- Overview
- Getting Started
- Screenshots
- Accurately mix any color from your reference photo using the paints you have
- Add your favorite color mixtures to the palette
- Do a tonal value study
- Reduce the detail on your reference photo
- Turn any photo into an outline and print it
- Draw a grid over your reference photo
- Play around with limited color palettes
- Mix specific colors from specific brands in any proportion
- Remove the background from your illustrations
- Use pairwise comparison to rank your photos
- Share your color set with others or between your devices
- Install ArtistAssistApp on your device
- Implementation details
ArtistAssistApp is a Progressive Web App (PWA) for artists to accurately mix any color from a photo, analyze tonal values, turn a photo into an outline, draw with the grid method, paint with a limited palette, simplify a photo, compare photos pairwise, remove the background from an image, and more.
Try it now at ArtistAssistApp.com
- Go to ArtistAssistApp.com.
- Watch the video tutorials.
- Join on Patreon
- Want to contact us? Find our contacts.
ArtistAssistApp does not use artificial intelligence (AI), but rather mathematics.
The web app doesn't depend on any math or color library and includes the implementation of the following:
- conversion between color models (e.g. sRGB to Oklab),
- sRGB to spectral reflectance,
- subtractive color mixing using Kubelka-Munk theory,
- matrix operations,
- matrix inversion using LU decomposition,
- solving a system of linear algebraic equations using forward and backward substitution,
- the average color of the circular area of the image
- calculation of color similarity by comparing spectral reflections (Euclidean distance and cosine similarity)
- vector operations,
- threshold filter based on perceived lightness (2D Canvas and WebGL),
- median blur filter using sliding window and histogram (2D Canvas),
- Kuwahara blur filter (WebGL),
- Sobel operator for edge detection (2D Canvas and WebGL),
- median cut for color quantization (2D Canvas and WebGL),
- adjusting white balance with white patch algorithm (2D Canvas and WebGL),
- adjusting saturation (2D Canvas and WebGL),
- invert colors filter (2D Canvas and WebGL),
- ranking images using pairwise comparison and Elo rating system,
- and more.
The web app uses Web Workers for parallel processing and Service Workers for offline access.
