| Name | FrameStory JSON |
| Version |
0.1.3
JSON |
| download |
| home_page | https://github.com/chigwell/FrameStory |
| Summary | A Python package for creating video descriptions by analyzing and extracting significant frames. |
| upload_time | 2024-04-07 11:45:25 |
| maintainer | None |
| docs_url | None |
| author | Eugene Evstafev |
| requires_python | >=3.6 |
| license | None |
| keywords |
|
| VCS |
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| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
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No Travis.
|
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No coveralls.
|
[](https://badge.fury.io/py/frame_story)
[](https://opensource.org/licenses/MIT)
[](https://pepy.tech/project/frame_story)
# Frame Story
`FrameStory` is a Python package designed for extracting and describing significant frames from videos. Leveraging state-of-the-art machine learning models, it can provide detailed descriptions of video content, making it a powerful tool for content analysis, accessibility, and summarization.
## Installation
To install `FrameStory`, you can use pip:
```bash
pip install FrameStory
```
## Usage
Using `FrameStory` is straightforward. Below are examples demonstrating how to extract and describe significant frames from videos with various parameters.
### Describing Video by URL
```python
from frame_story.video_describer import VideoDescriber
video_url = "https://example.com/video.mp4"
describer = VideoDescriber(show_progress=True)
descriptions = describer.get_video_descriptions(video_url=video_url)
print(descriptions)
```
### Describing Video from Local Path
```python
video_path = "/path/to/your/video.mp4"
describer = VideoDescriber(show_progress=True, max_tokens=50)
descriptions = describer.get_video_descriptions(video_path=video_path)
print(descriptions)
```
### Customizing Extraction Threshold
The `extract_significant_frames` method allows you to customize the threshold for what constitutes a "significant" change between frames.
```python
video_url = "https://example.com/video.mp4"
describer = VideoDescriber(threshold=25000)
descriptions = describer.get_video_descriptions(video_url=video_url)
print(descriptions)
```
These examples demonstrate the versatility of `frame_story` in processing videos from different sources and with various levels of detail in descriptions.
## Features
- Extraction of significant frames from videos for detailed analysis.
- Generation of descriptive text for each significant frame using state-of-the-art image captioning models.
- Support for videos from URLs or local file paths.
- Customizable settings for progress display, description length, and frame extraction threshold.
- Easy to integrate into Python projects for content analysis, summarization, and accessibility applications.
## Contributing
Contributions, issues, and feature requests are welcome! Feel free to check the [issues page](https://github.com/chigwell/frame_story/issues).
## License
This project is licensed under the [MIT License](https://choosealicense.com/licenses/mit/).
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