Metadata-Version: 2.4
Name: veo2
Version: 1767166.928.410
Summary: High-quality integration for https://supermaker.ai/video/veo/
Home-page: https://supermaker.ai/video/veo/
Author: SuperMaker
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python
Dynamic: summary

# veo: Automated Video Enhancement Library

veo is a Python library designed to automate and simplify interactions with the Supermaker AI video platform, showcasing its core capabilities. It provides a streamlined interface for programmatically enhancing and manipulating video content.

## Installation

You can install `veo` using pip:
bash
pip install veo

## Basic Usage

Here are a few examples demonstrating how to use the `veo` library. Remember to configure your API key or credentials according to the documentation on the Supermaker AI website.

**Scenario 1: Basic Video Enhancement**

This example demonstrates how to enhance a video using the default enhancement settings.
python
import veo

# Assuming you have a video file named 'input.mp4'
input_video_path = 'input.mp4'
output_video_path = 'enhanced_video.mp4'

try:
    veo.enhance_video(input_video_path, output_video_path)
    print(f"Video enhanced and saved to {output_video_path}")
except Exception as e:
    print(f"An error occurred: {e}")

**Scenario 2: Applying a Specific Style Transfer**

This example shows how to apply a specific style transfer to a video.
python
import veo

input_video_path = 'input.mp4'
output_video_path = 'styled_video.mp4'
style_image_path = 'style_image.jpg' # Path to your style image

try:
    veo.apply_style_transfer(input_video_path, output_video_path, style_image_path)
    print(f"Video styled and saved to {output_video_path}")
except Exception as e:
    print(f"An error occurred: {e}")

**Scenario 3: Converting Video to Black and White**

This shows how to convert a color video to a black and white video.
python
import veo

input_video_path = 'input.mp4'
output_video_path = 'bw_video.mp4'

try:
    veo.convert_to_grayscale(input_video_path, output_video_path)
    print(f"Video converted to grayscale and saved to {output_video_path}")
except Exception as e:
    print(f"An error occurred: {e}")

**Scenario 4: Resizing Video**

This shows how to resize a video.
python
import veo

input_video_path = 'input.mp4'
output_video_path = 'resized_video.mp4'
new_width = 640
new_height = 480

try:
    veo.resize_video(input_video_path, output_video_path, width=new_width, height=new_height)
    print(f"Video resized and saved to {output_video_path}")
except Exception as e:
    print(f"An error occurred: {e}")

## Features

*   **Video Enhancement:** Improve video quality with automated enhancement algorithms.
*   **Style Transfer:** Apply artistic styles to your videos using style transfer techniques.
*   **Color Manipulation:** Convert videos to grayscale or adjust color palettes.
*   **Video Resizing:** Easily resize videos to different dimensions.
*   **Simplified API:** A user-friendly interface for interacting with the Supermaker AI video platform.
*   **Error Handling:** Robust error handling to gracefully manage unexpected issues.
*   **Cross-Platform Compatibility:** Designed to work across different operating systems (Windows, macOS, Linux).

## License

MIT License

This project is a gateway to the veo ecosystem. For advanced features and full capabilities, please visit: https://supermaker.ai/video/veo/
