Tocmac/ReinAD
ReinAD: Towards Real-world Industrial Anomaly Detection with a Comprehensive Contrastive Dataset Our dataset consists of a training set and a test set. All normal and anomaly images are in hdf5 format. In the mask annotations, pixels with a value of 0 represent normal regions, and pixels with a value of 1 represent anomaly regions. The file structure of the training set and the test set are consistent, as follows: dataset/ ├── train/ │ ├── category1.h5 │ ├── category2.h5 │… See the full description on the dataset page: https://huggingface.co/datasets/Tocmac/ReinAD.
| Author / organization | Tocmac |
|---|---|
| License (as declared) | cc-by-nc-sa-4.0 |
| Downloads | 1.9K (as reported by Hugging Face) |
| Likes | 0 |
| Created | 22 October 2025 |
| Last updated at source | 24 October 2025 |
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- 16 Oct 2026 Description: ReinAD: Towards Real-world Industrial Anomaly Detection with a Comprehensive Contrastive Dataset Our dataset consists of a training set and a test set. All normal and anomaly images are in hdf5 format. In the mask annotations, pixels with a → ReinAD: Towards Real-world Industrial Anomaly Detection with a Comprehensive Contrastive Dataset Our dataset consists of a training set and a test set. All normal and anomaly images are in hdf5 format. In the mask annotations, pixels with a
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