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Palette.fm is a browser-based service that adds AI-predicted color to black-and-white photographs. You upload an image, choose a filter, optionally guide the result with descriptive words, then colorize and download it. It is a fast way to explore plausible color treatments—not a way to recover or prove a photograph’s original colors. Free users can preview results, but large previews are limited to 500 × 500 pixels and carry a Palette watermark; paid credits provide watermark-free, higher-resolution output, subject to the service’s limits.
What Palette.fm does—and what it does not
Palette.fm is an online AI colorization tool for monochrome photographs. Its workflow does not require painting each object or creating Photoshop masks: the service predicts color across the image, with more than 21 filters and text-based customization for trying different looks. Palette also documents API, bulk-processing, and video-related workflows for professional and developer use. See Palette.fm and its feature documentation.
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Colorization is not the same as restoration. It adds predicted color; it does not, by itself, repair scratches, tears, blur, missing image areas, or poor exposure. Nor can a grayscale photograph usually reveal whether a particular shirt was blue, green, or brown. Treat the result as an interpretation unless you can verify the colors from another source.
Palette is a good fit if you want a quick first pass, several visual options, and a browser workflow. It is less suitable if you need offline processing, exact manual control over every region, or historically verified color.
How to colorize a photo with Palette.fm
- Open Palette.fm and select Upload image, or drag and drop an image.
- Choose a color filter. Try more than one if the first result has an unsuitable overall cast.
- Use the adjustment control to add descriptive words or keywords that guide the color treatment.
- Select Colorize, inspect the result, then download it or continue editing.
For example, if foliage looks too yellow or skin too orange, compare another filter and try guidance such as “natural skin tones, muted clothing, overcast daylight.” That is a practical starting point, not a guaranteed formula: Palette describes text guidance but does not publish a definitive prompt syntax or promise particular results.
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Prepare the scan first
- Scan at the highest practical optical resolution and keep an untouched copy of the original.
- Crop unnecessary borders and correct severe rotation.
- If dust or scratches confuse the result, consider repairing the scan separately before colorizing it.
- Keep the original monochrome file alongside each colorized version so the interpretation is never mistaken for the source.
Free previews, credits, and output size
The consumer site’s displayed terms distinguish a preview from a finished export. The figures below are Palette’s published consumer pricing signals, not a guarantee of current checkout pricing; plan quantities, taxes, currency, and promotions can change. Check the live pricing display before buying.
| Option | What Palette advertises | Important conditions |
|---|---|---|
| Free | $0; unlimited previews and one free trial credit | Large-image previews are resized to a maximum of 500 × 500 pixels and include a Palette logo watermark. The trial credit can produce one logo-free, full-resolution colorization. |
| Subscription | $72 per year, displayed as $6 per month; 480 credits per year | Credits refresh; unused credits can roll over up to five times the monthly plan amount. Subscription credits remain valid while the subscription is active. |
| One-time credits | A displayed option was $49 for 75 credits; other displayed quantities included 1, 10, 200, and 500 credits | One-time credits are advertised as valid for two years. Confirm the live offer and terms at purchase. |
Palette says one credit produces one logo-free, high-resolution colorization, with consumer output up to 5000 × 5000 pixels. That is separate from the free preview limit. The practical choice is straightforward: previews help you compare looks, while a credit is needed for the clean, larger export.
How reliable are the colors?
Palette can produce convincing, natural-looking results, but visual plausibility is not historical accuracy. Its filters offer alternative interpretations; they are not evidence that one version is correct. Palette describes its engine as proprietary and claims realistic color, dynamic skin tones, and processing of approximately 100–300 milliseconds per image. Those are the company’s own claims, not an independent benchmark; the reviewed public sources do not establish a neutral accuracy score or systematic comparison with competing tools. See Palette’s engine description.
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Inspect the result at full size, especially where color carries historical or personal meaning:
- Faces and skin: Check cheeks, hands, lips, and ears for orange, pink, or gray patches.
- Clothing and uniforms: Do not infer a person’s unit, organization, or period from an AI-colored garment without independent documentation.
- Flags, signs, and insignia: Small symbols and text are easy to color attractively but incorrectly.
- Dark and pale areas: Black clothes, hair, shadows, and deep-blue objects can merge; white clothing, clouds, snow, and walls can pick up a tint from surrounding light.
- Landscapes: Green foliage, blue skies, and brown earth are common visual associations, not proof of the season, lighting, or actual scene colors.
- Edges and small subjects: Check hands, thin objects, crowded group photos, and small faces for color bleeding or inconsistent treatment.
When a color matters, compare against a known object, another photograph, a written record, or a credible historical reference. Keep uncertain details labeled as AI-generated rather than presenting them as recovered fact.
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- Colorization is not repair. A damaged face, missing section, or blurred object remains damaged or uncertain unless separately restored.
- Free output is limited. Large previews are reduced to 500 × 500 pixels and watermarked; a clean high-resolution export uses a credit.
- Processing is online. Palette’s standard consumer workflow requires uploading the image to its service.
- Manual control is limited compared with an editor. Filters and keyword guidance do not amount to precise, layer-based control of every object.
- Faded color is a different problem. Palette’s strongest documented use is monochrome colorization. The reviewed consumer information does not clearly establish a dedicated faded-color restoration mode, so do not assume it will faithfully reconstruct an already-color photograph.
- Consumer and API limits differ. The consumer site advertises output up to 5000 × 5000 pixels, while the API documentation describes SD, Full HD, and 4K tiers and a 10 MB per-image limit. These are different product specifications, not one universal cap.
Privacy and rights
Palette’s privacy policy says uploaded files are securely processed and deleted shortly after results are provided; it says files are not published, shared, or used for another purpose unless submitted as feedback. The policy reviewed is effective September 24, 2024. Because policies can change, check the live privacy policy before uploading sensitive family, legal, medical, or unpublished commercial images.
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For sensitive material, consider whether you have consent to upload it, remove metadata that could reveal private information, retain archival originals offline, and check any workplace or client rules for third-party cloud processing.
Palette’s terms of service say content generated through its API or user interface belongs to the user who submitted the content. That contractual statement does not necessarily settle rights in the original photograph or every jurisdiction’s treatment of AI-modified images. Do not read it as a universal guarantee of copyright or commercial-use rights.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Palette.fm compared with alternatives
| Tool | Best for | Main distinction | Trade-off |
|---|---|---|---|
| Palette.fm | Fast, adjustable browser colorization | Multiple filters, keyword guidance, free previews, and one-time credit options | Predicted colors; cloud processing; clean high-resolution output uses credits |
| MyHeritage In Color | Genealogy and family-photo archives | Works with photos uploaded to or already stored in a MyHeritage family tree; preserves the original separately | Several colorizations are free, then a subscription is required; non-subscribers receive a watermark |
| MyHeritage Reimagine | Mobile-oriented scanning and photo-archive workflows | Combines colorization with enhancement, repair, animation, and related photo features | An all-in-one subscription can be unnecessary if you only need occasional colorization |
| Adobe Photoshop Colorize | Designers and retouchers who need finishing control | Colorize Neural Filter can be followed by layer-, mask-, and retouch-based edits | More complex than an upload-and-download service and requires Photoshop |
| VanceAI Photo Colorizer | Users seeking colorization alongside enhancement tools | Browser workflow positioned around analyzing image regions and pairing with restoration | Credit-based use and a separate product ecosystem |
MyHeritage says its In Color technology was licensed from DeOldify and enhanced by MyHeritage; it can colorize uploaded images or photos already in a family tree and stores the original separately. Its help page describes several free colorizations, a subscription requirement afterward, watermarking for non-subscribers, and logo-free output for Complete subscribers. Details: MyHeritage In Color.
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For MyHeritage Reimagine, the reviewed help page listed $49.99 per year with a seven-day trial for the annual plan, or $7.99 per month without a trial. Check its current pricing page before subscribing.
Adobe documents the Colorize Neural Filter under Photoshop’s Filters menu and says it uses AI to predict colors for black-and-white images; the operation can be reverted. See Adobe’s Neural Filters documentation and Colorize feature page.
VanceAI says its web colorizer accepts JPG, PNG, and WebP files up to 10 MB, uses one to three credits depending on image size, and permits commercial use of paid-credit outputs without licensing restrictions on the result. Those are VanceAI’s claims; consult its current product terms for the applicable details.
For developers and high-volume users
Palette’s API documentation describes endpoints for automatic-prompt colorization, base64 output, reference-image colorization, and prompt generation, along with bulk workflows using scripts, Google Colab, Google Drive, and Dropbox. Its feature documentation gives a 10 MB per-image limit and lists broad accepted formats including JPG/JPEG, PNG, TIFF, PSD, WebP, HEIC, AVIF, BMP, and GIF. API output tiers include SD, Full HD, and 4K; do not assume the API file or output limits match the consumer product. See API features and the Palette documentation.
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Palette also documents frame-based video colorization and describes its video API as beta. Its documentation notes temporal-coherence limitations: a reference frame and repeated prompt may help for shorter scenes, but the system does not guarantee perfectly consistent color from frame to frame. See video plan documentation and feature notes.
Quick Recap
Which tool should you choose?
- Choose Palette.fm for a fast first pass, several color interpretations, and a browser-based workflow with keyword guidance.
- Choose MyHeritage In Color when family-tree storage and genealogy context matter more than filter experimentation.
- Choose Reimagine if scanning, repair, enhancement, and archive features justify an all-in-one app.
- Choose Photoshop when manual retouching and region-by-region refinement are central to the job.
- Consider another workflow if offline processing or a clearly documented enterprise data-processing agreement is essential.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
