Face recognition models must be trained on a wide range of human faces in various conditions such as lighting, pose, accessories, expressions, camera positions and more. As well, obtaining real-world data for face recognition tasks is often complicated by a lack of diversity and complex privacy regulations.
Our synthetic data solution solves these challenges with the following attributes:
Fast and Hyperrealistic
Generate up to 4K high-quality images with outstanding detail and resolution
100k+ identities with broad diversity
Use our API to control for ethnicity, age, gender, etc.
Intra-class variance per ID
Our API also enables granular control of expression, head pose, eye gaze, lighting, glasses, hairstyles, etc.
Full privacy compliance
Eliminate privacy concerns with our PII-free synthetic data, including for teenage identities.
Get accurate annotations including never possible before semantic segmentation
Receive images accompanied by all needed metadata such as demographic, pose, light conditions, etc.
Our code template can get you started with generating data for training a face recognition model. Use our template and SDK to code in Python for over 100K+ identities including age, gender, ethnicity and more.