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Official PyTorch implementation of the paper “Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection”, open-set anomaly detection, few-shot anomaly detection.
[IEEE TII 2023] Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization
Project for <SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation> (ECCV 2022)
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, and TIMM models.
Implementation of our paper "Optimizing PatchCore for Few/many-shot Anomaly Detection"
Official implementation of CVPR'24 paper 'Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection'.
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
An Attribute-based Method for Video Anomaly Detection (TMLR 2025)
A simple and easy-to-use cross-platform C++ wrapper for the SQLite API. Fork of the CppSQLite project, originally by Rob Groves, currently updated and maintained by NeoSmart Technologies.
Fast multi-dimensional generalized histogram with convenient interface for C++14
Segment Anything Model 2 CPP Wrapper for macOS and Ubuntu CPU/GPU
📐A collection of line segments detection algorithms.
line segment detector(lsd) &. edge drawing line detector(edl) &. hough line detector(standard &. probabilistic) for detection
基于CPP+OPENCV4.0实现的LineSegmentDetector定位算法
[AAAI 2024 Oral] AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models
This software allows to run MobileSAM, without python.
This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!
"FastSAM_Awsome_Openvino" 项目展示了如何通过 OpenVINO 框架高效部署 FastSAM 模型，实现了令人瞩目的实例分割功能。该项目提供了 C++ 版本和 Python 版本两种实现，为开发者提供了在不同语言环境下使用 FastSAM 模型的选择。
Run Segment Anything Model 2 on a live video stream
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Image Segmentation using Texture and Color features in C++
A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
