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

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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

thangkt/visionqc-efficientad-medium-pcb1

VisionQC EfficientAD-medium for VisA/pcb1

Results

Training configuration

Files

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Links

thangkt/
visionqc-efficientad-medium-pcb1