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This repository offers a comprehensive collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like YOLO11, RT-DETR, SAM 2, Florence-2, PaliGemma 2, and Qwen2.5VL.
Implementation of popular deep learning networks with TensorRT network definition API
🛠 A lite C++ AI toolkit: 100+🎉 models (Stable-Diffusion, Face-Fusion, YOLO series, Det, Seg, Matting) with MNN, ORT and TRT.
OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.
⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.
🔥🔥🔥 专注于YOLO11,YOLOv8、TYOLOv12、YOLOv10、RT-DETR、YOLOv7、YOLOv5改进模型,Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀
Effortless AI-assisted data labeling with AI support from YOLO, Segment Anything (SAM+SAM2), MobileSAM!!
Images to inference with no labeling (use foundation models to train supervised models).
Lightweight inference library for ONNX files, written in C++. It can run Stable Diffusion XL 1.0 on a RPI Zero 2 (or in 298MB of RAM) but also Mistral 7B on desktops and servers. ARM, x86, WASM, RISC-V supported. Accelerated by XNNPACK.
Turn any computer or edge device into a command center for your computer vision projects.
🔥🔥🔥TensorRT for YOLOv8、YOLOv8-Pose、YOLOv8-Seg、YOLOv8-Cls、YOLOv7、YOLOv6、YOLOv5、YOLONAS......🚀🚀🚀CUDA IS ALL YOU NEED.🍎🍎🍎
🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️
MetaSeg: Packaged version of the Segment Anything repository
YOLOv8 Object Tracking using PyTorch, OpenCV and DeepSORT