patchcore

Pipeline training and inference Anomalib models UI in Anomaly Detection

PatchCore method for Industrial Anomaly Detection + CLIP

Production-ready visual anomaly detection from normal images, featuring PaDiM, ultra-light PatchCore, automated edge deployment, and optimized ONNX, OpenVINO, TensorRT INT8, Hailo, and KV260 support.

An unofficial implementation using Pytorch for "Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types". Improve the algorithm with DINO pretrained ViT. Implement algorithms based on PatchCore.

Comprehensive benchmark for anomaly detection models on MVTec AD dataset using Anomalib. Includes PatchCore, EfficientAD, FastFlow, STFPM, PaDiM with Gradio demo.

Training-free deep learning for unsupervised industrial defect detection & localization on MVTec AD, PatchCore & PaDiM, with image and pixel level AUROC and a one-click free-Colab demo.

Anomaly detection for visual defect inspection: trained on normal images only, with localisation. PyTorch + MVTec AD.

PatchCore + YOLO screw anomaly detection demo with Gradio UI (MVTec AD)

Multi-view anomaly scoring models from scarce, unbalanced, multi-class data

End-to-end automated visual inspection: PatchCore anomaly detection + FastAPI + Next.js dashboard + ABB GoFa cobot (RobotStudio)

AI-powered industrial surface defect detection using PatchCore-inspired anomaly detection, ResNet50 feature extraction, heatmap visualization, Google Gemini AI, PDF inspection reports, and Streamlit.

📸🔥Thermal Camera Diagnosis App Prototype was my bachelor thesis project at THU, focused on enhancing battery recycling processes using thermal imaging anomaly detection.

Edge anomaly detection for video streams with multi-backend inference benchmarking (TensorRT, ONNX, PyTorch)

Industrial visual anomaly detection using PatchCore with FastAPI, Streamlit and Docker deployment.

Defect intelligence for rotating equipment. A photograph of a returned gearbox part becomes an ISO 15243 / ISO 10825 failure record linked to the batch that made it. The model suggests, the inspector decides.

Unsupervised maize disease detection with cross-domain evaluation on real-field PlantDoc imagery and a controlled background-sensitivity experiment. PatchCore generalizes from lab to field (AUROC 0.9995); reconstruction-based methods are 4× inflated by domain shift.

兼容 Anomalib 生态的通用异常检测推理库：一张图进去，缺陷 mask + 分数 + OK/NG 出来，一个 DLL + 一个头文件，零 OpenCV 依赖。

Unsupervised anomaly detection pipeline for real-time welding quality control with IATF 16949 audit trail compliance.

Real-time manufacturing defect detection using unsupervised PatchCore — FastAPI + Streamlit + OpenVINO

Modular 2D industrial inspection platform with a swappable method interface — two anomaly-detection methods (autoencoder + PatchCore) built from scratch, served via FastAPI + React, Dockerized. Benchmarked on MVTec AD (mean image AUROC 0.72 → 0.96).