Comments (5)
Hi @mashuai191, I see that you commented out the following line in your config
#test_split_mode: from_dir # options: [from_dir, synthetic]
If you set this to synthetic
, anomalib would generate some synthetic abnormal images using your normal data. You could then you the segmentation
task. Hope this helps!
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thanks @samet-akcay @blaz-r for your help! i will try at the weekend.
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Hello. All models implemented inside Anomalib support training without abnormal data. I am able to train the model with your config, could you share more details what seems to be the problem on your end?
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hi @blaz-r,
thanks for reply! yes i can train without abnormal data, but i cannot get the localization/segmentation. please see the attached sreenshot.
seems segmentation labels are required for training? if so that is superised training then?
BR, Shuai Ma
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Hello. No, labels are not required and Padim is an unsupervised model. You should get segmented results inside the results folder. If that is what your screenshot depicts, could you please post the entire image (heatmap, ground truth...).
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Related Issues (20)
- [Bug]: Can't download efficientAD pretrained weights HOT 9
- [Bug]: How to solve this problem self.image_threshold = AnomalyScoreThreshold().cpu() HOT 2
- [Bug]: EfficientAd is slower than other models in anomalib HOT 5
- [Task]: Missing modules may fail silently
- [Bug]: Error installing with pip version 24.1 HOT 1
- [Bug]: Issue with `self.model_size` Initialization in `EfficientAD` Class HOT 5
- [Bug]: RuntimeError: vstack expects a non-empty TensorList
- [Bug]: Training Fails on DataBricks Due to symlink not supported in DBFS HOT 2
- [Bug]: Why is training slow to start, about efficientAD? HOT 4
- `AnomalibDataset` is not `ABC` anymore. HOT 8
- [Bug]: train_batch_size for EfficientAd should be 1. HOT 3
- [Bug]: Whether different ways of writing can be unified
- [Task]: Grayscale / Singlechannel Image Support HOT 1
- Does `_setup_transform()` in `Engine.fit` use the train transforms properly? HOT 3
- Empty prediction mask and heatmap using WinCLIP in CLASSIFICATION task HOT 4
- [Bug]: No module named setuptools for Python 3.8.10 HOT 2
- [Task]: Config file hyperparameters HOT 1
- [Bug]: ValueError: Not possible to determine the import path for object typing.Iterable[pytorch_lightning.loggers.logger.Logger]. HOT 4
- [Bug]: Question about PaDiM model validation and testing HOT 1
- [Bug]: WinCLIP export pytorch model issue
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