A Python tool for managing YOLO datasets, including YOLOv5, YOLOv8, YOLOv11 and other Ultralytics-supported models. It streamlines tasks like dataset combination, data augmentation, class removal, and annotation visualization supports bounding box and segmentation formats, making it an essential tool for developers and researchers.

Mask Detection Dataset for yolo annotated by using https://github.com/tzutalin/labelImg

datasets generation for deep learning

This project demonstrates object detection using YOLOv5. The model is trained on a custom dataset and can detect objects in new images. YOLOv5 is a state-of-the-art object detection model known for its speed and accuracy, making it suitable for real-time applications.

This repository contains different random scripts for machine learning dataset preparations.

applies mosaic augmentation on YOLO format dataset

Object Detection Dataset Format Converter

Simple dataset creator in COCO-format.

Object Detection Tools to convert between dataset formats, image splitting and stitching.

Successfully developed an object detection model using YOLOv8 to accurately identify and localize tomatoes in images, supporting agricultural automation and yield monitoring tasks.

Successfully developed an object detection model using YOLOv8 to accurately detect and localize car number plates in real-time, suitable for smart surveillance and automated traffic monitoring systems.

I created a Python script to convert the YOLO format dataset labeled dataset into KITTI format using ChatGPT o1-mini.