OpenMMLab Detection Toolbox and Benchmark

OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.

NVIDIA DeepStream SDK 7.1 / 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models

🚀🚀🚀 YOLO series of PaddlePaddle implementation, PP-YOLOE+, RT-DETR, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv10, YOLOX, YOLOv5u, YOLOv7u, YOLOv6Lite, RTMDet and so on. 🚀🚀🚀

Officiel implementation of the paper "FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite Imagery"

juxtapose: Multi-Person Pose Tracking Inference SDK with RTMDet, YOLOv8, GDino, RTMPose (ONNX) & Trackers (ByteTrack & BotSORT) & Tapnet with custom ROIs + FastAPI GPU exe

Paddle detection to pytorch

支持RTMDet、YOLOv8、YOLOX、Faster R-CNN等常见算法的ncnn部署

OpenMMLab YOLO series toolbox and benchmark

RTMDET在snpe部署

This research delves into the applications CNNs in crowd detection, a domain critical for optimizing operations, ensuring safety, and making informed decisions in diverse industries.

Detect various marine species in an aquarium environment using MMDetection. This project builds and evaluates object detection models to accurately classify marine life forms like fish, jellyfish, and more. Leveraging the Aquarium Dataset from Roboflow, the project aims to enhance species identification with robust detection models.🐋