Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Enable training with only normal images for MVTec #1241

Merged
merged 2 commits into from
Aug 7, 2023
Merged

Enable training with only normal images for MVTec #1241

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
7885b0f
ignore mask check when dataset has only normal samples
djdameln Aug 7, 2023
3407f66
update changelog
djdameln Aug 7, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions CHANGELOG.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).

### Changed

- Enable training with only normal images for MVTecv in https://github.com/openvinotoolkit/anomalib/pull/1241
- Improve default settings of EfficientAD

### Deprecated
Expand Down
15 changes: 8 additions & 7 deletions src/anomalib/data/mvtec.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -153,13 +153,14 @@ def make_mvtec_dataset(
] = mask_samples.image_path.values

# assert that the right mask files are associated with the right test images
assert (
samples.loc[samples.label_index == LabelName.ABNORMAL]
.apply(lambda x: Path(x.image_path).stem in Path(x.mask_path).stem, axis=1)
.all()
), "Mismatch between anomalous images and ground truth masks. Make sure the mask files in 'ground_truth' \
folder follow the same naming convention as the anomalous images in the dataset (e.g. image: '000.png', \
mask: '000.png' or '000_mask.png')."
if len(samples.loc[samples.label_index == LabelName.ABNORMAL]):
assert (
samples.loc[samples.label_index == LabelName.ABNORMAL]
.apply(lambda x: Path(x.image_path).stem in Path(x.mask_path).stem, axis=1)
.all()
), "Mismatch between anomalous images and ground truth masks. Make sure the mask files in 'ground_truth' \
folder follow the same naming convention as the anomalous images in the dataset (e.g. image: \
'000.png', mask: '000.png' or '000_mask.png')."

if split:
samples = samples[samples.split == split].reset_index(drop=True)
Expand Down