How to streamline your Object Detection labeling experience with Hasty.ai

Object Detection is one of the most popular tasks in Computer Vision. It performs Classification and Localization algorithms on images with one or more objects. The idea behind OD is to detect the class of every object in the image and detect its location by using a bounding box.

Object Detection is widely used by businesses, governments, and other actors. Its real-life applications include:

• Detecting people without masks in crowded spaces;
• Helping self-driving vehicles perceive the space around them;
• Recognizing numbers on the car plates;
• Medical image processing and diagnosis;
• Being a part of other tasks (object tracking, activity recognition, image annotation, etc.)

However, nowadays, data annotation might be a bottleneck for AI startups as the conventional labeling approach is both costly and time-consuming. Hasty’s data-centric ML platform addresses the pain and automates 90% of the work needed to build and optimize your dataset for the most​ advanced use cases ​ with our self-learning assistants using AI to train AI.

Below is a video tutorial showing how to streamline your Instance Segmentation experience with Hasty. Want to make your annotation workflow easier? Watch the video and see how we can help.