Colorflow: Colorize black-and-white image sequences

Understand the project

Practical overview

Use Colorflow when the task is coloring a sequence of related images and color consistency for recurring characters or objects matters.

Developers exploring inference workflows for image-sequence colorization.
Artists and production teams working with cartoon or comic sequences that need recurring characters and objects to retain consistent colors.

Colorize black-and-white frames using relevant color references.
Maintain character and object color identity across an image sequence.
Explore a local Gradio interface or the linked Hugging Face demo for the project.

Before you choose

The repository links to a Hugging Face demo and provides instructions for running the interface locally.

The method is organized into retrieval-augmented, in-context colorization and guided super-resolution stages.
The documented local setup uses Python 3.8.5, Anaconda or Miniconda, pip dependencies and a Gradio interface.
The README says inference code and model weights have been released; it lists training code as a TODO.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Prepare the documented Python environment and start Colorflow’s local interface.

The README describes a running Gradio interface accessible locally at port 7860.

The README documents inference setup and launch, not a training workflow.
For a remote server, the README says to use its IP address or domain instead of localhost; a custom port requires changing server_port in demo.launch() in app.py.

Evidence and transparency

Source record details

Source availability: Active
Sources checked: 17 October 2026
Original website title: TencentARC/ColorFlow · Official homepage title · retained in its source language