Reproducing the PatchCore anomaly detection algorithm from the paper "Towards Total Recall in Industrial Anomaly Detection". Features: WideResNet backbone, patch extraction, memory bank construction, coreset subsampling (Farthest Point Sampling), nearest-neighbor anomaly scoring, and ROC-AUC evaluation on MVTec AD.
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Reproducing the PatchCore anomaly detection algorithm from the paper "PatchCore: Anomaly Detection Without Training" using PyTorch. Features: WideResNet backbone, patch extraction, memory bank construction, coreset subsampling (Farthest Point Sampling), nearest-neighbor anomaly scoring, and ROC-AUC evaluation on MVTec AD.
shiva2307/patchcore-anomaly-detection
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Reproducing the PatchCore anomaly detection algorithm from the paper "PatchCore: Anomaly Detection Without Training" using PyTorch. Features: WideResNet backbone, patch extraction, memory bank construction, coreset subsampling (Farthest Point Sampling), nearest-neighbor anomaly scoring, and ROC-AUC evaluation on MVTec AD.
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