image-annotation-tool

kili-technology/kili-python-sdk

Simplest and fastest image and text annotation tool.

andywang0607/AutoAnnotationTool

A label tool aim to reduce semantic segmentation label time, rectangle and polygon annotation is supported

Manchery/ImageLabeler

基于Qt实现的图片数据标注工具. Image Annotation Tool Based on Qt, supporting 2D/3D Detection/Segmentation Annotation.

DS2BRAIN/ds2

Easiest way to use AI models without coding (Web UI & API support)

QuentinWach/image-ranker

Rank images using TrueSkill by comparing them against each other in the browser. 🖼📊

bhavyaajani/smart-labelme

Video / Image Annotation (Polygon, Semantic mask, Classification) with Python

robertarvind/Interactive-Semi-Automatic-Image-2D-Bounding-Box-Annotation-Tool-using-Multi-Template_Matching

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 order to train an object detection deep neural network such as Mask R-CNN or U-Net. As the Annotater/User starts annotating/labelling by drawing a bounding box for a few number of images in the selected folder then the algorithm suggests bounding box predictions for the rest of the yet to be annotated/labelled images in the folder. If the predictions are right then the user/annotater can simply press the keyboard key 'y' which indicates that the detected bounding box is correct. If the prediction is wrong then the user/annotater can manually draw a rectangular 2D bounding box over the correct ROI (Region of interest) in the image and then press the key 'y' to proceed further to the rest of the images in the folder. If the user/annotater made a mistake while drawing the 2D bounding box, then he/she can press the key 'n' in order to remove the incorrectly marked 2D bounding box and he/she can repeat the process for the same image until he/she draws the correct 2D bounding box and then after drawing the correct 2D bounding box, the user/annotater may press the key 'y' to continue to the rest of the images. The 2D bounding box prediction over the whole image data set improves as the user/annotater annotates/labels more number of images by drawing 2D bounding boxes. This tool allows the user/annotater to not only interactively and rapidly annotate large number of images but also to validate the predictions at the same time interactively. This tool helps the user/annotater to save a lot of time when annotating/labelling and validating the predictions for a large number of training images in a folder. Instructions to use:- 1. If the training images are in JPEG or any other format, then convert them to PNG format using some other tool or program before using these images for annotation. 2. All the training images must contain the object of interest which is to be annotated. 3. Currently the application only supports 2D bounding box annotation for single object detection per image, but in the future semantic segmentation based annotation features will be added which will allow precise boundary segmentation masks of an object in an image. 4. If some or all of the training images have varying dimensions(shapes/resolutions), then resize them to the same dimensions using this tool by providing the height and width to which all the training images need to be resized to. The height and width are inputed separately in two different dialog boxes which pop up once the program is executed. If the training images need not be resized then press the cancel button in the dialog boxes requesting the height and width. 5. Select the folder containing the training images by navigating to the folder containing the training images through a dialog box which pops up after the program is executed. If the images need to be resized then two dialog boxes pop up. The first dialog box is to navigate to the destination folder containing the unresized raw training images and after resizing another dialog box pops up to navigate to the folder containing the saved resized training images named as "resized_data". If the images need not be resized then only one dialog box pops up so that the user can navigate to the raw training images folder directly. 6. The images in the folder pop up one by one. After drawing the correct 2D bounding box over the ROI (region of Interest), press the 'y' key. Except the first image, the rest of the images will have a 2D bounding box drawn over them. If the predicted box is accurate, then continue by pressing the 'y' key. If the prediction is incorrect, then draw the accurate bounding box and press the 'y' key. If any mistake occured while drawing the 2D box, then reset the image by removing the incorrect drawing by pressing the 'n' key and then draw the correct box and press the 'y' key. 7. The output images are stored in four different folders in the same directory containing the training images folder. among the four folders, one contains the cropped templates of the bounding boxes, black and white mask images, training images and the images with 2D box detection markings.

urobots-io/anno

Cross-platform image labeling tool for AI

hou2zi0/animexgeo

Annotate images in .JPG- or .PNG-format with markers and polygons in connection with freely composable input form fields for metadata and subsequently export the annotation data as GeoJSON, as data for cropping with Pillow image library, or download the cut out polygons and their corresponding metadata as a ZIP file.

silencesys/dh--image-annotation-tool

Image annotation tool is a web application that allows users to mark zones of interest in an image. These zones are then converted to XML TEI code snippet that can be used in your document to connect the image and the text.

danvc/remo

Platform for Image Labeling and Annotation Open Computer Vision

insspb/ikt

Image keyword tool

lifeart/sm-annotate

Vector Annotation tool for Video & Image files

looooongChen/IMANNO

an image annotation toolkit

stefanherdy/SAM-GAN-Clustering

Implementation of Meta AI's Segment Anything Model to do an automated image annotation of simple microscope images and a modified GAN to cluster the preprocessed images according to their qualitative features

valentinitnelav/img-with-box-from-excel

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

forhadsidhu/Image_Annotation_tool

Image Annotation Tool for preparing data of Deep learning model

LauLauThom/Fiji-QualiAnnotations

Fiji plugins for qualitative image annotations + analysis workflows for image-classification and data-visualization

pranavgoel29/Image-Annotation-tool

This tool is useful for tasks such as labeling datasets for machine learning, creating visual notes, or any other purpose that requires image annotation.

VisioSphereAI/labelvim

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.

Marinto-Richee/AI-Image-Annotation

An intuitive Python tool for annotating images with bounding boxes. Easily assign custom classes to objects and save annotations. Includes AI model integration for automated annotation. Perfect for streamlining computer vision projects. classes to these objects, and save annotations.

mnthnx64/image-annotator

Annotate 3D bounding boxes for 2D images with the link in description

rtrahms/dlannotator

Cross-Platform Image Annotation Tool. Useful for Images and Image Sequences targeted for training Object Detector DNNs

shamspias/VideoLabelMagic

Automate video data creation. Extract frames, generate annotations, export in various formats (YOLOv8, YOLO1.1). Integrate with Roboflow, CVAT. Built with Python and Streamlit.

TinyTinni/RegAn

A tool to create an annotated set of strict ordered data based on images.

tristan-mcinnis/Ollama-Image-Processing-CLI-Tool

This tool processes images from a specified directory or file using a local API for image analysis. It allows users to provide custom prompts and select vision-capable models for generating image descriptions.

alexkhor1983/ImageAnnotation

a simple tool to generate image caption

KahnSvaer/CustomImageTagger

A simple image annotator for showing images made with PIL and Tkinter

ogemarques/python-matlab

Example of how to integrate MATLAB apps into a Python deep learning workflow for computer vision and image analysis tasks.

well-thats-funny/simpletagger

Simple tool for images tagging

worree133/Labelme-for-Auto-Human-Segmentation

EPFL-Center-for-Imaging/napari-adaptive-painting

Propagate label annotations in Napari.

GioPicci/docu-labeler

DocuLabeler is a labeling and annotation tool focused on offering a simple and fast way to annotate document images.

pr1266/Image_Annotation_Assistant

Object Tracking based image annotation assistant, in order to increase annotation speed up

tanujajoshi1/Image-Annotation-Tool

Image Annotation Tool using Konva