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In addition, you can also work with entity tagging for full-length documents through its document annotation functionality. Like most other annotation tools, Dataturks also offers the ability to tag images and videos.

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No options for drawing any shapes other than rectanglesĭescription: Perhaps the best of the bunch, Dataturks offers a free collaborative annotation tool that you can sign up for free via their servers or alternatively, they offer an on-premise version which can be self-hosted.Needs to be installed locally and the installation process is more cumbersome than it should be, at least on MacOS.

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Limited free license to 2,500 tags/yearĭescription: An extremely simple image-only annotation tool written in Python and relying on the Qt library for its UI.

Offers the possibility of hiring data labelers.

Multiple shortcuts allow for fast annotation.

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Full on-premise: requires coordinating with their engineering team to fully deploy the software locally.

Hybrid on-premise: Allows you to host data on your own servers, but generated assets will be stored on Labelbox servers, unaccessible to them.

On top of their computer vision functionalities, they also offer text classification functionality. In their own words, they are a “data-labeling and training-data management platform”.

Extensible model for importing/exporting data from local or cloud storage providersĭescription: Labelbox has a slick user interface and a ton of functionalities.

Here’s an illustration for labeling a license plate on a car: When choosing to draw a polygon, you pinpoint the contour of your target object and when you’re finished, you double-click on the last location. VoTT then offers shortcuts, you can press the P key for drawing a polygon or the R key for a rectangle.

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For the purpose of this review I only looked at image labeling, although the process of labeling appears to be almost identical for video assets.Īs mentioned earlier, discovering how to annotate data can be a little tricky with this tool, so I’ve decided to give you some quick instructions on how the labeling process works in order to save you some time: After having selected the data to annotate, as well as the source and target connections, you can proceed to annotate then images by creating a tag on the right-side panel. Each project requires a target and a source connection, meaning the locations from which the assets are pulled (source) and where the data should be stored and sent (target). The way you work with VoTT is through what they call “projects”. I tested the MacOS version, the installation was quick and simple.

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It can be run locally, offers MacOS, Windows and Linux support or it can be accessed as a web app and is compatible with most modern web browsers. However, once you decipher how to work with it the rest goes rather smoothly. Link: CVAT VoTT (Visual Object Tagging Tool)ĭescription: Open source annotation and labeling tool for videos and images, with a no-brainer UI which feels a little outdated and getting the hang of it takes a little longer than it should.

Support for optional tools (TensorFlow Object Detection, Deep Learning Deployment Toolkit, etc.).

It’s relatively easy to deploy in the local network using Docker. It’s a browser-based application and it works only with Google’s Chrome browser. This will hopefully shine some light on your decision-making process CVAT (Computer Vision Annotation Tool)ĭescription: Developed by researchers at Intel, CVAT is an open-source annotation tool that works both for images and videos alike. We researched and tested five annotation tools and outlined the pros and cons of each one. With that in mind, it is safe to say that every aspect of the data annotation process should be treated carefully, including choosing the right tool for it. Therefore, choosing the right tool for your project can significantly both affect the quality of the data you end up with as well as the time it will take to complete it.

The data annotation process, as crucial as it is, is also one of the most time-consuming aspects of a project and, without a doubt, also the least-glamorous aspect of it.