| --- |
| library_name: anomalib |
| tags: |
| - anomaly-detection |
| - computer-vision |
| - pcb |
| - efficientad |
| - anomalib |
| datasets: |
| - VisA |
| --- |
| |
| # VisionQC EfficientAD-medium for VisA/pcb1 |
|
|
| [](https://github.com/pnthang04/VisionQC) |
|
|
| EfficientAD-medium anomaly detection checkpoint trained with Anomalib 2.6.0 |
| on the `pcb1` category of VisA. |
|
|
| ## Results |
|
|
| The reported test split is independent from the validation split used for |
| early stopping and checkpoint selection. |
|
|
| | Metric | Value | |
| |---|---:| |
| | Validation image AUROC | 0.8936 | |
| | Test image AUROC | 0.9364 | |
| | Test image F1 | 0.8785 | |
| | Test pixel AUROC | 0.9883 | |
| | Test pixel F1 | 0.6095 | |
| | Test pixel AUPRO | 0.8686 | |
|
|
| ## Training configuration |
|
|
| - Model: EfficientAD-medium |
| - Dataset: VisA/pcb1 |
| - Training images: 904 normal |
| - Validation: 100 images |
| - Test: 50 normal and 50 anomalous images |
| - Batch size: 32 per GPU |
| - Devices: 2 Tesla T4 GPUs |
| - Effective batch size: 64 |
| - Precision: FP16 mixed precision |
| - Early stopping: validation image AUROC, patience 20, minimum delta 0.001 |
| - Best epoch: 30 |
| - Best global step: 465 |
|
|
| This uses a local `BatchedEfficientAd` wrapper to permit batched DDP training |
| without modifying Anomalib core. The architecture itself remains |
| EfficientAD-medium. Results are not directly comparable to the official |
| batch-size-1 EfficientAD baseline. |
|
|
| ## Files |
|
|
| - `model-best.ckpt`: best Lightning checkpoint selected by validation image AUROC |
| - `config.yaml`: complete VisionQC training configuration |
| - `metrics.json`: test metrics generated after restoring the best checkpoint |
|
|
| ## Loading |
|
|
| Download the checkpoint: |
|
|
| ```bash |
| hf download thangkt/visionqc-efficientad-medium-pcb1 model-best.ckpt \ |
| --local-dir weights/efficientad-medium-pcb1 |
| ``` |
|
|
| Use it with the VisionQC project and Anomalib 2.6.0: |
|
|
| ```bash |
| visionqc evaluate \ |
| --checkpoint weights/efficientad-medium-pcb1/model-best.ckpt |
| ``` |
|
|
| ## Links |
|
|
| - Source: https://github.com/pnthang04/VisionQC |
| - Multi-GPU training PR: https://github.com/pnthang04/VisionQC/pull/1 |
| - Model repository: https://huggingface.co/thangkt/visionqc-efficientad-medium-pcb1 |
|
|
