List of manual image annotation tools: Difference between revisions
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Manual image annotation is the process of manually defining regions in an image and creating a textual description of those regions. This is a list of computer [[software]] which can be used for manual annotation of images. |
Manual image annotation is the process of manually defining regions in an image and creating a textual description of those regions. This is a list of computer [[software]] which can be used for manual annotation of images. |
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Revision as of 17:22, 28 August 2018
 | This article may require cleanup to meet Wikipedia's quality standards. The specific problem is: This page is a WP:LINKFARM. All external links of entries in this list should be removed and replaced with wikilinks. Entries should be removed if they lack wikilinks or inline citations of sources that are reliable and independent of the software. (August 2018) |
Manual image annotation is the process of manually defining regions in an image and creating a textual description of those regions. This is a list of computer software which can be used for manual annotation of images.
| Software | Description | Platform | License |
|---|---|---|---|
| OCLAVI | OCLAVI is an application where one can annotate their images that are stored in google drive or amazon s3 either alone or invite their team to annotate that can feed into their machine learning, artificial intelligence and NLP based models. OCLAVI Stands for Object(Image) Classification and Annotation for Computer Vision Models.
It supports all basic shapes like boundbox, circle, polygon, point and cuboid. It has REST API Export and you can directly feed data to your model. |
JS, HTML | Free for Academia otherwise custom license |
| DataLoop | DataLoop's platform offers manual and automatic image annotation capabilities. It supports image classification, creating bounding boxes, polygons and pixel level semantic segmentation (masks). The platform is also used to manage data (images), tasks and human workforce. | Custom License | |
| Labelbox | Labelbox is a data labeling platform for enterprises to easily train expert machine learning applications. The company is backed by top venture capitalists such as Kleiner Perkins, First Round and Google's new AI investment fund, Gradient Ventures[1].[2] Labelbox streamlines the data labeling workflow, from micro labeling projects for quick R&D to production grade projects requiring hundreds of collaborators. It can be used with on-premise data or hosted data. It is agnostic to data type and has an open source labeling frontend (https://github.com/Labelbox/Labelbox) [3] with already built interfaces for image classification & segmentation, text, audio and video annotation. Labelbox supports custom built labeling interfaces using a javascript API (labeling-api.js). Additional features include exporting data in JSON/CSV/WKT/COCO/Pascal VOC with auto-generated image masks, project & team management and labeling analytics. | Javascript, HTML, CSS, Python | Cloud or On-premise, some interfaces are Apache-2.0 |
| Pixorize | Pixorize is the browser-based image annotation platform where users can upload, annotate, and share images online. For images, Pixorize simplifies annotations for studying, giving feedback, explaining, and more. | Javascript, HTML, CSS | Custom License |
| FastAnnotationSingleObject | This tool can be used to annotate large number of images (draw bounding boxes and assign label) in PASCAL VOC format very fast if the user has collected the image corpus in an organized manner and each image has only one object of interest. Main goal of this tool was to reduce manual annotation time and because of its customization/restriction to label only one object per image, it is 10x faster than LabelImg (https://github.com/tzutalin/labelImg). You can annotate around 6000 images per day (8 hours) using this tool. | MATLAB | GPL-3.0 |
| AnnoStation | A cross-platform client–server web application to annotate videos and images. Allows labeling in larger teams, flexible task management, roles and rights, annotation of all kinds of primitives, and flexible XML based configuration. Developed by Hella Aglaia Mobile Vision for development and validation of ADAS and machine learning algorithms. | Javascript, HTML, CSS, PHP | Custom License |
| Images Annotation Programme | A full web application to annotate a collection of images. See this example. | Javascript, HTML, CSS, PHP | MIT License |
| Microsoft VoTT | A cross-platform tool to annotate videos and images. Supports computer-assisted object tracking with meanshift and direct deep learning framework integration with CNTK, Tensorflow, and YOLO to minimize manual annotation work. | Javascript, HTML, CSS, Windows, macOS, Linux[4] | MIT License |
| Alp’s Labeling Tool | Macro plugin to label images for Detectnet / KITTI dataset. | Windows 10
Ubuntu 14.04 |
Custom License |
| Annotorious | Annotorious is an Open Source image annotation toolkit written in JavaScript. | JavaScript, HTML, CSS[5] | MIT License |
| FastAnnotationTool | A tool using OpenCV to annotate images for image classification, optical character reading, ... | C++[6] | GNU GPL |
| Image Annotator Plug-in for Drupal | The module allows you to annotate images, and works in combination with field_collection. The module defines a new field called 'Image Annotator' that can be linked to an image field, so you can add multiple markers to an image. | PHP, Drupal | GNU GPL |
| Image Annotator Plug-in for Wordpress | This is a plugin that uses the HTML5 canvas and FabricJS to allow you to add shapes and text on top of images and display those images. | PHP, Javascript, Wordpress | GNU GPL |
| LabelImg | LabelImg is a graphical image annotation tool and label object bounding boxes in images. | Python | MIT License |
| LabelMe | The goal of LabelMe is to provide an online annotation tool to build image databases for computer vision research. | Perl, Javascript, HTML, CSS[7] | MIT License |
| LEAR Image Annotation Tool | A tool that facilitates the annotation of objects in images with bounding boxes. | C++ (with Qt library) | GNU GPL |
| Ratsnake Image Annotation Tool[8] | A tool for efficient, semantically-aware graphic annotation of images. Allows manual annotation through the use of polygons, splines and grids. It also incorporates a customizable Active Contour Model to enable semi-automatic segmentation of objects. | Java | Custom License |
| RectLabel | An image annotation tool to label images for bounding box object detection and segmentation. | Mac OS X | Custom License |
| Edgecase.ai | A cloud based image annotation tool to label images for bounding box object detection with audit of workers. Manual workers can also be hired via edgecase.ai | ||
| DataTurks | Dataturks (backed by Axilor ventures, FacebookStart etc) gives you a streamlined UX and labeling flow optimized based on user-research of ML tools of data-science teams at Amazon and Microsoft. It has a collaborative environment so that it takes just minutes for any data science team to create annotated datasets.
Supports Image Classification, Image Bounding Box, Image Segmentation, Document Annotation, NLP annotation etc. With the ability to zoom, overlapping labels, applying multiple labels etc. Also, give you real-time insights on the dataset and the labeler performance. One of the most widely used tool by thousands of AI teams, the data can be directly uploaded and downloaded in standard formats like PascalVoc, TensorFlow, Stanford NLP etc. See some of such projects here: https://dataturks.com/projects/trending |
JS, HTML | Free for OpenData otherwise custom license |
| szoter | Load your picture, take a screenshot or capture an image, then annotate, add text, and save to disk | Adobe Flash | Custom License |
| VGG Image Annotator (VIA) | A standalone image annotator application packaged as a single HTML file (< 400 KB) that runs on most modern web browsers | Javascript, HTML, CSS[9] | BSD 2-clause |
| jsoda | Simple pure JavaScript web application for bounding box annotation for object detection. | Javascript, HTML, CSS | MIT License |
| Philosys Label Editor / Ground Truth Annotator | Philosys Label Editor / Ground Truth Annotator allows full annotation of 2D images and 3D scenes represented point clouds with geometrical markers, properties and semantic segmentation. It is freely configurable by XML language and produces XML result data. It is used in automotive market to produce data for deep neural network machine learning and validation of algorithms for ADAS and Autonomous Driving. | Windows7, Windows10 | Custom License |
| Simple Image Annotator | An easy-to-use, bare-bones image annotator. | Python, Javascript, HTML, CSS | MIT License |
| Annotation of Image Data by Assignments (AIDA) | An easy-to-use web based annotation system that allows the definition of prescribed annotation tasks for a given study. | Javascript, HTML, CSS, Groovy | MIT License |
| Sequence.work | Cloud based annotation system. It can provide its own workforce ("workers") or you can provide your own. | Javascript, HTML, Node.js | Custom license |
| ImageTagger | An online platform for collaborative image labeling. It allows bounding box, polygon, line and point annotations and includes user, image and annotation management, annotation verification and customizable export formats. | Python (Django), Javascript, HTML, CSS | MIT License |
| Paperworks | A paper-and-marker based annotation system. Images are tiled into PDF pages, which are then to be printed, annotated with color markers, and scanned. The system then extract the color channels from the scanned images and convert those to annotation masks. | Python | BSD 2-clause |
| CVAT | Computer Vision Annotation Tool (CVAT) is a web-based tool which helps to annotate video and images for Computer Vision algorithms. It was inspired by Vatic free, online, interactive video annotation tool. CVAT has many powerful features: interpolation of bounding boxes between key frames, automatic annotation using TensorFlow OD API, shortcuts for most of critical actions, dashboard with a list of annotation tasks, LDAP and basic authorization, etc… It was created for and used by a professional data annotation team. UX and UI were optimized especially for computer vision tasks. | Python (Django), Javascript, HTML, CSS | MIT License |
| SimAnno | A simple web based image annotation tool providing just enough functionality to get your machine learning projects rolling. | Angular 5, Python 3 | Apache 2 License |
| Annotation App | Aims at solving image annotation needs, in the simplest, most efficient form by minimizing the number of interactions, context switch, and visual overload. It has a light configurable user interface. It supports bounding boxes, polygons, points, strokes and free outlines. It is easily embedded in a micro-tasks service like Amazon Mechanical Turk. Open sourced on GitHub[10]. Online user guide. | Web (Elm, JavaScript, HTML) | MPL-2.0 |
| Semantic Segmentation Editor | A web based labeling editor dedicated to the creation of training data for machine learning. The tool has been developed in the context of autonomous driving research. It supports images (.jpg and .png files) and point clouds (.pcd files). | JS, PaperJs, ThreeJS, React | MIT License |
| gtmaker | A simple image annotation tool for bounding box and contour. | Windows, macOS | MIT License |
References
- ^ "A pickaxe for the AI gold rush, Labelbox sells training data software". TechCrunch. Retrieved 2018-07-31.
- ^ "Labelbox website". Retrieved 10 March 2018.
- ^ "Labelbox labeling interface source". Retrieved 10 March 2018.
- ^ "End to End Object Detection in a Box". Retrieved 17 November 2017.
- ^ "Annotorious Core Library Source Code". Retrieved 26 January 2017.
- ^ "FastAnnotationTool Source". Retrieved 26 January 2017.
- ^ "LabelMe Source". Retrieved 26 January 2017.
- ^ Iakovidis, D. K.; Goudas, T.; Smailis, C.; Maglogiannis, I. (2014-01-27). "Ratsnake: A Versatile Image Annotation Tool with Application to Computer-Aided Diagnosis". The Scientific World Journal. 2014: 1–12. doi:10.1155/2014/286856. ISSN 2356-6140. PMC 3926425. PMID 24616617.
{{cite journal}}: CS1 maint: unflagged free DOI (link) - ^ "VGG Image Annotator Source". Retrieved 26 January 2017.
- ^ "mpizenberg/annotation-app". GitHub. Retrieved 2018-07-08.