Extract colors from any image and create beautiful palettes in less than 5 seconds!
The flow is simple: upload image -> extract colors -> copy the colors RGBA codes or the generated CSS code!
If you are not interested in replicating this application but you want to use it, you can head to the live demo
To install and build the application from source code, you first need to clone it:
git clone https://github.com/AstraBert/palettify
cd palettifyThen you need to build the application with the following command (Go 1.24.5+ is required for the build):
go build -tags netgo -ldflags '-s -w' -o palettifyThen you can run the application:
./palettifyImportant
If you wish to change something in the frontend of the application, you need to do so by modifying the .templ files in the templates folder. Once you are done, make sure to run templ generate to update the templates (you might need to install Templ)
You can directly install the application binary from NPM, using a simple:
npm install @cle-does-things/palettifyNote that, with this installation, you cannot customize the application itself.
Once the binary is installed, you can run it with:
palettifyYou can directly install the application binary from GitHub, using a simple:
go install github.com/AstraBert/palettify@latestYou need Go 1.24.5+ for this operation to be successfull.
Once the binary is installed, you can run it with:
palettifyYou can pull and run the Docker image from the GitHub Registry in the following way:
docker pull ghcr.io/AstraBert/palettify:main # use the main tag to have the version updated to the latest commit to main, otherwise use a version tag (v0.1.0 e.g.)
docker run -p 8000:8000 ghcr.io/AstraBert/palettify:mainTo build the Docker image locally, you first need to clone the GitHub repository:
git clone https://github.com/AstraBert/palettify
cd palettifyThen you can launch the build command:
docker build . -t username/imagename:tagOnce you are done, you can run it with:
docker run -p 8000:8000 username/imagename:tagContributions (both for the blog and for the source code) are more than welcome! You can find a detail contribution guide here.
This project is distributed under MIT license.