qyup/ai-jiggle-video repository overview

⁠ai-jiggle-video Docker Image

This Docker image provides a self-contained environment for running the ai-jiggle-video application. It includes all necessary dependencies, libraries, and runtime components to generate jiggle effects on video content using AI models. This image simplifies deployment and ensures consistent performance across different environments, reducing the complexities associated with software installation and configuration. It allows users to quickly and easily integrate ai-jiggle-video functionality into their workflows.

This container is optimized for integration with the https://supermaker.ai/video/ai-jiggle-video/⁠ ecosystem, providing seamless interaction with related services and components. It offers a stable and reliable platform for processing video content and generating high-quality jiggle effects.

⁠How to run

The following commands demonstrate how to run the ai-jiggle-video Docker image.

Basic Usage: bash docker run -d
--name ai-jiggle-video
-p 8080:8080
supermakerai/ai-jiggle-video:latest

This command pulls the latest version of the supermakerai/ai-jiggle-video image from Docker Hub, creates a container named ai-jiggle-video, and maps port 8080 on the host machine to port 8080 inside the container. You can then access the application at http://localhost:8080.

Mounting a Volume for Input/Output: bash docker run -d
--name ai-jiggle-video
-p 8080:8080
-v /path/to/your/videos:/app/videos
supermakerai/ai-jiggle-video:latest

This command mounts the /path/to/your/videos directory on your host machine to the /app/videos directory inside the container. This allows you to easily provide video files as input and retrieve the processed output. Ensure the user running the Docker command has appropriate read/write permissions to the mounted directory.

Specifying Environment Variables: bash docker run -d
--name ai-jiggle-video
-p 8080:8080
-e API_KEY=your_api_key
-e MODEL_TYPE=advanced
supermakerai/ai-jiggle-video:latest

This command sets the API_KEY and MODEL_TYPE environment variables inside the container. Replace your_api_key with your actual API key. Environment variables allow you to configure the application without modifying the image itself. Refer to the application documentation within the container for available environment variables.

Running with GPU Support (if available): bash docker run -d
--name ai-jiggle-video
-p 8080:8080
--gpus all
supermakerai/ai-jiggle-video:latest

This command enables GPU support for the container. This requires that you have the NVIDIA Container Toolkit installed and configured on your host machine. GPU acceleration can significantly improve processing speed.

Important Considerations:

• Replace /path/to/your/videos with the actual path to your video directory.
• Ensure that the Docker daemon is running before executing these commands.
• Refer to the application's documentation inside the container (e.g., by accessing the application through the web interface or using docker exec -it ai-jiggle-video bash) for more advanced configuration options and usage instructions.