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
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
This is the code used for my project NavAssist, a smart navigational assistive device to help the visually-impaired navigate unfamiliar spaces. It uses Tensorflow lite and the COCO dataset. You will need to download labels from the COCO website. You can recreate the prototype by following the visuals at the link below. I'm running out so goodluck!
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.