For media texture processing, the strongest matches are rodzill4/material-maker (Material Maker is a node-based procedural texture generator and), anthonynsimon/bild (Bild is an image processing library in Go that) and alexjc/neural-doodle (This repository provides neural network tools for texture synthesis). armory3d/armortools and mxgmn/wavefunctioncollapse round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
Discover the best open-source media texture processing libraries on GitHub, ranked by stars and activity, and compare top alternatives to find the right fit.
Material Maker is a node-based material editor, procedural texture generator, and 3D painting software. Built on the Godot engine, it provides a visual graph interface for authoring complex surface properties and textures through the connection of functional operation nodes. The tool allows for painting colors and materials directly onto the surfaces of three-dimensional geometry. It features a procedural material exporter that converts authored data into file formats compatible with external 3D modeling software and game engines. The system supports physically based rendering material creat
Material Maker is a node-based procedural texture generator and material editor that provides GPU-accelerated visual graph authoring and cross-platform support for computer graphics workflows.
Bild is an image processing library implemented in the Go programming language. It provides a collection of algorithmic engines for image manipulation, including a convolution kernel engine for filtering, an image blending tool for layer composition, and a procedural noise generator for creating synthetic textures. The project is distinguished by its procedural generation capabilities, implementing Perlin, Gaussian, binary, and uniform noise algorithms to produce random pixel distributions and organic patterns. It also features a command-line interface that allows users to apply visual effect
Bild is an image processing library in Go that supports procedural noise generation for synthetic textures and various manipulation filters, though it lacks dedicated material map conversion and GPU acceleration features.
Neural Doodle is a collection of neural network tools designed for image upscaling, texture synthesis, and semantic-guided style transfer between visual inputs. It provides a semantic style transfer engine and an example-based image upscaler that increase image resolution by referencing visual details from a target style example. The project includes a neural texture synthesizer for creating seamless bitmap textures and repeating patterns from a single input style image. It also functions as an image generation tool capable of transforming simple sketches and photos into detailed artwork. Th
This repository provides neural network tools for texture synthesis, image generation, and style transfer, making it a fitting utility for procedural texture creation despite lacking broader texture map conversion features.
Armortools is a 3D PBR texture painting suite and mesh texture workflow tool. It provides a system for painting physically based rendering materials directly onto 3D meshes using a combination of layer and mask support, a GPU-accelerated texture baker for extracting geometry data from high-polygon models, and a node-based material editor for creating procedural textures. The software features integrated neural network tools for AI texture authoring, allowing the generation of PBR maps from text prompts, image-based material extraction, and texture upscaling via local nodes. It also implements
Armortools is a 3D texture painting and material authoring suite that provides procedural node-based generation, GPU acceleration, and texture map conversions, fitting the media texture processing domain well despite being a standalone application rather than a lower-level library.
WaveFunctionCollapse is a procedural generation engine that creates complex, non-repeating patterns by treating spatial arrangement as a constraint satisfaction problem. It functions as a stochastic solver that derives output structures from a single input example, ensuring that every element placed within a grid satisfies specific adjacency requirements relative to its neighbors. The system distinguishes itself by using an entropy-driven approach to grid collapse, where it iteratively selects the cell with the fewest remaining possibilities to trigger a cascade of logical updates. By decompo
WaveFunctionCollapse is a procedural generation engine that creates textures and patterns from a sample using constraint satisfaction and entropy-driven solving, though it focuses on grid-based synthesis rather than general surface map conversion.