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Images and video restoration in multiple-stages using MIRNETv2 model, additionally object detection on images and video through FASTER-RCNN . And complete web application in flask including responsive front-end
Welcome to the project on downloading the COCO dataset from a JSON file! This application was developed with one goal in mind: to provide an educational and entertaining solution for obtaining data from the famous COCO (Common Objects in Context) dataset.
Demonstrates real-time object detection using the YOLOv8 pre-trained model. The script utilizes the YOLOv8 model to identify objects in a live video stream captured from the user's webcam.
This application eliminates a set of given elements from a serial video resource. You can directly set some classes and qualifications for filtering options also, there also exixst an sql output for schemes.
Unsafe overtaking of large trucks is a major cause of traffic accidents and road congestion. Current solutions, such as Samsung's attempt to install screens on trucks, have been unsuccessful. There is a need for a reliable and accurate system to assist drivers in overtaking trucks safely.