Stars
Unofficial implemention of lanenet model for real time lane detection
Udacity Self-Driving Car Engineer Nanodegree projects.
An open source lane detection toolbox based on PyTorch, including SCNN, RESA, UFLD, LaneATT, CondLane, etc.
[CVPR 2025 Best Paper Nomination] FoundationStereo: Zero-Shot Stereo Matching
SPI LCD graphics library for ESP32 (ESP-IDF/ArduinoESP32) / ESP8266 (ArduinoESP8266) / SAMD51(Seeed ArduinoSAMD51)
Implementation of "YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception".
基于YOLOv12的智能害虫检测系统，集成FastAPI后端和React前端，提供图像和视频中农作物害虫的实时识别、分析与管理功能。
Autonomous Driving System is an integrated system combining the powerful YOLOPv2 vision model with a practical processing pipeline developed by a student of FPT University Quy Nhon. This project ai…
Compare 2 model of lane detection which is Polylannet, YOLOPv2
The improved model for multi-object detection and lane line segmentation based on the YoloP model.
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Tools used to create the RDK OS images for RDK X5
Arduino and PlatformIO IDE compatible TFT library optimised for the Raspberry Pi Pico (RP2040), STM32, ESP8266 and ESP32 that supports different driver chips
A Python-based Xiaozhi AI for users who want the full Xiaozhi experience without owning specialized hardware.
本项目为xiaozhi-esp32提供后端服务，帮助您快速搭建ESP32设备控制服务器。Backend service for xiaozhi-esp32, helps you quickly build an ESP32 device control server.
A cross-platform framework that deploys and applies ModelAssistant models to microcontrol devices
Screw type detection using ESP-EYE, YOLOv5, and TensorFlow Lite Micro for real-time classification on ESP32.
An open source quadruped robot pet framework for developing Boston Dynamics-style four-legged robots that are perfect for STEM, coding & robotics education, IoT robotics applications, AI-enhanced r…
🚀🚀🚀This is an AI high-performance reasoning C++ library, Currently supports the deployment of yolov5, yolov7, yolov7-pose, yolov8, yolov8-seg, yolov8-pose, yolov8-obb, yolox, RTDETR, DETR, depth-an…
分别使用OpenCV、ONNXRuntime部署YOLOPV2目标检测+可驾驶区域分割+车道线分割，一共包含54个onnx模型，依然是包含C++和Python两个版本的程序。仅仅只依赖OpenCV就能运行，彻底摆脱对任何深度学习框架的依赖。