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
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Updated
Jun 28, 2024 - C++
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
A cloud-based software application that monitors compliance with multiple personal protective equipment for construction safety and delivers reports to safety officers' mobile applications via a lightweight messaging protocol called MQTT.
🚀 ⭐ The list of the most popular YOLO algorithms - awesome YOLO
🔥 Unleash the Power of Computer Vision!
Easy & Modular Computer Vision Detectors, Trackers & SAM - Run YOLOv9,v8,v7,v6,v5,R,X in under 10 lines of code.
🛠 A lite C++ toolkit of awesome AI models, support ONNXRuntime, MNN. Contains YOLOv5, YOLOv6, YOLOX, YOLOR, FaceDet, HeadSeg, HeadPose, Matting etc. Engine: ONNXRuntime, MNN.
🔥🔥🔥 专注于YOLOv5,YOLOv7、YOLOv8、YOLOv9改进模型,Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀
🔥🔥🔥TensorRT for YOLOv8、YOLOv8-Pose、YOLOv8-Seg、YOLOv8-Cls、YOLOv7、YOLOv6、YOLOv5、YOLONAS......🚀🚀🚀CUDA IS ALL YOU NEED.🍎🍎🍎
implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
🤖 Trained YOLOR model to detect texts on manga pages
Detection fresh and old fracture on spine CT image using YOLOR
Created by Mehmet Zahid Genç
test models to proove state of art of object detection and classification in 3 differents dataset
Helpful programs for dataset preparation in YOLO and YOLOR detection algorithms.
FSOD stands for Firearms and Sharp Object Detector. Conclusively, this dashboard is a web application made with streamlit that can detect several kind of firearms and sharp object threat that I build for my bachelor's thesis project. Object detection algorithm used to make the model are YOLO-R and also used Deepsort for tracking purpose.
Implementation of the state of the art YOLOR algorithm for object detection and linked it with flask for a web app where the images and videos can be given as input and the detected output can be viewed in a separate images and videos. The aim of this project is to detect real time objects in both images and videos with the maximum accuracy.
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