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Anno-Mage: A Semi Automatic Image Annotation Tool which helps you in annotating images by suggesting you annotations for 80 object classes using a pre-trained model

Make drawing and labeling bounding boxes easy as cake

🚤 Label data at scale. Fun and precision included.

LabelImgTool is a graphical image annotation tool which supports CLS,DET and SEG(semantic&instance )

One-click image sorting/labelling script

Zero Shot Image Classification but more, Supports Multilingual labelling and a variety of CNN based models for a vision backbone by using OpenAI CLIP for $ conscious uses (Super simple, so a 10th-grader could totally write this but since no 10th-grader did, I did) - Prithivi Da

Interactive Semi Automatic Image 2D Bounding Box Annotation and Labelling Tool using Multi Template Matching An Interactive Semi Automatic Image 2D Bounding Box Annotation/Labelling Tool to aid the Annotater/User to rapidly create 2D Bounding Box Single Object Detection masks for large number of training images in a semi automatic manner in orde…

Web-based app for labeling DICOM files in Python.

Matplotlib Image labeller for classifying images

An automatic Image Segmentation and labelling tool which can make labelling of images for segmentation feel effortless

boxcel: Integrate Excel with Python for visualizing images with their corresponding bounding boxes for object detection annotation workflows

Serverless image labelling using Lambdas, Rekognition, s3, DynamoDB.

Multi-Auto-Annotate : Automatically annotate multiple labels in your entire image directory by a single command. Works with COCO dataset and also has the ability to train on custom dataset.

This is a python based standalone image annotation tool designed for tasks such as image segmentation and object detection. The tool allows users to draw bounding boxes, polygons, and freehand paths, edit and manage annotations, and export the annotated data in multiple formats including COCO, YOLO, and PASCAL VOC.

A deep residual network implementation using TF high-level APIs.

Scripts used to create 3D annotations from 2D annotations of cells from fluorescence microscopy images.

Python script generates colored masks from COCO-style annotations. It reads the COCO annotation files, creates masks for each annotation, colors the masks based on the annotation's category, and saves the colored masks as images. The script is designed to handle multiple categories and can be easily extended to support more categories if needed.