Solutions for Computer Vision.
Whether you want to implement autonomous checkout systems, analyze patron demographics, or improve inventory management, synthetic data from Zumo Labs can accelerate the development and improve the performance of your computer vision models.
Running an object detection model for the purposes of inventory management requires training on potentially thousands of SKUs. Zumo Labs can replicate those products with the fidelity required to train on, provide truly massive data sets, and bolster the model performance by ensuring class balance and randomizing lighting and appearance.
If you’re building a model that recognizes how patrons interact with your products, you need a tremendous variety of models and poses. Our synthetic data sets include full pose keypoints, even when occluded, which means your models always have access to ground truth in training.
You may want a functional model in advance of the launch of your cashierless store concept, or to be able to identify new products as soon as they’re received. Synthetic data addresses the issue of data scarcity, enabling you to train and iterate on your computer vision models before you have any real world data.
Representative & Privacy Compliant
Whether you’re using computer vision to reduce shrink or simply understand customer behavior, your models will need to be trained on human data. Synthetic data can be gender balanced and diverse. It’s also free of the privacy concerns that come with storing images of real people; it’s both GDPR and CCPA compliant.
Save yourself time and money by taking complete control of your machine learning workflow with synthetic data.