ROAD-DAMAGE-DETECTION-ML-MODEL-USING-ULTRALYTICS USING YOLOV8X AND AND PRIDICTING WITH MAXIMUM ACCURACY

Demo project for Sahi Pro driver written on Java

Archipelago 2025 hack repo: automatic recognition of objects (people) in images obtained from UAVs

This project integrates SAHI with YOLOv8 for efficient object detection, supporting image, video, and real-time webcam feeds. By using SAHI's slicing technique, it improves detection in complex or high-resolution scenarios. Ideal for versatile object detection needs with state-of-the-art performance.

Python Driver for Sahi Web Automation tool based on Sahi ruby driver

Demo project for Sahi Pro driver written on Java

Mini project in the module TDT17 for object detection 😎

This Repo contains code for used for age and gender detection in CCTV videos

Tile your highres images to squares in FiftyOne directly to train for small object detection purpose (e.g. with SAHI)

This repository contains a Python-based program that detects and tracks people in a video, counting the number of individuals entering and exiting a defined area. It uses the YOLOv8 model for object detection and the SORT (Simple Online and Realtime Tracking) algorithm for tracking.

This is a plugin for SwiftOps Bot Engine.

Finetuning pretrained YOLOv11n for Small Object Detection

This project contains service to parse Sahi run result and display it in JSON. This service is a part of SwiftOps project

This project automates detection and counting of shelters in a refugee camp to estimate population. A drone's high-def image is analyzed with YOLOv8 for detecting shelters and other categories. The SAHI library handles large images. The model is trained on data from various camps in DRC. Future work will explore segmentation with models like SAM

SAHI Kütüphanesi için Detaylı Türkçe Dokümantasyonu

Code for Automated Detection of Antarctic Benthic Organisms in High-Resolution In Situ Imagery to Aid Biodiversity Monitoring (Trotter et. al, 2025)

🛰️ SAHI-powered satellite reconnaissance system for detecting military vehicles in high-resolution imagery. Uses YOLOv8 with sliding window inference to detect small objects (tanks, trucks, AFVs) that standard detection misses due to aggressive image downscaling. Processes 4000x4000 images via 512x512 overlapping tiles.

YOLOv9 (Ultralytics) Python interface for training, validating and running detection on waste detection dataset + detection using SAHI.