Free online eyedropper tool that extracts colors from any image. Upload a PNG, JPG, or WebP file, hover to preview colors with a zoom lens, click to pick, and get HEX, RGB, and HSL values instantly. Build color palettes from images.
Drop an image here or click to upload
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Click on the image to pick colors and build a palette.
Image Color Picker is a free online eyedropper tool that extracts colors from any uploaded image. Drop or upload a PNG, JPG, GIF, WebP, or SVG file, then hover over any pixel to see its color in real time — complete with a zoom lens for pixel-level precision. Click to pick a color and get its value in HEX, RGB, and HSL formats instantly. Build a palette by picking multiple colors from your image, then copy all values at once. An optional 3×3 average mode smooths out noise by averaging neighboring pixels. All processing happens locally in your browser using the Canvas API — your images are never uploaded to any server.
Use the Image Color Picker when you need to extract exact color values from a screenshot, design mockup, photograph, or any visual reference. It is ideal for matching colors from a client's logo or brand assets, sampling colors from inspiration images for your CSS palette, checking the exact color value of a UI element in a screenshot, and building color palettes from photographs for design projects.
Front-end developers and designers use the Image Color Picker to extract brand colors from logos and marketing assets, sample accent colors from photographs for web design, verify that rendered colors match design specifications, build CSS color palettes from visual references and mood boards, and identify colors in screenshots during design QA and code review. The zoom lens and 3×3 averaging mode make it especially useful for images with gradients, anti-aliased edges, or compressed artifacts where single-pixel sampling might capture noise.
Essential terms and definitions related to Image Color Picker.
A color sampling tool that captures the exact color value of a pixel at the cursor position. Originally a physical tool in photography, the digital eyedropper reads pixel data from a rendered image and reports it in color formats like HEX, RGB, and HSL. Modern browsers support a native EyeDropper API, but it requires user gesture activation and is not available in all browsers.
A browser API for drawing and manipulating graphics using JavaScript. The Canvas 2D rendering context provides getImageData() to read raw pixel RGBA values from any rendered image. This tool uses the Canvas API to load uploaded images and extract per-pixel color data without any server-side processing.
A specific organization of colors that defines the range (gamut) of colors that can be represented. sRGB is the standard color space for the web and most consumer displays. Wider gamut spaces like Display P3 (used by modern Apple devices) and Adobe RGB (used in print) can represent more saturated colors. The Canvas API operates in sRGB by default.
A technique that smooths jagged edges in digital images by blending edge pixels with surrounding colors. This means that a pixel on the edge of a red shape on a white background might appear as a lighter shade of red (mixed with white). When using an eyedropper, anti-aliased edge pixels will not match the pure color of the shape — zoom in or use average sampling to get a more accurate color.
The tool supports all image formats that your browser can display: PNG, JPEG, GIF, WebP, SVG, BMP, and ICO. Images are loaded into an HTML Canvas element for pixel-level color extraction. There is no file size limit imposed by the tool — performance depends on your device's memory and the image dimensions.
Several factors can cause color discrepancies: JPEG compression introduces color artifacts near edges, anti-aliasing blends pixels with surrounding colors, and your monitor's color profile may display colors differently from the raw pixel values. Use the 3×3 average mode to smooth out compression artifacts, or zoom in to identify the exact pixel you want to sample.
Yes. Take a screenshot, save it as PNG (for pixel-perfect accuracy) or JPEG, then upload it to the tool. PNG is preferred for UI screenshots because it uses lossless compression, preserving exact pixel colors. JPEG compression may alter colors slightly, especially in flat-color areas like UI elements.
When enabled, instead of sampling a single pixel, the tool averages the RGB values of the target pixel and its 8 immediate neighbors (a 3×3 grid). This reduces noise from compression artifacts, anti-aliasing, and dithering, giving you a more representative color of the area. It is especially useful for photographs and compressed images.
Yes. Click on different areas of the image to pick multiple colors. Each picked color is added to the palette strip below the image with its HEX, RGB, and HSL values. You can copy all palette colors at once using the Copy All button, making it easy to transfer an entire color scheme to your CSS or design tool.
Common errors developers encounter and how to resolve them.
Canvas tainted by cross-origin data: Cannot pick colors This error occurs when trying to load an image from a different domain directly via URL. Due to browser CORS (Cross-Origin Resource Sharing) security policies, the Canvas API cannot read pixel data from cross-origin images. Solution: download the image to your device first, then upload it to this tool using the file upload or drag-and-drop feature.
Colors appear washed out or incorrect on the canvas This can happen if the image contains an embedded ICC color profile that the Canvas API does not fully support. The Canvas 2D context uses sRGB by default. Images in wider color spaces (Display P3, Adobe RGB) will be converted to sRGB, which may shift some colors. For color-critical work, use the original design file in your design tool instead of a rasterized export.
Picked color shows rgba(0, 0, 0, 0) on transparent areas Transparent pixels in PNG or GIF images have an alpha value of 0, meaning the RGB values are undefined (often all zeros). The tool reports the actual pixel data including alpha. If you need to know what color the transparent area appears as in context, composite the image onto a known background color first, or use the surrounding opaque pixels as reference.