Projects based on self learning purpose.

A facemask detection tool utilizing YOLOv7 with a custom dataset.

Vision Based Inteligent Recipe Recommendation system

Using YOLOv7,Sort.py,OpenCV,EasyOCR, Jetson Orin Nano

The project aims to develop a robust Pothole Detection System that can analyze video data from car dash cams in real-time, identify potholes accurately, and generate comprehensive reports containing images and geospatial coordinates of the detected potholes. This system will enhance road safety and also contribute to proactive road maintenance.

PyTorch implementation of YOLOv7.

This project aims to enhance industrial safety by accurately identifying safety objects within a workplace environment

This repository contains a project for detecting flags in images using the YOLOv7 object detection model. Designed for applications in events, sports, and public gatherings, this project enables accurate flag localization through advanced deep learning.

According to the official release of YOLOv7, support for YOLO-POSE inference script `detect_pose.py` has been added.

Fabric defect detection using yolov7.

This project utilizes the YOLOv7 architecture to develop a drowsiness detection system. The model is designed to identify signs of driver drowsiness, such as closed eyes, yawning, and head movements, using a custom dataset. However, the results indicate that YOLOv7 may not be the best choice for real-time drowsiness detection.

This project uses YOLO models for efficient object detection with a Streamlit interface. Users can upload images or video streams for real-time detection. It supports YOLOv8, YOLOv9, and YOLOv10; offering flexibility and high accuracy in various scenarios.

benchmark of object detection algorithms for license plate detection

yolov7을 활용한 kaggle mask image fine tuning

INSTALLATION AND DEPLOYMENT GUIDELINE YOLOV7's PRE-PRETRAINED MODEL ON JETSON PLATFORM

The application is developed based on the Yolo v7 machine learning model utilizing Google Colab as a tool for distinguishing between fresh fruits and spoiled fruits.

Compare the performance of AWS Serverless and Serverful compute by deploying YOLO V7 model

YOLOv7 implementation on Indian Roads

In this repository, I will be creating a tool that can be used when you want to prepare your data to be used in YOLO Object Detection.