RunToolRunColor Palette Extractor
Extract color palettes from images.
How to Extract a Color Palette
Upload an image
Drop a photo, artwork or screenshot.
Colors are extracted locally
The tool finds the dominant colors in the image.
Copy the palette
Grab each color's HEX code for your design work.
How colours are extracted from an image
A photograph contains thousands of distinct colours, so extraction means grouping similar ones and picking representatives. The algorithm samples pixels, clusters them in colour space and reports the centre of each cluster — which is why the colours you get are often not colours present in any single pixel, but averages of a region.
This is also why the same image can produce different palettes in different tools. Clustering involves choices about how many groups to form and how to measure similarity, and reasonable choices give different answers.
Dominant is not the same as representative
The most common colour in a photograph is frequently the background — a wall, a sky, a sheet of paper — and it is rarely the colour that characterises the image. A product shot on white returns white as dominant, which is true and useless.
The colours worth having are usually the ones that occupy a moderate area with high saturation. Cropping to the subject before extracting is the simplest way to get a palette about the subject rather than about the backdrop.
An extracted palette is a starting point
Colours pulled from an image have no structure: no designated text colour, no background, no hierarchy. Building an interface palette from them means assigning roles and, critically, checking contrast — an extracted pair can be beautiful together and completely illegible as text on background.
Extracted palettes also tend to lack neutrals. Almost every design needs a range of greys or near-greys for text, borders and surfaces, and photographs rarely supply them.
Where it genuinely helps
Matching a page to a hero image, building a theme around a product photograph, finding the actual colours in a brand asset when the brand guidelines are missing, and generating coordinated backgrounds for a set of images are all cases where extraction saves real time.
It is also useful analytically: seeing which colours dominate a competitor's imagery, or checking whether a set of photographs is visually consistent enough to sit together in a grid.
Practical notes
Image compression alters colours slightly, so a heavily compressed JPEG yields a palette a little different from the original. For brand colours, take the value from the source file or the brand guidelines rather than from a compressed copy on a web page.
Extraction runs in your browser, so unreleased product photographs and client images are not uploaded anywhere.
How many colours to take
Asking for more colours does not produce a better palette. Beyond about six, the extra entries are usually near-duplicates of ones you already have, separated by differences too small to use. Five is enough for most purposes and forces the clustering to find genuinely distinct groups.
The exception is analysis rather than design. If you are studying an image's colour composition — checking consistency across a set of product shots, for instance — a longer list shows the distribution rather than giving you a working palette, and those are different questions.