yolov8s

YoloV8 for a bare Raspberry Pi 4 or 5

A lightweight C++ implementation of YoloV8 running on NVIDIAs TensorRT engine

This project implements a Wrinkle Detection application using YOLOv8 for segmentations. The application is built with Streamlit and allows users to upload images for wrinkle detection of human faces. Segmentation using YOLOv8s (small) finetuned model.

In computer vision, this project meticulously constructs a dataset for precise 'Shoe' tracking using YOLOv8 models. Emphasizing detailed data organization, advanced training, and nuanced evaluation, it provides comprehensive insights. A final project for the Computer Vision cousre on Ottawa Master's in (2023).

This repository provides a fully containerized microservice for object detection using YOLOv8 and FastAPI. With Docker and Docker Compose, developers can easily set up, run, and integrate advanced object recognition capabilities into their applications.

A computer vision desktop application for automated insect phenotyping using YOLOv8, FastAPI, React and Tauri to detect and count insect embryos in high‑resolution microscopy images.

Advanced real-time object detection with YOLOv8s, counter, dynamic colors, and HD fullscreen display Topics: python yolo computer-vision object-detection opencv deep-learning real-time yolov8s object-counting

Real-time underwater trash detection using YOLOv8s trained on the TrashCan dataset

detect football player, ball, goalkeeper, refree with custom trained yolo wieghts

Traffic Sign Recognition (TSR) vison model for Advanced Driver Assitance System (ADAS) using YOLO-based object detection, trained on a custom Indian traffic sign dataset aligned with Indian Road Congress (IRC:67-2022) standards.

Real-time traffic object detection using YOLOv8s and the BDD100K dataset for intelligent transportation and smart traffic monitoring applications.

A wearable AI-powered sling bag that assists visually impaired users through real-time obstacle detection, text reading, and voice-based guidance using YOLOv8s and Phi-2 LLM.

First google colab Trained model for pen and highlighter detection

Low-light pedestrian detection via visible-infrared pixel fusion + YOLOv8s fine-tuning on the LLVIP benchmark dataset

An advanced YOLOv8 object detection pipeline trained on mixed BDD100k & RDD datasets. Features custom stratification, live spatial mapping, and a three-tier risk assessment classifier optimized

Face Recognition of individuals using YOLOv8 + ArcFace

End-to-end real-time rescue detection system using Android, Insta360 X4, YOLO, WebSocket, and a cloud Command Center.

Real-time object detection, tracking, and per-class counting from a laptop camera (YOLOv8 + supervision/ByteTrack)

Low-light image enhancement and pedestrian detection based on the LLVIP dataset.