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Joy Caption Batch
Overview :
joy-caption-batch is a programming model that uses the Joytag Caption tool to batch generate descriptive titles for image files. Currently in the Alpha stage, it analyzes image content to generate corresponding text descriptions using artificial intelligence, helping users quickly understand the content of their images. Key advantages of this tool include batch processing capability, support for custom image directories, and LOW_VRAM_MODE support, allowing it to run on devices with low memory. Additionally, detailed installation and usage instructions are provided to help users get started quickly.
Target Users :
The primary target audience includes developers, data scientists, and anyone who needs to batch process images and generate descriptive titles. This tool provides comprehensive installation and usage instructions, making it suitable for programming beginners and enthusiasts alike. Moreover, for users with low VRAM devices, the support for LOW_VRAM_MODE makes this tool even more accessible.
Use Cases
Developers use this tool to batch generate descriptive titles for website images, enhancing search engine optimization (SEO).
Data scientists utilize this tool to generate descriptions for images in datasets for training machine learning models.
Enthusiasts employ this tool to generate interesting descriptions for personal image collections, adding fun to their pictures.
Features
Batch process image files to generate descriptive titles
Support for custom image directories, beyond just the default ./input directory
LOW_VRAM_MODE support for devices with limited GPU memory
Comprehensive installation and usage instructions for swift onboarding
Compatible with Python versions 3.9 to 3.11, excluding 3.12
Requires installation of PyTorch with CUDA support matching your CUDA version
Open-source on GitHub, allowing users to download and modify freely
How to Use
1. Clone the repository to your local machine using the git clone command.
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2. (Optional) Create a virtual environment and activate it.
3. Run pip install -r requirements.txt to install the required dependencies.
4. Install PyTorch that matches your CUDA version.
5. Place the images you want to generate descriptions for into the /input directory, or use the --img_dir parameter to specify a different directory.
6. Run the command python batch.py; the tool will automatically generate descriptive titles for the images in the specified directory.
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