How to Train YOLOv8 Instance Segmentation on a Custom Dataset

Traffic Sign Detection and Warning System in real time with Custom Dataset & YOLOV8.

This repository demonstrates how to fine-tune YOLOv11n on multiple fire detection datasets. It provides a complete pipeline for combining multiple datasets from Roboflow, training a unified model, and evaluating its performance.

This project implements a YOLOv8 model to detect and classify various skin diseases from images. The model is trained on a dataset of labeled images and can identify different types of skin conditions in real-time.

Machine Learning model

Detect football players in videos using YOLOv5 for training and YOLOv8 for inference. The dataset is sourced from Roboflow and includes 663 annotated images. The project involves pre-processing, augmentation, and model training for accurate player detection.

The road sign recognition system of the Russian Federation, which uses an already prepared model for object detection and image segmentation in real time to improve road safety

Fire detection using YOLOv8 involves utilizing a state-of-the-art object detection model to accurately identify fire in images or video feeds in real-time, leveraging its advanced capabilities to enhance early warning systems.

Custom Yolov8x-cls edge model deployment and training to classify trash vs recycling.

Use machine learning to identify players, refs and football field markings.

From dataset https://universe.roboflow.com/drone-detection-pexej/drone-detection-data-set-yolov7/dataset/1 a model is obtained, based on yolov10 to detect drones in images. Predictions from several models are used in cascade to obtain the optimal result.

From a selection of data from the Roboflow file https://universe.roboflow.com/landy-aw2jb/fracture-ov5p1/dataset/1, which represents a reduced but homogeneous version of that file, a model is obtained based on yolov10 with that custom dataset to indicate fractures in x-rays.

A football analysis system built using YOLOv5, Supervision, OpenCV in Python.

Utilize YoloV8 for object detection of copper ore in Albion Online game with farming capabilities.

This project focuses on leveraging the YOLO-NAS model for Smoke Detection.

From dataset https://universe.roboflow.com/test-svk7h/brain-tumors-detection/dataset/2 a model is obtained, based on yolov10 to indicate tumors in images of brains.

From dataset https://universe.roboflow.com/drone-detection-pexej/drone-detection-data-set-yolov7/dataset/1# a model is obtained, based on ML (SVR), with that custom dataset, to indicate drones detection

This project demonstrates how to track a ball in a video showcasing a Tennis game by training a custom YOLO detection model. The model is trained not only for ball detection but also interpolation to handle areas where the tracking fails.

This research work introduced various aspects from dataset preparation techniques to image pre-processing, model comparison, and performance analysis on the detection & instance segmentation of three microalgae class namely Chlorella vulgaris FSP-E, Chlamydomonas reinhardtii, and Spirulina platensis.

StreetSpecter is an innovative AI-driven solution designed to detect potholes and facilitate road maintenance.