patchcore

基于 PatchCore 的工业异常检测项目，研究 layer2/layer3 分数融合、敏感性引导收缩与风险受控门控，并提供 Streamlit 工程化 Demo。

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.

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

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.

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

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

One-class industrial defect detection and localization (PatchCore + tiled DINOv3) under a pre-registered protocol. MVTec AD 2 server: AU-PRO 62.97, SegF1 53.76.

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。

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

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

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).

Detección de defectos en tela con PatchCore + ONNX Runtime, API FastAPI, MLflow, drift y decisión de calidad ASTM D5430 / ISO 2859-1

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

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

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

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

Industrial anomaly detection and localization with a convolutional autoencoder and compact PatchCore on MVTec AD. Includes measured benchmarks, fitted models and a local inspection app.