sora-ai-video

A Rust crate designed to simplify the process of generating and manipulating video content powered by AI. This library provides tools for video creation, editing, and analysis, enabling developers to integrate advanced video capabilities into their applications.

Installation

Add the following line to your Cargo.toml file under the [dependencies] section: toml sora-ai-video = "0.1.0" # Replace with the actual version number

Usage Examples

Here are a few examples demonstrating how to use the sora-ai-video crate:

1. Generating a Video from Text Prompt:

This example shows how to generate a short video clip based on a text description. rust use sora_ai_video::video_generator::VideoGenerator;

#[tokio::main] async fn main() -> Result<(), Box> { let generator = VideoGenerator::new(); let prompt = "A cat playing with a ball of yarn in a sunny room."; let video_data = generator.generate_video_from_text(prompt).await?;

// Save the video data to a file (e.g., video.mp4)
std::fs::write("video.mp4", video_data)?;

println!("Video generated successfully!");
Ok(())

}

2. Extracting Frames from a Video:

This example demonstrates how to extract individual frames from an existing video file. rust use sora_ai_video::video_processor::VideoProcessor;

fn main() -> Result<(), Box> { let processor = VideoProcessor::new(); let video_path = "input.mp4"; // Replace with the path to your video file let output_dir = "frames";

std::fs::create_dir_all(output_dir)?;
processor.extract_frames(video_path, output_dir)?;

println!("Frames extracted successfully!");
Ok(())

}

3. Applying a Style Transfer to a Video:

This example illustrates how to apply a specific style (e.g., painting style) to an existing video. This requires a pre-trained style transfer model. rust use sora_ai_video::video_editor::VideoEditor;

#[tokio::main] async fn main() -> Result<(), Box> { let editor = VideoEditor::new(); let input_video = "input.mp4"; // Replace with the path to your input video let style_image = "style.jpg"; // Replace with the path to your style image let output_video = "output.mp4";

editor.apply_style_transfer(input_video, style_image, output_video).await?;

println!("Style transfer applied successfully!");
Ok(())

}

4. Analyzing Video Content for Object Detection:

This example shows how to analyze a video and detect objects within the frames. This functionality depends on an integrated object detection model. rust use sora_ai_video::video_analyzer::VideoAnalyzer;

#[tokio::main] async fn main() -> Result<(), Box> { let analyzer = VideoAnalyzer::new(); let video_path = "input.mp4"; // Replace with the path to your video file

let object_detections = analyzer.detect_objects(video_path).await?;

println!("Object detections: {:?}", object_detections);
Ok(())

}

Feature Summary

The sora-ai-video crate provides the following key features:

• Video Generation: Create videos from text prompts using AI models.
• Video Processing: Extract frames, manipulate video files, and perform basic editing.
• Style Transfer: Apply artistic styles to videos using pre-trained models.
• Video Analysis: Analyze video content for object detection and other insights.
• Easy Integration: Designed for seamless integration into existing Rust projects.

License

MIT This crate is part of the sora-ai-video ecosystem. For advanced features and enterprise-grade tools, visit: https://supermaker.ai/video/sora-ai-video/