Goku: Generates detailed and consistent videos, ideal for creating commercials with detailed characters and objects.

General Introduction

Goku is a federated image and video generation model based on stream transform technology designed to achieve industry-grade performance. It integrates advanced high-quality visual generation techniques, including fine-grained data curation, model design, and stream transform formulation.Goku's key contributions include high-quality fine-grained image and video data curation, innovative use of stream transforms to enhance the interaction of video and image markers, and excellent qualitative and quantitative performance in image and video generation tasks.Goku supports a wide range of generative tasks including text-to video generation, image-to-video generation, and text-to-image generation. Goku performs well in major benchmarks, achieving top scores.

Preview example: https://saiyan-world.github.io/goku/

Function List

• 🎬 Text to Video Generation: Convert text descriptions into high-quality videos.
• 🖼️ Image to Video Generation: Dynamize static images to generate video content.
• 🎨 Text-to-Image Generation: Generate high-quality images based on text descriptions.
• 📊 High-quality data collation: Provides fine-grained organization of image and video data.
• 🔄 Innovative Flow Conversion Technology:: Enhanced interaction between video and image markers.
• 🌟 superior performance: Excellent performance in image and video generation tasks.

Using Help

Installation process

1. clone warehouse:

   git clone https://github.com/Saiyan-World/goku.git
   

2. Go to the project directory:

   cd goku
   

3. Installation of dependencies:

   pip install -r requirements.txt
   

Guidelines for use

1. Text to Video Generation:
   • Input text description: Enter a text description in the input box, e.g. "A man walking on the beach".
   • Selecting Generation Parameters: Select the video resolution, duration, and other parameters.
   • Click Generate: Click the "Generate Video" button and the model will generate a video according to the text description.
2. Image to Video Generation:
   • Upload images: Click the "Upload Image" button and select a still image to convert to video.
   • Selecting Generation Parameters: Select the video resolution, duration, and other parameters.
   • Click Generate: Click the "Generate Video" button and the model will generate a video based on the uploaded image.
3. Text-to-Image Generation:
   • Input text description: Enter a text description in the input box, e.g. "A butterfly in a bush".
   • Selecting Generation Parameters: Select parameters such as the resolution of the image.
   • Click Generate: Click on the "Generate Image" button and the model will generate an image according to the text description.

Advanced Features

• Data organization and labelling: Provide high-quality image and video data organization services to help users with data annotation and management.
• Performance Evaluation: Provide detailed performance evaluation reports to help users understand how the model performs in different tasks.

caveat

• hardware requirement: In order to ensure the generation effect, it is recommended to use hardware devices with powerful computing capabilities, such as high-performance GPUs.
• parameterization: Users can adjust the generation parameters according to actual needs to get the best generation results.

Generate Video Features

The Goku project is characterized by its stream transformation-based technology that enables enhanced interaction between video and image markers to generate high-quality images and videos. Specifically, the Goku project has the following features:

1. High-quality fine-grained data collation: The Goku project finely organizes high-quality image and video data, which provides a solid foundation for generating high-quality output.
2. Innovative flow conversion technology: For the first time, the Goku project uses the stream transformation technique, which enables better interaction between video and image markers to enhance generation.
3. Excellent performance: The Goku project excels in image and video generation tasks, leading in both qualitative and quantitative performance.
4. Multiple generation task support: The Goku project supports text-to-video, image-to-video and text-to-image generation tasks for a wide range of scenarios.

Applicable Scenarios

The Goku program is suitable for a variety of scenarios, mainly including but not limited to the following:

1. Advertising and marketing: In the field of advertising and marketing, the Goku program generates high-quality videos or images based on copywriting that can be used to advertise and promote products or services.
2. film and television production: In the field of film and television production, the Goku program converts static scripts or subplots into dynamic videos, helping directors and production teams to better present their ideas.
3. Education and training: In the field of education and training, the Goku program can generate relevant videos or images based on the teaching materials to help students better understand and master their knowledge.
4. social media: In the social media space, the Goku project helps users generate interesting videos or images based on text descriptions for sharing and distribution.
5. art: In the field of art creation, the Goku project can generate high-quality videos or images based on the artist's ideas, helping the artist to realize his or her creation.