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)
This reposity contains some serverless functionality for auto annotations
Tools for working with data for annotating animal behavior. These were specifically designed during construction of the KABR dataset.
A parser for tracklet labels in KITTI Raw Format 1.0 created by the Computer Vision Annotation Tool (CVAT).
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.
Documentation for deployment of cvat on Google Cloud (under development)
Yolo autolabel. It can export the dataset to CVAT format for editing or exporting to another format
Código para entrenamiento de modelo para detección de objetos con algoritmo Yolov8 de Ultralytics
AnnotationParser is a universal Python library that parses annotation files from different formats (LabelMe, COCO, VOC, etc.) into a single unified Shape data structure. This allows you to work with annotations using a consistent interface, regardless of the original format.
Connects Nuclio / CVAT to Lighting flash ML models
A Python program that can convert Segmentation mask 1.1 to Yolov8 format.
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