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https://github.com/janclemenslab/napari-video
Napari plugin for working with video files.
https://github.com/janclemenslab/napari-video
napari-plugin opencv video
Last synced: about 1 month ago
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Napari plugin for working with video files.
- Host: GitHub
- URL: https://github.com/janclemenslab/napari-video
- Owner: janclemenslab
- License: mit
- Created: 2020-12-14T17:05:41.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-08-23T12:13:38.000Z (about 2 years ago)
- Last Synced: 2024-09-28T00:22:00.474Z (about 2 months ago)
- Topics: napari-plugin, opencv, video
- Language: Jupyter Notebook
- Homepage:
- Size: 26.4 KB
- Stars: 12
- Watchers: 3
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# napari-video
[](https://napari-hub.org/plugins/napari_video)
Napari plugin for working with videos.
Relies on [pyvideoreader](https://pypi.org/project/pyvideoreader/) as a backend which itself uses [opencv](https://opencv.org) for reading videos.
## Installation
```shell
pip install napari[all] napari_video
```
## Usage
From a terminal:
```shell
napari video.avi
```
Or from within python:
```shell
import napari
from napari_video.napari_video import VideoReaderNP
path='video.mp4'
vr = VideoReaderNP(path)
with napari.gui_qt():
viewer = napari.view_image(vr, name=path)
```
## Internals
`napari_video.napari_video.VideoReaderNP` exposes a video with a numpy-like interface, using opencv as a backend.
For instance, open a video:
```python
vr = VideoReaderNP('video.avi')
print(vr)
```
```
video.avi with 60932 frames of size (920, 912, 3) at 100.00 fps
```
Then
- `vr[100]` will return the 100th frame as a numpy array with shape `(902, 912, 3)`.
- `vr[100:200:10]` will return 10 frames evenly spaced between frame number 100 and 200 (shape `(10, 902, 912, 3)`).
- Note that by default, single-frame and slice indexing return 3D and 4D arrays, respectively. To consistently return 4D arrays, open the video with `remove_leading_singleton=False`. `vr[100]` will then return a `(1, 902, 912, 3)` array.
- We can also request specific ROIs and channels. For instance, `vr[100:200:10,100:400,800:850,1]` will return an array with shape `(10, 300, 50, 1)`.