These samples are internal test generations used to show expected style, framing behavior, and common output differences. They are not endorsements or real-world claims.

A centered face with clear lighting. This kind of input usually produces the most stable tiny-face alignment.

Close-up portrait input with strong face visibility. Useful for checking edge smoothness around facial contours.

Group composition used to test how the model handles multiple visible faces in one frame.

A partial side angle to show how pose changes can affect final proportion and expression clarity.

Higher contrast input with stronger shadows. Helpful for understanding where artifacts may appear.

Faces at different distances from the camera. Useful for comparing consistency across foreground and background subjects.

A visually busy background to illustrate how clutter can influence perceived output quality.

Soft-light portrait showing cleaner blending around face boundaries.

Wide-frame group sample for evaluating tiny-face readability when subjects are smaller in the source image.
Showing 1-9 of 9 creations
Use the gallery as a quality reference before uploading your own photo.
Compare your own photo to samples with similar lighting, angle, and face visibility. This gives you a more realistic quality expectation.
Group photos, extreme poses, and low light can reduce consistency. The examples above show typical outcomes in those conditions.
Treat outputs as stylized AI edits. Review the final image before public posting and add context when needed.
Quick answers about where these examples come from and how to use them.
Use the generator when you are ready, and review policy/disclosure pages before public posting.