You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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.
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.
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.
Support Yolov5(4.0)/Yolov5(5.0)/YoloR/YoloX/Yolov4/Yolov3/CenterNet/CenterFace/RetinaFace/Classify/Unet. use darknet/libtorch/pytorch/mxnet to onnx to tensorrt