This project is a Python-based plugin for Krita that provides a streamlined interface for generating images with AI. It has gained significant traction with 1889 stars and 45 forks. The project has a high level of activity with 253 commits across 6 branches.
The project seems to be in active development with the last push made recently. It has 46 open issues, many of which are recent, indicating an engaged user base. The project is licensed under the GNU General Public License v3.0.
A significant number of issues relate to installation problems, server connection errors, and hardware requirements. Some users have reported problems with specific features, such as inpainting and live mode. There are also several feature requests and questions about the plugin's functionality.
The project is likely to continue to grow and improve, given the active development and high level of community engagement. However, the high number of open issues indicates that there may be some challenges to overcome, particularly around installation and hardware compatibility.
Krita AI Diffusion is an active project with a high volume of recent issues. The majority of these issues are related to installation problems, feature requests, and usage questions. There are no major disputes or anomalies, but several users report difficulties with specific hardware configurations and operating systems.
The project is actively maintained, with the maintainer responding promptly to issues. The project appears to be in a healthy state, with ongoing development and user engagement. The maintainer is receptive to feature requests and provides detailed responses to user queries. The project could benefit from improved installation guides and troubleshooting documentation to address the recurring installation issues.
The project is actively maintained with recent pull requests (PRs) addressing new features and bug fixes. The project has a total of 3 PRs, with 1 currently open and 2 already closed and merged.
There is one open PR titled "Support Apple GPU (MPS)" which aims to add support for Apple silicon GPU (MPS) backend. The PR is fresh, created 0 days ago.
Two PRs have been closed and merged recently:
PR #9 titled "Add new style and delete style buttons" was merged 61 days ago. This PR added the functionality to create and delete styles.
PR #6 titled "Add https and wss support" was merged 63 days ago. This PR added support for https and wss connections. There were some issues noted with the connection when extra_model_paths.yaml was configured to take models from a specific folder. However, these issues seem to have been resolved before the PR was merged.
No notable issues, problems, disputes, or anomalies have been identified based on the provided information. The project appears to be progressing smoothly with active contributions and regular updates.
The Acly/krita-ai-diffusion project is a Python-based plugin for Krita, providing a streamlined interface for generating images with AI. The project has a significant user base, as indicated by 1889 stars and 45 forks. It has a steady development pace with 253 commits across 6 branches.
The project has 46 open issues, suggesting some ongoing challenges or enhancements. The project's README provides a comprehensive guide on its features, installation, and usage, with a dedicated section for troubleshooting common issues.
The plugin offers a range of features including inpainting, outpainting, image generation, refinement, live painting, control, resolutions, upscaling, job queue, history, strong defaults, and customization. It supports Windows, Linux, and MacOS (experimental), with hardware support for NVIDIA GPU, AMD GPU, CPU, and Cloud GPU.
Despite its robust features, the project has some limitations. It recommends a powerful graphics card with at least 6 GB VRAM for local use, which may not be available to all users. Also, the MacOS support is still experimental.
The project is licensed under the GNU General Public License v3.0, promoting open-source use and modification. The plugin uses several technologies for image generation, including Stable Diffusion, ComfyUI, ControlNet, and IP-Adapter.
Overall, the project appears to be in active development with a strong user base and a comprehensive set of features. However, the number of open issues suggests there may be ongoing challenges or areas for improvement.
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