Converting COCO annotation (CVAT) to annotation for YOLO-seg (instance segmentation) and YOLO-obb (oriented bounding box detection)

A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.

Use this project to automatically annotate your dataset for free in CVAT

Репозиторий для обучения нейросетевых моделей по семантической сегментации + пример использования моделей на практике

This project aims to develope a Road-Segmentation model for Advanced Driver Assistance System (ADAS)

Python wrapper for cvat

This reposity contains some serverless functionality for auto annotations

A parser for tracklet labels in KITTI Raw Format 1.0 created by the Computer Vision Annotation Tool (CVAT).

Создание автоматической аннотации с использованием предобученной модели YOLOv5

Documentation for deployment of cvat on Google Cloud (under development)

Connects Nuclio / CVAT to Lighting flash ML models

Código para entrenamiento de modelo para detección de objetos con algoritmo Yolov8 de Ultralytics

Yolo autolabel. It can export the dataset to CVAT format for editing or exporting to another format

Integrating Delphi and CVAT: Bandwidth-Efficient Interactive Labeling

The "Car Brand Detection" project aims to develop an efficient system for identifying car brands from images using computer vision techniques. Utilizing a labeled dataset created with CVAT and training with the YOLO v8 model, the project seeks to achieve high accuracy in recognizing various car brands in real-world scenarios.

Use this if you have a set of annotations and images and want to import them into CVAT (could be for editing the bounding boxes or to export the dataset to another format).

CVAT SDK for JavaScript in the browser and Node.js