and update import paths * Refactor import statements in test_visualizer.py * Remove unused code and deprecate Denormalize and ToNumpy classes * Remove empty code cell * Add a description why input image is read from path * Fix bug in superimpose * Migrate deploy tests Part 4 (#1481) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Migrate deploy tests * trained_padim_path->ckpt_path * Split normalization line * Fix normalization class path --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Migrate model components unit tests Part 5 (#1482) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Migrate deploy tests * Migrate model component tests * Migrate visualizer callback + cli tests * Fix lightning entrypoint test * trained_padim_path->ckpt_path * Add todo * Fix TaskType import * Apply suggestions from code review Co-authored-by: Samet Akcay <[email protected]> --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Reorg Part III: Move the main anomalib components from `anomalib.utils` to `anomalib` (#1487) * Update Anomalib data with the new structure * Update dataset imports and remove unused imports * ruff format in engine.py * Move TaskType to utils/types * Revert TaskType import from anomalib * Revert tox.ini * Refactor imports and fix import errors * Fix import errors and update type annotations * Fix imports in jupyter notebooks * Remove pre-processor subpackage from anomalib * Remove unused imports and update import paths * Refactor import statements in test_visualizer.py * Move callbacks from utils under anomalib * Fix import statements in benchmarking and CLI modules * Move CLI under anomalib * Add benchmark to pipelines * Move hpo to pipelines * Move sweep to pipelines * Move loggers to anomalib * Move metrics to anomalib * Move callbacks from utils to test/utils * Move config to anomalib.utils * Fix the metric imports * Remove unused code and deprecate Denormalize and ToNumpy classes * Remove empty code cell * Add a description why input image is read from path * Fix bug in superimpose * Move anomalib.utils.config.config to anomalib.utils.config * Fix config import * Merge feature/custom_trainer * Migrate tools test Part 6 (#1488) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Migrate deploy tests * Migrate model component tests * Migrate visualizer callback + cli tests * Fix lightning entrypoint test * trained_padim_path->ckpt_path * Migrate metrics tests * Migrate tools + remove nightly --------- Co-authored-by: Ashwin Vaidya <[email protected]> * π Refactor padim and patchcore models (#1300) * Fix metadata path * Ignore hidden directories in folder dataset * Add check for mask_dir for segmentation tasks in Folder dataset * add is_fitted * self.model._is_fitted to self.model.is_fitted * Format anomaly module * Remove on_save_checkpoint * Refactor padim * Add __repr__ to anomaly score threshold * Revert patchcore config * Add memory bank modules for anomaly detection * Add explanation to MemoryBankTorchModule docstring. * Update memory bank module imports and fix typo in Padim model * Rename Dynamic Buffer Module to Memory Bank Module in docstring. * Revert "Add explanation to MemoryBankTorchModule docstring." This reverts commit 44c991450f7c78eee2b0ceb0e7c855c3893a0801. * Refactor memory bank modules based on Dick's suggestion * Fix model attribute assignment in lightning models * Add MemoryBankMixin to anomaly detection models * revert padim and patchcore * Reorder inheritance in anomaly detection models --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Migrate unit tests Part 7 (#1490) * Refactor CLI tests * Add api tests * Select a random model * Fix test for all the models * Fix API tests * refactor pre-post processing + get model ckpt from fixture * Add tests for custom transforms * Migrate deploy tests * Migrate model component tests * Migrate visualizer callback + cli tests * Fix lightning entrypoint test * trained_padim_path->ckpt_path * Migrate metrics tests * Migrate tools + remove nightly * Increase coverage * Migrate remaining tests * Fix imports * Fix import * Update tests/unit/deploy/test_inferencer.py Co-authored-by: Samet Akcay <[email protected]> * Update test_get_logger.py --------- Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Fix circular import in cdf normalizer (#1494) * fix circular import in cdf normalizer * fix pre-commit --------- Co-authored-by: Samet Akcay <[email protected]> * π οΈ Refactor: Split models to image and video (#1493) * Move AiVad to anomalib.video * Move cfa to models.image * Add Ganomaly model to image models * Add Fastflow model to image models * Add EfficientAd anomaly detection model to image models * Move dfm, dfkde and draem * Add CS-Flow model implementation for image-based defect detection * Add cflow to image models * Add padim to image models * Add patchcore to image models * Add Reverse distillation to image models. * Add rkde to image models * Add stfpm to image models. * Add image models for handling image datasets in anomalib * Update copyright year in model files * Update import statement for Fastflow model * Update image and video model documentation * Update src/anomalib/models/video/README.md Co-authored-by: Dick Ameln <[email protected]> * Update clip_length_in_frames parameter in AvenueDataset and Avenue classes * Remove folder references * Fix a typo in readme * Fix shape of image in batch * Update clip_length_in_frames parameter --------- Co-authored-by: Dick Ameln <[email protected]> * v1: Update the readme file (#1503) * Fix metadata path * Ignore hidden directories in folder dataset * Add check for mask_dir for segmentation tasks in Folder dataset * Replace docs * Add each inferencing scripts as a details section * update readme * Add training * modify getting started * Make getting started a subsection * tmp * Added inference section * Refactor Lightning inference code * Update entry point in setup.py * Add training api example to readme * Update training command in README * Fix bug in login functionality * Update HPO and Logging Documentation * refactor getting started section * Update HPO and benchmarking commands * Update the image * Update README.md Co-authored-by: Dick Ameln <[email protected]> * Update README.md Co-authored-by: Dick Ameln <[email protected]> * Remove getting started section * Update README.md Co-authored-by: Dick Ameln <[email protected]> * Update README.md Co-authored-by: Dick Ameln <[email protected]> * Address the reviewer comments --------- Co-authored-by: Dick Ameln <[email protected]> * Extend Engine Tests (#1509) * Add validate + predict * Add train * Add export tests + refactor export cli command * Fix tests * Fix jupyternotebook --------- Co-authored-by: Ashwin Vaidya <[email protected]> * v1: Create the new documentation via `sphinx-design` and `myst` (#1518) * removed docs * Created the new docs * Finished get started * Remove jupyter notebook from docs * Add mvtec to data * Add reference guide * Add section for each image datasets * Add base data modules and datasets * v1 - π Update and Enhance Docstrings (#1532) * removed docs * Created the new docs * Finished get started * Remove jupyter notebook from docs * Add mvtec to data * Add reference guide * initial commit * Remove subrocess from btech * Remove unused import and commented out code * Add section for each image datasets * Add base data modules and datasets * Refactor dataset classes and add docstrings * Add initial draft for backbone docs * Update the docstring in folder_3d * Update mvtec 3d docstring * Added feature extractor tutorial * Add a readme file to the docs * Update folder data docstring * Update kolektor docstrings * Update kolektor docstring * Update mvtec docstring * Update visa docstrings * Update avenue docstring * Update cfa docstring * Update cflow docstring * Update csflow docstring * Update csflow docstring * Update dfkde docstrings * Update dfm docstring * Update draem docstring * Update efficient ad docstring * Update ganomaly docstring * Update padim and patchcore docstrings * Update reverse distillation docstring * update rkde docstring * update stfpm docstring * Update ai-vad docstring * Update feature extractors * add docstring to sparse random projection * Update dimensionality reduction components * Exclude prompt from copying * Normalizing flow update * Add pro * Add feature extractor docs * update aupr * Update aupr * Update aupro * Update auroc * Update docs/source/markdown/guides/how_to/models/feature_extractors.md * Update f1 and manual thresholds * add minmax * add optimal f1 * update utils * update comet * add tensorboard * update wandb * Add callbacks * Update deploy docstrings * Fix pre-commit on Blasz changes * Change the requirement file in readthedocs config file * Partially address pr comments * Fix the model to padim for the cli integration tests --------- Co-authored-by: BlaΕΎ Rolih <[email protected]> Co-authored-by: Blaz Rolih <[email protected]> * Fix AI-VAD issues (#1524) * partially fix empty bbox issue * allow empty region detections * add torch implementation of gmm (WIP) * make knn mem bank persistent * set val_split_mode to same_as_test as default to enforce deterministicness * add unit tests and docstrings to gmm * improve typing of knn estimator * remove todo * update buffer name * fix minor mistakes in gmm implementation * remove unnecessary tensor conversion * fix visualization when predicting with video model * add __init__.py to components.cluster * check for empty bboxes in feature extractor * reduce default batch size * cast deep features to float * fix device issue * add unit tests for feature extractors * add license header * disable random model selection in integration tests * typing and docstrings * add test case for non-convergence warning * π v1 - Docs: Create a dedicated section for each model. (#1540) * Initial commit for model components * FIx the grid in model components * Add image models * Add video models * Fix titles and do some cleanup * reduce the sphinx version as it fails the readthedocs builds * Fix examples for reading transforms from albumentations Compose object and deserializing from a yaml file * Update __init__.py * OpenVINO NNCF updates (#1534) * Update versions of openvino and nncf * All export functions return the model path * Change default OV device to AUTO * Minor changes on openvino API * Fix pre-commit issues * Restored onnx dependency * Added OV export tests * Drop export tests * Rename path var * Renamed test paths * [Docs] Add average score to the FastFlow's performance results tables (#1587) Add average score in the tables of performance results * Update the paper title in CS-FLOW and CFLOW readme (#1579) * Fix csflow name in readme * Update cflow name in readme * v1 - [Refactor] Reflect the changes in #1562 into v1 (#1595) Reflect the changes in #1562 into v1 * βοΈ Refactor `ExportMode` to `ExportType` (#1594) * Update export_mode to export_type * Fix typo typel -> model * Revert the python version in the notebook * π v1 - Modify the PR template (#1596) * Modify the PR template * Update pull_request_template.md * added emojis to the checklist * [Bug] v1: Fix default input normalization method (#1583) Fix default input normalization method * Modify `Engine.predict` (#1514) * Add validate + predict * Add train * Add export tests + refactor export cli command * Fix tests * Fix jupyternotebook * Update engine.predict + expand tests * Fix lightning entrypoint test * Address PR comments * Use only Padim * Fix commands * Move padim to common args * Address 1st PR comment * Address PR comments * Fix aivad tests * Fix missing docstring * Rename config to args * Add missing ckpt_path warning in predict * Remove ckpt_path as required parameter * Add tests for image path in predict * Fix image path in predict * Address PR comments * Fix missing checkpoint path * Fix fastflow precommit issue * Fix tests * Fix test --------- Co-authored-by: Ashwin Vaidya <[email protected]> * Fix issue with incorrect image save location (#1515) Co-authored-by: Ashwin Vaidya <[email protected]> * Upgrade gradio version to 4.x (#1608) * upgrade gradio version to 4.x * refactor variable names * refactor --------- Co-authored-by: Ashwin Vaidya <[email protected]> * β InferenceDataset->PredictDataset (#1544) * β InferenceDataset->PredictDataset * update predict dataset references * update predict dataset references * update predict dataset references * update predict dataset references * update predict dataset references * update notebook --------- Co-authored-by: Ashwin Vaidya <[email protected]> * `FeatureExtractor` -> `TimmFeatureExtractor` (#1543) Deprecate FeatureExtractor Co-authored-by: Ashwin Vaidya <[email protected]> * Add `LearningType` and refactor enums (#1598) * add LearningType and move enums to separate module * add enum definitions * move shared enums to root init * place version above enums * π Add custom data tutorial (#1571) * Add custom data tutorial * Add the custom data training instructions * Address PR comments * Start with a classification data * Release hazelnut toy dataset and refer to the link here. * Update docs/source/markdown/guides/how_to/data/custom_data.md Co-authored-by: Dick Ameln <[email protected]> * Update docs/source/markdown/guides/how_to/data/custom_data.md Co-authored-by: Dick Ameln <[email protected]> * Update docs/source/markdown/guides/how_to/data/custom_data.md Co-authored-by: Dick Ameln <[email protected]> * Remove no-val-test section from tutorials * Address PR comments --------- Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Add URL verification for downloading dataset (#1620) * add url path verification for dataset downloading module * specify node version to pre-commit-config * fix import errors on the notebooks * π v1 - Fix training with mps accelerator (#1618) * Convert mask to float32 in AnomalibDataset * Convert the tensor to cpu before convrting to numpy * replace np.float32 with np.single * Update Engine docstrings (#1549) Update docstrings Co-authored-by: Ashwin Vaidya <[email protected]> * Fixed shape error, allowing arbitary image sizes for EfficientAD * Revert the previous commit * Extend supported models in TimmFeatureExtractor (#1443) Extend Timm feature extractor for v1.0 * π v1 - Address security issues (#1637) * Address path traversal issues 1-3 * address traversal path 6 * Address traverse path 8 * modify the comment to make it more descriptive * π Fix mps float64 tensor conversion issue (#1644) Fix leftover * π Fix metadata_path arg to metadata in OpenVINO inferencer (#1648) Fix metadata_path arg to metadata in OpenVINO inferencer * π Address path traversal issues (#1643) * Address path traversal issues 1-3 * address traversal path 6 * Address traverse path 8 * modify the comment to make it more descriptive * Update get_image_filename function to enhance the input security * fix example * Fix incorrect default value assignment * Refactor project_path fixture to create temporary directory in the root directory of the project * Update .gitignore file to include test-related files and directories * Refactor get_image_filenames_from_dir to filter out non-image files * Add test case for path outside base directory * Add examples to get_filenames * Address PR comments. * Renamed the tmp dir * CVS-129503 * add validate_path to anomalib.data.utils.path * Validate depth path * π Add `SECURITY.md` file (#1655) * Add SECURITY.md file * Add security item to the type of changes in the pull request template. * Update pr template * replace the security emoji * Validate path in make_dataset functions * Add a check whether path contains null byte * fix tests * Remove duplicated tests that causes the ci fail * π Add zero-/few-shot model support and WinCLIP model implementation (#1575) * add clip normalization * initial commit for winclip * add cosine similarity computation * add multiscale score computation * simplify mask generation * add few-shot extension (unvalidated) * refactor * cleanup * add todo * formatting * minor refactor * add comment * expose optimal F1 metric * some cleanup * add ln_after_pool logic * remove final_ln_after_pool * update module docstring and remove comments * add typing and docstrings to torch model * cleanup lightning model * hardcode backbone * n_shot -> k_shot * add temperature as constant * minor bugfix * add typing and docstrings to utils * set class name dynamically * replace inf values in harmonic aggregation * run validate before test * set default class name to None * formatting * remove config * comments * minor bugfix * Revert "expose optimal F1 metric" This reverts commit e8e1ead9601d76c743af3678f26b1eb0e06d38fb. * more descriptive assert message * expose scales as configurable parameter and hardcode pretrained as constant * add readme * add images for readme * update docstrings * update license headers * ruff * add openclip as requirement * skip model tests for winclip * fix visualizer test * add example in docstring * fix typo in function name * typing * imports * docstrings * check if model has trainer attribute * remove pylint ignore statement * typing * docstring * improve tensor shape handling * refactor and rename class_scores function * add docstring example * commenting * Update src/anomalib/models/image/winclip/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/image/winclip/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/image/winclip/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * formatting * docstrings * docstrings * comment * typing * multiscale -> multi_scale * add winclip to docs * add few_shot_source parameter * use PredictDataset in WinCLIP implementation * add learning type to winclip lightning model * add custom model checkpoint callback to save at validation end * remove trainer arguments from winclip model * prune state dict for smaller model file * add learning type logic to engine.train * pass full path to model checkpoint * remove training step * enable integration tests for winclip * fix typo * index masks at 0 * formatting * simplify make_masks * validate inputs in make_masks * add unit tests for winclip utils * add default class_name to prompt ensemble * add unit tests for winclip prompt ensemble * add base class for normalization callback * add _should_run_validation check * add engine.model property * use custom modelcheckpoint in tests * update name in todos * fix predict tests * skip export tests for winclip * fix mistake in model retrieval from trainer * add model checks * fix checks * simplify model check * add todo for winclip export * add todo * add bufferlist mixin * update bufferlist docstring * add setup method and register buffers * import torch model in root of winclip module * add unit tests for bufferlist mixin * add unit tests for torch model * fix transform and update docstring * disable strict loading in export * initialize embeddings as tensors * add test to check if erors are raised * add todo * enable winclip export test * remove device references in torch model * restore frozen weights in load_state_dict * make embedding collection methods private * move state dict handling to winclip from base * fix typo * make generate_masks private * increase onnx opset version * remove future import * update docstring * Update src/anomalib/callbacks/normalization/__init__.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/callbacks/normalization/cdf_normalization.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/callbacks/normalization/min_max_normalization.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * typing in docstrings * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/engine/engine.py Co-authored-by: Samet Akcay <[email protected]> * use exception instead of assert * update license header * docstrings * bufferlist -> buffer_list --------- Co-authored-by: Samet Akcay <[email protected]> * Check if the path too long and contains non-printable chars * WinCLIP attribution (#1662) give credit to related works * π Merge main to v1 (#1652) * Address tiler issues (#1411) * fix tiler * deprecate random tile locations * restore random tiling in tile method * check tiling section in config * disable tiling for ganomalu * pad -> padding * Refactor Reverse Distillation to match official code (#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 <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/reverse_distillation/README.md Co-authored-by: Samet Akcay <[email protected]> * Remove early_stopping * Update src/anomalib/models/reverse_distillation/lightning_model.py Co-authored-by: Samet Akcay <[email protected]> * Easier to read code --------- Co-authored-by: Samet Akcay <[email protected]> * Patch for the WinError183 on the OpenVino export mode (#1386) * Fix WinError183 (Windows Error) * Add commentary of the change --------- Co-authored-by: Youho99 <[email protected]> * Add DSR model (#1142) * 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 <[email protected]> * Apply suggestions from code review Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * 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 <[email protected]> * 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 <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> * Fix unexpected key pixel_metrics.AUPRO.fpr_limit (#1055) * fix unexpected key pixel_metrics.AUPRO.fpr_limit Signed-off-by: FanJiangIntel <[email protected]> * load AUPRO before create_metric_collection Signed-off-by: FanJiangIntel <[email protected]> * code refine Signed-off-by: FanJiangIntel <[email protected]> * fix comment Signed-off-by: FanJiangIntel <[email protected]> * fix Signed-off-by: FanJiangIntel <[email protected]> * Support test Signed-off-by: Kang Wenjing <[email protected]> * Update test Signed-off-by: Kang Wenjing <[email protected]> * Update test Signed-off-by: Kang Wenjing <[email protected]> --------- Signed-off-by: FanJiangIntel <[email protected]> Signed-off-by: Kang Wenjing <[email protected]> Co-authored-by: FanJiangIntel <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Improved speed and memory usage of mean+std calculation (#1457) * preexisting OpenCV version check added to `setup.py`, ran formatting pre-commit hooks on previous contribution. (#1424) * testing upstream switch * picked up on stale OpenCV `setup.py` issue #1041 * π Hotfix: Limit Gradio Version (#1458) * 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 * Fix/efficient ad normalize before every validation (#1441) * Normalize anomaly maps before every validation * Remove print statement --------- Co-authored-by: Samet Akcay <[email protected]> * Fix DRAEM (#1431) * 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 * Adding U-Flow method (#1415) * 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 <[email protected]> * Update src/anomalib/models/uflow/anomaly_map.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/uflow/feature_extraction.py Co-authored-by: Samet Akcay <[email protected]> * Update src/anomalib/models/uflow/torch_model.py Co-authored-by: Samet Akcay <[email protected]> * 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 <[email protected]> * Update README.md * π Announce anomalib v1 on the main `README.md` (#1542) * 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 (#1486) * fixed DSR squeeze bug * added comment * Refactor/extensions custom dataset (#1562) * 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 * π Modify the PR template (#1611) Update pull_request_template.md * Fix result image URLs (#1510) * Fix tests * refactor path + fix issues + fix linting issues * Migrate docs * fix typing * fix failing model tests * Fix tests * Address PR comments * Fixed shape error, allowing arbitary image sizes for EfficientAD (#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 * Clean up badge --------- Signed-off-by: FanJiangIntel <[email protected]> Signed-off-by: Kang Wenjing <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: abc-125 <[email protected]> Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: ggiret-thinkdeep <[email protected]> Co-authored-by: Youho99 <[email protected]> Co-authored-by: Philippe Carvalho <[email protected]> Co-authored-by: Wenjing Kang <[email protected]> Co-authored-by: FanJiangIntel <[email protected]> Co-authored-by: belfner <[email protected]> Co-authored-by: Abdulla Al Blooshi <[email protected]> Co-authored-by: BlaΕΎ Rolih <[email protected]> Co-authored-by: MatΓas Tailanian <[email protected]> Co-authored-by: Jan SchlΓΌter <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Christopher <[email protected]> * Update license headers * Check symlinks --------- Signed-off-by: FanJiangIntel <[email protected]> Signed-off-by: Kang Wenjing <[email protected]> Signed-off-by: Samet Akcay <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Weilin Xu <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: Ashwin Vaidya <[email protected]> Co-authored-by: abc-125 <[email protected]> Co-authored-by: Harim Kang <[email protected]> Co-authored-by: Dick Ameln <[email protected]> Co-authored-by: BlaΕΎ Rolih <[email protected]> Co-authored-by: Blaz Rolih <[email protected]> Co-authored-by: Adrian Boguszewski <[email protected]> Co-authored-by: Willy Fitra Hendria <[email protected]> Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Yunchu Lee <[email protected]> Co-authored-by: ggiret-thinkdeep <[email protected]> Co-authored-by: Youho99 <[email protected]> Co-authored-by: Philippe Carvalho <[email protected]> Co-authored-by: Wenjing Kang <[email protected]> Co-authored-by: FanJiangIntel <[email protected]> Co-authored-by: belfner <[email protected]> Co-authored-by: Abdulla Al Blooshi <[email protected]> Co-authored-by: MatΓas Tailanian <[email protected]> Co-authored-by: Jan SchlΓΌter <[email protected]> Co-authored-by: Christopher <[email protected]>
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π Description
Mirror #1596 for the main branch.
π οΈ Fixes # N/A
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