Simplest and fastest image and text annotation tool.

Georeferenced Bounding Box.

Octree/Quadtree/N-dimensional linear tree

Semi-automatic YOLO dataset preparation. Use a pre-trained object detection model to annotate your dataset, then review each image and 'accept' or 'refuse'. Can also edit/mark bounding boxes by hand. Store project data in a single .csv file.

Highly customizable Vue3/React component for resizing nested content

Image Annotation Tool - A modern desktop application for creating bounding box annotations on images. Export to COCO, YOLO, and Pascal VOC formats with a single click. Built with Python and Tkinter.

Python library for Object Detection metrics.

Developed an object and face detection system using YOLOv8 and OpenCV. The model detects multiple object classes in images, counts the number of persons detected, and applies Haar Cascade to locate faces within the person regions. The solution runs in Google Colab and visualizes results with annotated bounding boxes.

Calculate path lengths, points or angles at lengths based on raw pathdata

Implementation for 3D bounding box prediction of objects using images, point clouds, and segmentation masks.

An object detection model based on YOLOv8 to detect and localize mangoes in images and videos. This project covers image annotation, transfer learning with pretrained weights, and evaluation using a public dataset from Hugging Face, manually annotated for mango detection.

This mini project focuses on detecting doors and windows in architecture blueprints using a custom-labeled dataset with the YOLOv8 model family. The workflow includes manual annotation, preprocessing, data augmentation, training with different YOLO models, and evaluating performance metrics.

This is useful to debug the Argoverse V1.1 dataset.

Make drawing and labeling bounding boxes a piece of cake

Geometry intersection and bounding volume helpers for PEX.

This is a project about the work of a transfer learning (from binary image classification) to multi category image classification and regression, as well as some data processing, regularization, and data augmentation as well as Object Detection using Bounding Boxes (bbox)

This project performs real-time object detection using your laptop camera or external webcam with OpenCV and the MobileNetSSD model. It captures live video frames, detects common objects (like person, chair, dog, etc.), and draws bounding boxes around them in real-time. The goal is to help beginners understand object detection using OpenCV’s.

Intelligent Surveillance and Identification for Secure Campus

A real time face detection that captures video from your webcam. Highlights detected faces with bounding boxes in the live feed.

Detection is performed by combining two approaches: Yolo bounding box and pose landmarks, where both outputs are mapped into a 10x10 grid (made with OpenCV), which serves as a reference for the wheelchair to avoid obstacles. Commands are sent from the NUC to the ESP32, which then moves the motor.