This is a simplified guide to an AI model called Batch-Image-Captioning maintained by Fofr. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
The batch-image-captioning model developed by fofr processes multiple images to generate detailed captions using advanced language models like GPT-4, Claude, and Gemini. This versatile tool fills a gap between basic image captioning models like clip prefix caption and more complex vision-language models like instructblip.
Model inputs and outputs
The model takes a ZIP archive containing images and processes them in batch, with options to customize the captioning process through prompts and image preprocessing settings. It outputs organized caption files that match the original image names.
Inputs
- ZIP archive containing images (png, jpg, jpeg, webp)
- Caption prefix/suffix for customizing output format
- Image resizing options to optimize processing costs
- API keys for OpenAI, Anthropic, or Google
- Custom prompts to guide caption generation
- Model selection from GPT-4, Claude-3, or Gemini variants
Outputs
- ZIP file containing caption files matching image names
- CSV summary of all generated captions
Capabilities
The system processes image batches thro...
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