Object Detection Application
A Flask-based web application that utilizes YOLOv5 for real-time object detection using uploaded images. The application highlights detected objects and provides labels for them.
Project Overview
This object detection project allows users to upload images, and the application uses the YOLOv5 model to identify and label objects within the image. The results are then displayed on the web interface with bounding boxes drawn around the detected objects. This project is a demonstration of integrating computer vision models with a simple web application using Flask.
The object detection is powered by YOLOv5, a state-of-the-art object detection model, which processes the uploaded image and returns bounding boxes and labels for the objects detected. This project demonstrates the ability to apply computer vision techniques in real-world scenarios.
Screenshots
Object Detection Interfacet
Video Detection Interface
Skills & Technologies Used
- YOLOv5 (You Only Look Once)
- Flask (Backend)
- Python (General Programming)
- Computer Vision
- OpenCV
- HTML/CSS for Frontend
- PyTorch for Model Inference