Add support for Detection task type #732
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| pl_module.normalization_metrics(outputs["pred_scores"]) | ||
| else: | ||
| raise ValueError("No values found for normalization, provide anomaly maps, bbox scores, or image scores") |
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Should it be image score or pred score? It means the same thing but might confuse the users.
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I agree that image_score would be more suitable, but I feel changing this is outside of the scope of this PR.
samet-akcay
reviewed
Nov 25, 2022
| @@ -14,6 +14,7 @@ | |||
| from .folder import Folder | |||
| from .inference import InferenceDataset | |||
| from .mvtec import MVTec | |||
| from .task_type import TaskType | |||
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would this be used by models and other components as well? If so, would it be an idea to move it to a place that would be accessible by other components?
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Yeah, I'm not super happy with the location of TaskType but couldn't think of a better place. Maybe somewhere in anomalib/config would work? @ashwinvaidya17 any ideas?
I found a few str <--> enum conversion issues at some point when trying to use the cli with config files (somehow the string from the So it made me wonder: are there tests covering this? (i.e. the different values of the enum work properly when being passed from the config file) |
Co-authored-by: Samet Akcay <[email protected]>
This reverts commit cec6138.
I don't think the tests cover this explicitly at the moment. Which enum was causing problems at your end? |
Honestly I don't remember because it was blocking me to use the new cli so I dropped the ball. |
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@ashwinvaidya17 @samet-akcay I've updated the PR based on your comments, and also added test cases and inference support. So it's ready for the next round of review. |
ashwinvaidya17
approved these changes
Dec 5, 2022
| raise ValueError(f"Unknown task type: {mode}. Please choose one of ['classification', 'segmentation']") | ||
| if task not in [TaskType.CLASSIFICATION, TaskType.DETECTION, TaskType.SEGMENTATION]: | ||
| raise ValueError( | ||
| f"Unknown task type: {mode}. Please choose one of ['classification', 'detection', 'segmentation']" |
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Not really necessary here but I wonder if f"Unknown task type: {mode}. Please choose one of {TaskType.__members__.values()} will work here. But will not make it a very descriptive docstring for the programmers.
djdameln
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Jan 6, 2023
* New datamodules design (#572) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add base classes * update docstring * fix imports * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * fix typo Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Joao P C Bertoldo <[email protected]> * Video Datamodules (#676) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add base classes * update docstring * fix imports * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add pedestrian and avenue datasets and video utils * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * add basic visualization for video datasets * simplify ucsdped implementation * add ucsd and avenue to __all__ * add default value for task * add tests for ucsd and avenue * add tests for video dataset and utils * add download info for avenue dataset * add download info for ucsd pedestrian dataset * more consistent naming * fix path to masks folder in gt dir * pass original image in batch to facilitate visualization * convert mask files for avenue * suppress warning due to torchvision bug * fix bug in avenue masks * store visualizations for each video in separate folder * rename parameters * add warning for clip_length > 1 * fix dataset tests * fix labels tensor shape bug * add pyav to requirements * add description for avenue dataset * use pathlib * Update anomalib/data/avenue.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/avenue.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/utils/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/base/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/base/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/ucsd_ped.py Co-authored-by: Samet Akcay <[email protected]> * import video dataset from base * fix bug when collecting ucsd samples * clean up datamodules tests * fix tests * remove redundant test cases * retrieve masks as numpy array * use pathlib * variable name * pathlib * use preprocesser from arguments * fix indexing bug Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Update lightning_inference.py * Make `val split ratio` configurable (#760) * make val split ratio configurable * use DeprecationWarning, update config key * Add support for Detection task type (#732) * add basic support for detection task * use enum for task type * formatting * small bugfix * add unit tests for bounding box conversion * update error message * use as_tensor * typing and docstring * explicit keyword arguments * simplify bbox handling in video dataset * docstring consistency * add missing licenses * add whitespace for readability * add missing license * Update anomalib/data/utils/boxes.py Co-authored-by: Samet Akcay <[email protected]> * Revert "Update anomalib/data/utils/boxes.py" This reverts commit cec6138. * add test case for custom collate function * docstring * add integration tests for detection dataloading * extend and clean up datamodules tests * add detection task type to visualizer tests * only show pred_boxes during inference * add detection support for torch inference * add detection support for openvino inference * test inference for all task types * pylint Co-authored-by: Samet Akcay <[email protected]> * [Datamodules] Update deprecation messages (#764) * update deprecation messages * raise warnings as DeprecationWarning * Improve image source parsing for Folder dataset (#784) * mask -> mask_dir * properly handle absolute and relative paths * make root path parameter optional * formatting * path -> root * update docs * remove options hint for name parameter * refactor function * Update anomalib/config/config.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/config/config.py Co-authored-by: Samet Akcay <[email protected]> * make root and abnormal_dir optional * Update anomalib/data/folder.py Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Synthetic anomaly for testing and validation (#634) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add synthetic dataset class * move augmenter to data directory * add base classes * update docstring * use synthetic dataset in base datamodule * fix imports * clean up synthetic anomaly dataset implementation * fix mistake in augmenter * change default split ratio * remove accidentally added file * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * add logging message * use val_split_ratio for synthetic validation set * pathlib * make synthetic anomaly available for test set * update configs * add tests * simplify test set splitting logic * update docstring * add missing licence * split_normal_and_anomalous -> split_by_label * VideoAnomalib -> AnomalibVideo Co-authored-by: Joao P C Bertoldo <[email protected]> * Bugfixes for Datamodules feature branch (#800) * properly handle NoneType mask_dir and add test case * fix wrong deprecation handling * Deprecate PreProcessor (#795) * deprecate PreProcessor * update configs * update deprecation messages * update video dataset * update inference dataset * move transforms to data module * update and extend transform tests * fix cyclic import * add validity checks for image size and center crop * pass image size as tuple * update path to get_transforms * update error message * fix center crop tuple conversion * update inferencers * remove draem transform config * update changelog * fix cyclic import * add crop size vs image size check * improve readability * mypy * use enum to configure input normalization * update lightning inference * update inference dataset * [Datamodules] Fix bug in bbox score to image score conversion (#803) handle empty box predictions * Improve handling of `test_split_mode='none'` and `val_split_mode='none'` (#801) * enable none as split mode * use get to retrieve config keys * update deprecation message and config key * fix to float transform * Detection improvements (#820) * apply pixel threshold to bbox detections * allow visualizing normal boxes * normalize box scores * fix bbox logic in base anomaly module * boxes_scores -> box_scores * fix inferencers * update changelog * update csflow config to new format * remove unused imports * line length * suppress bandit warnings * use torch rng in augmenter * use tuple instead of list * add missing params to dosctring * add missing licence information * COLS -> COLUMNS * typing and variable naming * remove duplicate parameter in docstring * im_dir -> image_dir * typing and docstring * typing * ValSplitMode -> ValidationSplitMode * add missing licence * rename variable * remove empty comment * remove unused class attribute * [Detection] Compute box score when generating boxes from masks (#828) * infer box scores from anomaly maps * discard single pixel boxes * revert discard single pixel boxes * add test case for bbox scores * update torch inferencer * minor refactor * revert val_split_mode -> validation_split_mode Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Samet Akcay <[email protected]>
djdameln
added a commit
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Jan 6, 2023
* New datamodules design (#572) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add base classes * update docstring * fix imports * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * fix typo Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Joao P C Bertoldo <[email protected]> * Video Datamodules (#676) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add base classes * update docstring * fix imports * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add pedestrian and avenue datasets and video utils * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * add basic visualization for video datasets * simplify ucsdped implementation * add ucsd and avenue to __all__ * add default value for task * add tests for ucsd and avenue * add tests for video dataset and utils * add download info for avenue dataset * add download info for ucsd pedestrian dataset * more consistent naming * fix path to masks folder in gt dir * pass original image in batch to facilitate visualization * convert mask files for avenue * suppress warning due to torchvision bug * fix bug in avenue masks * store visualizations for each video in separate folder * rename parameters * add warning for clip_length > 1 * fix dataset tests * fix labels tensor shape bug * add pyav to requirements * add description for avenue dataset * use pathlib * Update anomalib/data/avenue.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/avenue.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/utils/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/base/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/base/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/ucsd_ped.py Co-authored-by: Samet Akcay <[email protected]> * import video dataset from base * fix bug when collecting ucsd samples * clean up datamodules tests * fix tests * remove redundant test cases * retrieve masks as numpy array * use pathlib * variable name * pathlib * use preprocesser from arguments * fix indexing bug Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Update lightning_inference.py * Make `val split ratio` configurable (#760) * make val split ratio configurable * use DeprecationWarning, update config key * Add support for Detection task type (#732) * add basic support for detection task * use enum for task type * formatting * small bugfix * add unit tests for bounding box conversion * update error message * use as_tensor * typing and docstring * explicit keyword arguments * simplify bbox handling in video dataset * docstring consistency * add missing licenses * add whitespace for readability * add missing license * Update anomalib/data/utils/boxes.py Co-authored-by: Samet Akcay <[email protected]> * Revert "Update anomalib/data/utils/boxes.py" This reverts commit cec6138. * add test case for custom collate function * docstring * add integration tests for detection dataloading * extend and clean up datamodules tests * add detection task type to visualizer tests * only show pred_boxes during inference * add detection support for torch inference * add detection support for openvino inference * test inference for all task types * pylint Co-authored-by: Samet Akcay <[email protected]> * [Datamodules] Update deprecation messages (#764) * update deprecation messages * raise warnings as DeprecationWarning * Improve image source parsing for Folder dataset (#784) * mask -> mask_dir * properly handle absolute and relative paths * make root path parameter optional * formatting * path -> root * update docs * remove options hint for name parameter * refactor function * Update anomalib/config/config.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/config/config.py Co-authored-by: Samet Akcay <[email protected]> * make root and abnormal_dir optional * Update anomalib/data/folder.py Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Synthetic anomaly for testing and validation (#634) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add synthetic dataset class * move augmenter to data directory * add base classes * update docstring * use synthetic dataset in base datamodule * fix imports * clean up synthetic anomaly dataset implementation * fix mistake in augmenter * change default split ratio * remove accidentally added file * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * add logging message * use val_split_ratio for synthetic validation set * pathlib * make synthetic anomaly available for test set * update configs * add tests * simplify test set splitting logic * update docstring * add missing licence * split_normal_and_anomalous -> split_by_label * VideoAnomalib -> AnomalibVideo Co-authored-by: Joao P C Bertoldo <[email protected]> * Bugfixes for Datamodules feature branch (#800) * properly handle NoneType mask_dir and add test case * fix wrong deprecation handling * Deprecate PreProcessor (#795) * deprecate PreProcessor * update configs * update deprecation messages * update video dataset * update inference dataset * move transforms to data module * update and extend transform tests * fix cyclic import * add validity checks for image size and center crop * pass image size as tuple * update path to get_transforms * update error message * fix center crop tuple conversion * update inferencers * remove draem transform config * update changelog * fix cyclic import * add crop size vs image size check * improve readability * mypy * use enum to configure input normalization * update lightning inference * update inference dataset * [Datamodules] Fix bug in bbox score to image score conversion (#803) handle empty box predictions * Improve handling of `test_split_mode='none'` and `val_split_mode='none'` (#801) * enable none as split mode * use get to retrieve config keys * update deprecation message and config key * fix to float transform * Detection improvements (#820) * apply pixel threshold to bbox detections * allow visualizing normal boxes * normalize box scores * fix bbox logic in base anomaly module * boxes_scores -> box_scores * fix inferencers * update changelog * update csflow config to new format * remove unused imports * line length * refactor make_mvtec_dataset to improve flexibility * add visa dataset * move download and extract functionality to shared location * move visa subset splitting to separate method * update changelog * add tests for visa dataset * suppress bandit url warning * update test * address PR comments * suppress bandit warnings * use torch rng in augmenter * fix logic in prepare_data * add comments * cleaner zipfile import * address PR comments * use tuple instead of list * add missing params to dosctring * add missing licence information * COLS -> COLUMNS * typing and variable naming * remove duplicate parameter in docstring * im_dir -> image_dir * typing and docstring * typing * ValSplitMode -> ValidationSplitMode * add missing licence * rename variable * remove empty comment * remove unused class attribute * [Detection] Compute box score when generating boxes from masks (#828) * infer box scores from anomaly maps * discard single pixel boxes * revert discard single pixel boxes * add test case for bbox scores * update torch inferencer * minor refactor * revert val_split_mode -> validation_split_mode * use empty string instead of nan as empty mask path * typing Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Samet Akcay <[email protected]>
djdameln
added a commit
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Jan 6, 2023
* fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add base classes * update docstring * fix imports * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add pedestrian and avenue datasets and video utils * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * Created rbad directory * Keep refactoring region-extractor * rename new_image_sizes to transformed_image_sizes * Renamed the variables in region extractor * post-process function in region extractor * Refactored tile-boxes function * Added feature extractor * Add main.py * Added feature extractor to tests * Update the jupyter notebook * Uncomment loa weights from region.py * Add feature and region extractors * Finished feature-extractor implementation * Rename the algo as rkde * New datamodules design (#572) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add base classes * update docstring * fix imports * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * fix typo Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Joao P C Bertoldo <[email protected]> * add basic visualization for video datasets * simplify ucsdped implementation * TODO: Investigate torch_model * add ucsd and avenue to __all__ * add default value for task * add tests for ucsd and avenue * add tests for video dataset and utils * add download info for avenue dataset * add download info for ucsd pedestrian dataset * more consistent naming * fix path to masks folder in gt dir * pass original image in batch to facilitate visualization * convert mask files for avenue * suppress warning due to torchvision bug * fix bug in avenue masks * store visualizations for each video in separate folder * rename parameters * add warning for clip_length > 1 * fix dataset tests * fix labels tensor shape bug * add pyav to requirements * Add TODO notes * add todo notes * add description for avenue dataset * use pathlib * Update anomalib/data/avenue.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/avenue.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/utils/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/base/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/base/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/ucsd_ped.py Co-authored-by: Samet Akcay <[email protected]> * import video dataset from base * fix bug when collecting ucsd samples * clean up datamodules tests * fix tests * remove redundant test cases * add test case for normality model * retrieve masks as numpy array * use pathlib * variable name * pathlib * use preprocesser from arguments * fix indexing bug * Video Datamodules (#676) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add base classes * update docstring * fix imports * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add pedestrian and avenue datasets and video utils * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * add basic visualization for video datasets * simplify ucsdped implementation * add ucsd and avenue to __all__ * add default value for task * add tests for ucsd and avenue * add tests for video dataset and utils * add download info for avenue dataset * add download info for ucsd pedestrian dataset * more consistent naming * fix path to masks folder in gt dir * pass original image in batch to facilitate visualization * convert mask files for avenue * suppress warning due to torchvision bug * fix bug in avenue masks * store visualizations for each video in separate folder * rename parameters * add warning for clip_length > 1 * fix dataset tests * fix labels tensor shape bug * add pyav to requirements * add description for avenue dataset * use pathlib * Update anomalib/data/avenue.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/avenue.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/utils/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/base/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/base/video.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/data/ucsd_ped.py Co-authored-by: Samet Akcay <[email protected]> * import video dataset from base * fix bug when collecting ucsd samples * clean up datamodules tests * fix tests * remove redundant test cases * retrieve masks as numpy array * use pathlib * variable name * pathlib * use preprocesser from arguments * fix indexing bug Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * properly handle batch processing * include batch index in rois tensor * return rkde results as lists * update default rkde config * add basic support for detection task * use enum for task type * formatting * small bugfix * add unit tests for bounding box conversion * update error message * use as_tensor * typing and docstring * explicit keyword arguments * simplify bbox handling in video dataset * docstring consistency * add missing licenses * add whitespace for readability * add missing license * Update anomalib/data/utils/boxes.py Co-authored-by: Samet Akcay <[email protected]> * Revert "Update anomalib/data/utils/boxes.py" This reverts commit cec6138. * add test case for custom collate function * docstring * add integration tests for detection dataloading * extend and clean up datamodules tests * add detection task type to visualizer tests * Update lightning_inference.py * only show pred_boxes during inference * add detection support for torch inference * add detection support for openvino inference * test inference for all task types * pylint * Make `val split ratio` configurable (#760) * make val split ratio configurable * use DeprecationWarning, update config key * Add support for Detection task type (#732) * add basic support for detection task * use enum for task type * formatting * small bugfix * add unit tests for bounding box conversion * update error message * use as_tensor * typing and docstring * explicit keyword arguments * simplify bbox handling in video dataset * docstring consistency * add missing licenses * add whitespace for readability * add missing license * Update anomalib/data/utils/boxes.py Co-authored-by: Samet Akcay <[email protected]> * Revert "Update anomalib/data/utils/boxes.py" This reverts commit cec6138. * add test case for custom collate function * docstring * add integration tests for detection dataloading * extend and clean up datamodules tests * add detection task type to visualizer tests * only show pred_boxes during inference * add detection support for torch inference * add detection support for openvino inference * test inference for all task types * pylint Co-authored-by: Samet Akcay <[email protected]> * [Datamodules] Update deprecation messages (#764) * update deprecation messages * raise warnings as DeprecationWarning * update rkde * Improve image source parsing for Folder dataset (#784) * mask -> mask_dir * properly handle absolute and relative paths * make root path parameter optional * formatting * path -> root * update docs * remove options hint for name parameter * refactor function * Update anomalib/config/config.py Co-authored-by: Samet Akcay <[email protected]> * Update anomalib/config/config.py Co-authored-by: Samet Akcay <[email protected]> * make root and abnormal_dir optional * Update anomalib/data/folder.py Co-authored-by: Samet Akcay <[email protected]> Co-authored-by: Samet Akcay <[email protected]> * Synthetic anomaly for testing and validation (#634) * move sample generation to datamodule instead of dataset * move sample generation from init to setup * remove inference stage and add base classes * replace dataset classes with AnomalibDataset * move setup to base class, create samples as class method * update docstrings * refactor btech to new format * allow training with no anomalous data * remove MVTec name from comment * raise NotImplementedError in base class * allow both png and bmp images for btech * use label_index to check if dataset contains anomalous images * refactor getitem in dataset class * use iloc for indexing * move dataloader getters to base class * refactor to add validate stage in setup * implement alternative datamodules solution * small improvements * improve design * remove unused constructor arguments * adapt btech to new design * add prepare_data method for mvtec * implement more generic random splitting function * update docstrings for folder module * ensure type consistency when performing operations on dataset * change imports * change variable names * replace pass with NotImplementedError * allow training on folder without test images * use relative path for normal_test_dir * fix dataset tests * update validation set parameter in configs * change default argument * use setter for samples * hint options for val_split_mode * update assert message and docstring * revert name change dataset vs datamodule * typing and docstrings * remove samples argument from dataset constructor * val/test -> eval * remove Split.Full from enum * sort samples when setting * update warn message * formatting * use setter when creating samples in dataset classes * add tests for new dataset class * add test case for label aware random split * update parameter name in inferencers * move _setup implementation to base class * address codacy issues * fix pylint issues * codacy * update example dataset config in docs * fix test * move base classes to separate files (avoid circular import) * add synthetic dataset class * move augmenter to data directory * add base classes * update docstring * use synthetic dataset in base datamodule * fix imports * clean up synthetic anomaly dataset implementation * fix mistake in augmenter * change default split ratio * remove accidentally added file * validation_split_mode -> val_split_mode * update docs * Update anomalib/data/base/dataset.py Co-authored-by: Joao P C Bertoldo <[email protected]> * get length from self.samples * assert unique indices * check is_setup for individual datasets Co-authored-by: Joao P C Bertoldo <[email protected]> * remove assert in __getitem_\ Co-authored-by: Joao P C Bertoldo <[email protected]> * Update anomalib/data/btech.py Co-authored-by: Joao P C Bertoldo <[email protected]> * clearer assert message * clarify list inversion in comment * comments and typing * validate contents of samples dataframe before setting * add file paths check * add seed to random_split function * fix expected columns * fix typo * add seed parameter to datamodules * set global seed in test entrypoint * add NONE option to valsplitmode * clarify setup behaviour in docstring * add logging message * use val_split_ratio for synthetic validation set * pathlib * make synthetic anomaly available for test set * update configs * add tests * simplify test set splitting logic * update docstring * add missing licence * split_normal_and_anomalous -> split_by_label * VideoAnomalib -> AnomalibVideo Co-authored-by: Joao P C Bertoldo <[email protected]> * Bugfixes for Datamodules feature branch (#800) * properly handle NoneType mask_dir and add test case * fix wrong deprecation handling * Deprecate PreProcessor (#795) * deprecate PreProcessor * update configs * update deprecation messages * update video dataset * update inference dataset * move transforms to data module * update and extend transform tests * fix cyclic import * add validity checks for image size and center crop * pass image size as tuple * update path to get_transforms * update error message * fix center crop tuple conversion * update inferencers * remove draem transform config * update changelog * fix cyclic import * add crop size vs image size check * improve readability * mypy * use enum to configure input normalization * update lightning inference * update inference dataset * expose more parameters and fix wrong return format * fix tdd tests * update config * [Datamodules] Fix bug in bbox score to image score conversion (#803) handle empty box predictions * update config * apply pixel threshold to bbox detections * remove confidence threshold parameter from rkde * hardcode steepness and offset * rename variable * remove unused parameters from config * Improve handling of `test_split_mode='none'` and `val_split_mode='none'` (#801) * enable none as split mode * use get to retrieve config keys * update deprecation message and config key * update config with new keys * remove unused parameter * set device in rpn stage * move prediction format conversion to lightning model * clean up torch model * move region- and feature-extractor to separate files * allow visualizing normal boxes * refactor * WIP: simplify region extractor * simplify region extractor * cleanup and docstrings * typing * expose max detections per image parameter * explain configurable parameters * fix wrong config value * remove unnecessary squeeze * box_likelihood -> rcnn_box_threshold * update comments * remove unnecessary typing * separate density estimation stage from torch model * improve readability * change default transform settings * fix to float transform * simplify feature extractor * normalize box scores * further simplify region extractor * update comment * improve prn configurability * remove unnecessary check * use enum for roi stage options * use enum for feature scaling method * re-order parameters * clean up model dir * fix bbox logic in base anomaly module * update key in output dict * boxes_scores -> box_scores * remove notebook * add comments and todo * Detection improvements (#820) * apply pixel threshold to bbox detections * allow visualizing normal boxes * normalize box scores * fix bbox logic in base anomaly module * boxes_scores -> box_scores * fix inferencers * add readme * update changelog * update changelog * update csflow config to new format * initialize max_length as empty tensor * include RKDE in model tests * remove unused imports * line length * move kde classifier to shared location * fix import * re-use RKDE classifier in DFKDE * remove old imports * docstrings * fix codacy issues * load feature extractor weights from url * suppress bandit warnings * use torch rng in augmenter * typing * add fit method to torch model * fix typo * use enum when checking stage * use tuple instead of list * add missing params to dosctring * add missing licence information * COLS -> COLUMNS * typing and variable naming * remove duplicate parameter in docstring * im_dir -> image_dir * typing and docstring * typing * ValSplitMode -> ValidationSplitMode * add missing licence * rename variable * remove empty comment * remove unused class attribute * [Detection] Compute box score when generating boxes from masks (#828) * infer box scores from anomaly maps * discard single pixel boxes * revert discard single pixel boxes * add test case for bbox scores * update torch inferencer * minor refactor * revert val_split_mode -> validation_split_mode Co-authored-by: Joao P C Bertoldo <[email protected]> Co-authored-by: Samet <[email protected]>
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Description
This PR adds the detection task type. This is mainly to support region-based models that produce bounding box predictions instead of / in addition to anomaly maps.
Changes
Major
detectionas task type for a padim model training on MVTec bottle dataset:Minor
collate_fnfunction had to be implemented to allow collating the ground truth bounding boxes across batches.Known issues
No test casesNo inference supportChanges
Checklist