A 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 RF-DETR, YOLO11, SAM 3, and Qwen3-VL.
Turn any computer or edge device into a command center for your computer vision projects.
Images to inference with no labeling (use foundation models to train supervised models).
🔥🔥🔥TensorRT for YOLO26 (det/pose/seg/depth/obb/cls), YOLOv11,YOLOv10 YOLOv9,YOLOv8, ... 🚀🚀🚀 CUDA IS ALL YOU NEED. 🍎🍎🍎
MetaSeg: Packaged version of the Segment Anything repository
Python Computer Vision & Video Analytics Framework With Batteries Included
Real-Time Powerlifting Form Check 2026: AI Pose Correction with YOLOv5 and MediaPipe
Real-time YOLOv5s + UNet on RK3588 with OpenCL GPU-accelerated lens undistortion. Dual-camera AI perception system for autonomous driving assistance.
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
《Pytorch实用教程》(第二版)无论是零基础入门,还是CV、NLP、LLM项目应用,或是进阶工程化部署落地,在这里都有。相信在本书的帮助下,读者将能够轻松掌握 PyTorch 的使用,成为一名优秀的深度学习工程师。