IBM launches new open source tool to label images using AI
Images for use in development projects need to be correctly labeled to be of use. But adding labels is a task that can involve many hours of work by human analysts painstakingly applying manual labels to images, time that could be better spent on other, more creative, tasks.
In order to streamline the labelling process IBM has created a new automated labeling tool for the open source Cloud Annotations project that uses AI to 'auto-label' images and thus speed up the process.
Backed by IBM Cloud Object Storage, Cloud Annotations enables users to store as much data as they need, access the data from anywhere and share it across multiple collaborators in real-time.
Writing on the IBM Developer Blog, Nicholas Bourdakos, developer advocate, IBM Cognitive Applications says, "Faced with the daunting task of hand labeling thousands of images, developers are looking for an easier way to train their object detection models. Currently, it takes 200-500 samples of hand-labeled images for a model to detect one specific object. Auto-labeling images speeds the process and gives developers back valuable time to work on other innovative projects."
To use Cloud Annotations a user uploads a small number of photos, trains a model then uses the tool to label more photos automatically. Finished labels can be reviewed to verify the tool's accuracy.
Bourdakos has also posted a video on Twitter demonstrating how the new tool works.
Cloud Annotations now has auto labeling ? It's an early beta, but you can now upload a model to your project and let it do the labeling for you! pic.twitter.com/cEXJQVW2xl
— Nick Bourdakos (@bourdakos1) December 3, 2019
The Cloud Annotations tool is available now on GitHub for anyone to try out and IBM is keen to receive feedback on its effectiveness.