SuperAnnotate Desktop: A better alternative to free annotation tools

Product Sep 16, 2020
SuperAnnotate OpenCV Partnershsip 1

It’s no secret that there is a massive functionality gap between free and commercial image annotation tools. SuperAnnotate Desktop is closing this gap by providing the fastest all-inclusive software tool for computer vision engineers to complete their annotation tasks. As part of our partnership with OpenCV, we decided to launch the best free annotation tool for the computer vision community. In this post, we’ll introduce SuperAnnotate’s free-to-use desktop app, discuss some of the reasons why we built it, and share more about many of the features which we feel dramatically increase the speed, accuracy, and efficiency of annotation projects.

Outline

  • The world of free annotation tools
  • Introducing SuperAnnotate Desktop 
  • Eight reasons why you should use SuperAnnotate Desktop 
  • Importing annotations from other platforms
  • The future of SuperAnnotate Desktop

The world of open-source annotation tools

The universe of free image annotation tools is enormous. Awesome Open Source suggests 100+ sources for image annotation alone and ranks them based on the number of GitHub stars each tool has. According to the list, CVAT managed by Intel and VOTT managed by Microsoft are among the most popular free tools for image annotation. There are more articles discussing open source annotation tools that you may research, such as Bohemian.ai, Sicara.ai.

We strongly recommend digging into various resources to learn about different tools available and even try and test them out. However, what you soon will start to realize is that free tools lack in many areas resulting in slow speed, disjointed project management, and an overall non-intuitive user experience - especially when you consider what we’ve come to expect from software today.

Introducing SuperAnnotate Desktop  

The founding team members of SuperAnnotate, me and my brother, Tigran, were Ph.D. students in biomedical imaging and computer vision, respectively. During the course of the PhDs, we spent a considerable amount of time working with images, particularly with annotations. In 2018, free annotation tools were as inconvenient as they are today, and it was quite painful using them. They were not only extremely slow and clunky but also lacked many key annotation functionalities. These pains led us to found SuperAnnotate.

Since launching SuperAnnotate, we have always focused on releasing software that is lightning-fast, easy to use, and extremely functional for all types of computer vision tasks. Over the last two years, we’ve worked hard to build what we think is the fastest and most efficient annotation platform for computer vision pipelines. And, as we came from academia, we also wanted to make a version of our platform easily installable and free for anyone, to help eliminate many of the pains my brother and I faced as Ph.D. students.

Back in June of 2019, we announced our partnership with OpenCV to bring a free annotation tool to the broader computer vision community that is a significant upgrade over the current free tools available. We released software for Mac, Windows, and Linux users that provides multiple advanced features that will accelerate your labeling process by 3–5x.


SuperAnnotate OpenCV Partnershsip 2

Eight reasons why you should use SuperAnnotate Desktop

Let’s dive deeper into some of the features that make our app unique compared to some of the most popular alternatives. As mentioned above, the paid version of our platform is focused on delivering lightning-fast speed, robust workflows, and a delightful user experience. We tried to bring that focus (and a few of the features) into our desktop app. Here’s a video that summarizes all these components.

Born out of SuperAnnotate’s core platform

We’ve spent the last two years and invested hundreds of thousands of engineering hours and millions of dollars on the core web version of SuperAnnotate, building what we feel is the fastest and most efficient annotation platform for computer vision. It incorporates feedback from annotators working long hours in the web version of our platform as well. This has allowed us to deliver our desktop editor with some of the designs, features, and refinements from our core product offering. We hope the result is a 100% free product that is delightful, feature-rich, and professional grade.

Advanced polygon tool

Polygon annotation is often the most time-consuming annotation task. Anyone who tried open source annotation tooling knows how poor the experience can be. We made several additions to traditional polygon tools in order to make manual polygon creation and editing much faster. Some of these features include:

  • Pen-polygon tool  — use the polygon as a pen making curved annotations much faster
  • Point addition/removal — Add and remove polygon points with just a couple of clicks
  • Edit polygon —  Substantially increase the speed of editing polygons with our pen polygon tool
  • Share polygon boundaries — draw polygons with shared boundaries 2x faster than traditional tools
  • Polygon move/group/delete — select, drag, drop, and delete individual or groups of polygons wherever you want

These are just some of the features that allow us to reduce polygon annotation duration by 20-60% while making polygon annotations significantly more accurate.

Filtering

Most annotation tools lack the ability to filter images. Yet we have found that class filtering has a dramatic impact on speeding up the annotation review process. Through SuperAnnotate’s filtering menu, users can display only images with certain classes they are interested in reviewing, avoiding the need to comb through all of the images and saving tremendous amounts of time.

Tracking multiple objects between frames

Tracking multiple objects between consecutive frames can dramatically improve the annotation experience while also making annotating much faster. Our desktop app allows users to select multiple objects and perform operations such as move, delete, group, copy, paste, and duplicate. Users can copy and duplicate annotations in successive frames while keeping the same attribute ID so that a particular attribute can be tracked through multiple frames easily.

Huge list of shortcuts

Gamers and power users of tools like Excel and Photoshop know how a robust list of shortcuts can both improve the user experience and add considerable speed. That’s why we made a massive list of shortcuts for actions like tool selection, on-screen navigation, copy, paste, group, ungroup objects, switching between frames, and others. All shortcuts take place on the left side of the keyboard (similar to gaming), so your right hand can stay focused on the mouse, and your left hand does not have to move while finding the right shortcut.

Labeling flexibility

Current platforms (both free and paid) limit you to one labeling workflow: you set the attributes and then draw the shapes. Oftentimes, having different workflows such as drawing shapes first or copying classes between instances can be much more efficient. With SuperAnnotate, we allow for a wide range of labeling workflows, giving users the flexibility they need to be most productive.

Classes/attributes/point labels

 Creating, adding, or deleting classes and attributes is very simple in the SuperAnnotate desktop app. Users can effortlessly import classes from previous projects saving the time required to define projects. In addition, we allow users to annotate individual points with free text. This can have multiple uses such as describing the object by a sentence, giving a tag to the object, or describing the specific point in the polygon (e.g. rear-right wheel).

Leveling up your annotations

As your annotation needs increase, you will likely find yourself looking for things like increased automation, ML features, more robust project management, detailed quality assurance, team collaboration, and user roles. You might also find yourself needing outsourced annotation teams. At SuperAnnotate, we can satisfy all of these and even more via our core platform. Our core platform leverages ML and workflow-based features to help computer vision teams increase annotation speed by up to 10x, while dramatically improving the quality of training data and increasing the efficiency of managing annotation projects. We also have integrated services on the platform, giving customers the ability to access thousands of professionally managed outsourced annotators armed with our lightning-fast tooling. You’re welcome for a demo if you are interested in learning more about our core platform and services.

Importing annotations from other platforms or open-source tools

Migrating to SuperAnnotate from other software is important to our customers. This was a common request because many of the users wanted to use our platform to quality check their previous work and move over from other tools. We’ve made it super easy to import annotated data from other annotation tools using only a few lines of code that are presented below. Then, once in our platform, users can leverage features described above like filtering and advanced polygon editing to easily perform QA on previous annotation work and check prediction accuracy.

To see how easy it is to migrate previous annotations, I have included the full code required. Note that you can transfer your annotations not only from other open-source tools but also from other paid platforms. For the conversion, you can use our SDK where we provide all the conversion scripts to ensure a smooth transition. Below is an example from Labelbox, but it can be applied to other platforms such as Amazon SageMaker, Google Cloud AutoML, Scale AI, VOTT, etc.

First, install the SDK and the supplementary repositories:

pip install superannotate

pip install 'git+https://github.com/cocodataset/panopticapi.git'

pip install 'git+https://github.com/philferriere/cocoapi.git#egg=pycocotools&subdirectory=PythonAPI'

The use the script below to convert your data to SuperAnnotate format:

import superannotate as sa

sa.import_annotation_format(<input_dir>, <output_dir>, "LabelBox", <dataset_name>)

Once you receive the converted json file, you can simply upload annotations into our editor.

SuperAnnotate OpenCV Partnershsip 3

Our premium features allow you to bring the images and clean the annotations in our web-based platform, then automate the annotation of the next set of images using transfer learning. Check out how to speed up image labeling using transfer learning without writing a single line of code.

The future of SuperAnnotate Desktop

The goal of SuperAnnotate Desktop is to provide fast and intuitive tools for academic researchers or solo annotators and save precious time during the annotation process. We will be constantly updating the tool to provide features that address our community’s most important pain points. Therefore, we encourage our community to be more active and raise such issues on our GitHub page.

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