VideoDataAnimation

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.

Features

• 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.

Installation

To install VideoDataAnimation, simply use pip:

pip install VideoDataAnimation

Quick Start

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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