chaiNNer-org/chaiNNer

A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.

What it solves

ChaiNNer is a node-based image processing GUI that simplifies the creation of complex, customizable image processing pipelines. It was originally designed for AI upscaling but has evolved into a general-purpose programmatic image processing tool, allowing users to chain together various tasks without needing to write code.

How it works

Users build workflows by dragging and dropping nodes from a selection panel into an editor. Each node represents a specific processing step. Nodes are connected via color-coded handles to ensure compatible connections. The application supports multiple neural network frameworks for AI tasks, including PyTorch, NCNN, ONNX, and TensorRT, and can run on Windows, MacOS, and Linux.

Who it’s for

It is designed for users who want high levels of customization in their image and video processing workflows, particularly those performing AI upscaling or background removal, across different hardware (Nvidia, AMD, Intel, and Apple Silicon).

Highlights

  • Node-Based Workflow: Create complex processing chains by connecting visual nodes rather than writing scripts.
  • Cross-Platform Support: Compatible with Windows, MacOS, and Linux.
  • Harnesses Multiple AI Frameworks: Supports PyTorch, NCNN, ONNX, and TensorRT for optimized inference.
  • Integrated Python: Includes an isolated integrated Python build to simplify installation and dependency management.
  • Batch Processing: Capable of handling folders of images or video files through dedicated loading nodes.

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