VideoDataAnimation is a Python library designed for creating synchronized visualizations of video data and corresponding time-series data. It allows users to visualize changes in data alongside video frames, making it ideal for applications in research, data analysis, and educational purposes where visual context is crucial.
- Synchronized Visualization: Seamlessly integrate video playback with real-time data plots, ensuring synchronized visualizations that enhance understanding and analysis.
- Interactive Plotting: Utilize interactive plotting features to zoom, pan, or hover over data points for detailed inspection, providing a deeper analysis of the data alongside video content.
- Flexible Data Integration: Easily integrate various data sources by supporting multiple data formats, including CSV, Excel, and direct data frames, facilitating hassle-free data visualization.
- Region of Interest Cropping: Focus on specific areas within your videos by defining regions of interest, allowing for detailed analysis of targeted video segments.
- Customizable Visual Styles: Personalize your visualizations with customizable plot styles, including color schemes, line styles, and marker options, to match your presentation or branding requirements.
- Dynamic Windowing: Adjust the data viewing window dynamically, either by specifying a fixed number of data points or by setting a time window, to focus on specific segments of your data over time.
- Annotation and Labeling: Enhance your visualizations with annotations and labels, providing context and insights directly on your plots and video frames, making complex data more accessible.
- Multiple Export Formats: Export your synchronized video and data visualizations to a variety of formats such as MP4, AVI, GIF, or even as interactive HTML files, ensuring compatibility across different platforms and devices.
- Batch Processing Support: Automate the processing of multiple video and data pairs with batch processing capabilities, saving time and ensuring consistency across large datasets.
- Extensive Documentation and Examples: Get up and running quickly with comprehensive documentation, including detailed setup instructions, usage examples, and troubleshooting tips.
- Community and Support: Join an active community of users and contributors for support, to share ideas, and to collaborate on new features, making VideoDataAnimation not just a tool but a growing ecosystem.
To install VideoDataAnimation, simply use pip:
pip install VideoDataAnimation
from VideoDataAnimation import VideoDataAnimation
Initialize the VideoDataAnimation with your video and CSV file paths··
vda = VideoDataAnimation(
csv_path='./comp_APP.csv',
video_path='./comp_APP.avi',
labels=['$m_{x}$', '$m_{y}$', '$m_{z}$'],
crop_region=(145, 300, 1000, 400),
window_size=None)
Load the data, set up video capture, and prepare the plot
vda.load_data()
vda.setup_video_capture()
vda.setup_plot()
Save the animation to an MP4 file, adjusting the playback speed with the slow_factor··
vda.save_animation('mp4', slow_factor=2)
Release resources after saving the animation··
vda.release_resources()
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