Samples code for world class Artificial Intelligence SoCs for computer vision applications.
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Updated
May 29, 2024 - CMake
Samples code for world class Artificial Intelligence SoCs for computer vision applications.
🚀🚀🚀 YOLO series of PaddlePaddle implementation, PP-YOLOE+, RT-DETR, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOX, YOLOv5u, YOLOv7u, YOLOv6Lite, RTMDet and so on. 🚀🚀🚀
Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.
🚀 ⭐ The list of the most popular YOLO algorithms - awesome YOLO
YoloV6 NPU for the RK3566/68/88
Detection models and Python scripts for automated insect monitoring with the Insect Detect DIY camera trap.
Real-time multi-camera multi-object tracker using (YOLOv5, YOLOv7,YOLOv8) and StrongSORT with OSNet
NVIDIA DeepStream SDK 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models
PaddleSlim is an open-source library for deep model compression and architecture search.
OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.
MetaSeg: Packaged version of the Segment Anything repository
GUI for marking bounded boxes of objects in images for training neural network YOLO
💎A high level pipeline for face landmarks detection, it supports training, evaluating, exporting, inference(Python/C++) and 100+ data augmentations, can easily install via pip.
🛠 A lite C++ toolkit of awesome AI models, support ONNXRuntime, MNN. Contains YOLOv5, YOLOv6, YOLOX, YOLOR, FaceDet, HeadSeg, HeadPose, Matting etc. Engine: ONNXRuntime, MNN.
🔄 A tool for object detection and image segmentation dataset format conversion.
The project can achieve FCWS, LDWS, and LKAS functions solely using only visual sensors. using YOLOv5 / YOLOv5-lite / YOLOv6 / YOLOv7 / YOLOv8 / YOLOv9 / EfficientDet and Ultra-Fast-Lane-Detection-v2 .
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