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araviq6-2.1.1
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مشاهده بیشترتوضیحات
Package for converting QVideoFrame to NDArray with Qt6
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | araviq6-2.1.1 |
| نام | araviq6 |
| نسخه کتابخانه | 2.1.1 |
| نگهدارنده | ['Jisoo Song'] |
| ایمیل نگهدارنده | ['jeesoo9595@snu.ac.kr'] |
| نویسنده | Jisoo Song |
| ایمیل نویسنده | jeesoo9595@snu.ac.kr |
| آدرس صفحه اصلی | https://github.com/JSS95/araviq6 |
| آدرس اینترنتی | https://pypi.org/project/araviq6/ |
| مجوز | MIT |
# AraViQ6 - NDArray-based Video processing with Qt6
[](https://badge.fury.io/py/AraViQ6)
[](https://pypi.org/project/araviq6/)
[](https://github.com/JSS95/araviq6/actions/workflows/ci.yml)
[](https://araviq6.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/JSS95/araviq6/blob/master/LICENSE)
AraViQ6 is a Python package which integrates NDArray-based image processing with video pipeline of Qt6.
It provides:
- QVideoFrame processor based on array processing
- Converters between NDArray and QVideoFrame
- Convenience classes and widgets for array displaying
The following Qt bindings are supported:
- [PySide6](https://pypi.org/project/PySide6/)
- [PyQt6](https://pypi.org/project/PyQt6/)
# How to use
There are two ways to use AraViQ6; using QVideoFrame-based pipeline, or using NDArray-based pipeline.
## Frame-based pipeline
Frame-based pipeline is a high-level approach that works well with Qt Multimedia scheme.
<div align="center">
<img src="https://github.com/JSS95/araviq6/raw/master/doc/source/_images/frame-pipeline.jpg"/><br>
QVideoFrame pipeline with AraViQ6
</div>
Frame-based pipeline consists of:
1. `VideoFrameWorker`
2. `VideoFrameProcessor`
QVideoFrame comes from and goes to Qt6's `QVideoSink`. AraViQ6's
`VideoFrameWorker` converts QVideoFrame to numpy array, performs processing, and sends the results to downstream in both QVideoFrame and NDArray. User may subclass the worker to define own processing.
`VideoFrameProcessor` wraps the worker and provides API around it.
Worker is mulithreaded in the processor.
## Array-based pipeline
Array-based pipeline is a low-level approach.
It can be useful when third-party package provides video frame in numpy array format.
<div align="center">
<img src="https://github.com/JSS95/araviq6/raw/master/doc/source/_images/array-pipeline.jpg"/><br>
NDArray pipeline with AraViQ6
</div>
Array-based pipeline consists of:
1. `FrameToArrayConverter`
2. `ArrayWorker`
3. `ArrayProcessor`
4. `ArrayToFrameConverter`
`FrameToArrayConverter` and `ArrayToFrameConverter` performs conversion between frame pipeline and array pipeline.
To retain the metadata (e.g., timestamp) of QVideoFrame, these classes includes the original frame for the array.
`ArrayWorker` performs processing on incoming array and sends the result to downstream in NDArray. User may subclass the worker to define own processing.
`ArrayProcessor` wraps the worker and provides API around it.
Worker is mulithreaded in the processor.
## Convenicence classes
AraViQ6 also provides various convenience classes to make building the pipeline easier.
The following classes help setting array pipeline with the video source and the display.
- `NDArrayVideoPlayer`
- `NDArrayMediaCaptureSession`
- `NDArrayLabel`
The following classes are plug-and-play widgets where user can process the video with minimal boilerplate.
- `PlayerProcessWidget`
- `CameraProcessWidget`
# Examples
Use cases are provided in [examples](https://github.com/JSS95/araviq6/tree/master/doc/source/examples) directory.
They can be found in documentation as well.
# Installation
Before you install, be careful for other Qt-dependent packages installed in your environment.
For example, non-headless OpenCV-Python modifies the Qt dependency thus can make other Qt bindings unavailable.
`araviq6` can be installed using `pip`.
```
$ pip install araviq6
```
# Documentation
AraViQ6 is documented with [Sphinx](https://pypi.org/project/Sphinx/).
Documentation can be found on Read the Docs:
> https://araviq6.readthedocs.io/
If you want to build the document yourself, clone the source code and install with `[doc]` option.
Go to `doc` directory and build the document.
```
$ pip install araviq6[doc]
$ cd doc
$ make html
```
Document will be generated in `build/html` directory. Open `index.html` to see the central page.
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| >=1.10 | qimage2ndarray |
| - | numpydoc |
| - | sphinx |
| - | sphinx-tabs |
| - | sphinx-rtd-theme |
| - | typing-extensions |
| - | numpydoc |
| - | mypy |
| - | sphinx-tabs |
| - | flake8 |
| - | sphinx |
| - | sphinx-rtd-theme |
| - | pytest-xvfb |
| - | pytest |
| - | black |
| - | pytest-qt |
| - | opencv-python-headless |
| - | typing-extensions |
| - | black |
| - | flake8 |
| - | mypy |
| - | opencv-python-headless |
| - | pytest |
| - | pytest-qt |
| - | black |
| - | flake8 |
| - | mypy |
| - | opencv-python-headless |
| - | pytest |
| - | pytest-qt |
| - | pytest-xvfb |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl araviq6-2.1.1:
pip install araviq6-2.1.1.whl
نصب پکیج tar.gz araviq6-2.1.1:
pip install araviq6-2.1.1.tar.gz