lllyasviel / lllyasviel/ControlNet
[Feature]: Please use headless package of opencv-python
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- Dominant language
- Python
- Stars
- 34.1k
- Forks
- 3k
- PR merge metrics
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Description
### Feature description
[opencv-contrib-python-headless](https://pypi.org/project/opencv-contrib-python-headless/) and [opencv-python-headless](https://pypi.org/project/opencv-python-headless/) are drop-in replacements for _opencv-contrib-python_ and _opencv-python_ but without Qt dependencies. This makes it easier to run on minimal server environments, and if glib can't be installed without root.
> b. Packages for server (headless) environments (such as Docker, cloud environments etc.), no GUI library dependencies
>
> These packages are smaller than the two other packages above because they do not contain any GUI functionality (not compiled with Qt / other GUI components). This means that the packages avoid a heavy dependency chain to X11 libraries and you will have for example smaller Docker images as a result. You should always use these packages if you do not use cv2.imshow et al. or you are using some other package (such as PyQt) than OpenCV to create your GUI.
>
> Option 3 - Headless main modules package: pip install opencv-python-headless
> Option 4 - Headless full package (contains both main modules and contrib/extra modules): pip install opencv-contrib-python-headless (check contrib/extra modules listing from [OpenCV documentation](https://docs.opencv.org/master/))
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no repository files or tests. Start by locating the OpenCV dependency declarations, then check the installation and relevant server or Docker workflows. Done means the appropriate headless OpenCV package is used without breaking the project’s installation or tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- opencv, python
- Domain
- devops
- Issue type
- Feature
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100