StarByFace vs Palette.fm

StarByFace matches your selfie to celebrity faces using neural network recognition. Upload one clear frontal photo and the site builds a facial pattern from eyebrows, eyes, nose, and mouth positions, then ranks the closest celebrity matches.

The web app is free and also ships as Star By Face mobile apps on Google Play and the App Store. Sample photos on the homepage let you test the flow before uploading your own picture.

Results split into male, female, and best-pair celebrity lists so you can compare look-alike suggestions side by side. Recognition accuracy depends on image resolution and lighting, and the site warns that only one person should appear in the frame.

StarByFace fits casual users hunting a doppelganger meme or party icebreaker rather than professional identity verification. High server load can queue requests, so the page asks you not to refresh while processing.

Palette.fm colorizes black-and-white photos through a browser upload flow with 21+ filter presets and keyword-based color tweaks. Upload an image, pick a filter, adjust descriptive keywords if needed, then download a full-resolution result or keep iterating on previews. The photo editing workflow targets family historians, photographers, and creators restoring old prints without opening Photoshop.

Most colorizers lean on heavy sepia and purple casts with little room to steer skin tones or fabric colors. Palette.fm lets you click a filter then fine-tune hues through plain-language keywords, and it sells one-time credit packs alongside subscriptions. Free previews cap at 500x500 pixels with a watermark, while paid credits remove the logo and support files up to 5000x5000 pixels.

Genealogy researchers, photo archivists, and YouTube educators use Palette.fm to batch-test color looks before committing credits. The site reports 54 million photos colorized and 6.6 million registered users, with an API option for teams that want programmatic access.