Generate text descriptions from images
a tiny vision language model
Score image-text similarity using CLIP or SigLIP models
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Generate captions for images
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Generate a caption for an image
Generate image captions from images
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Generate text from an uploaded image
Label text in images using selected model and threshold
Generate captions for images in various styles
CLIP Interrogator 2 is an advanced tool designed for generating text descriptions from images. It leverages cutting-edge AI technology to analyze visual content and produce accurate and relevant captions. Built on the principles of the CLIP (Contrastive Language–Image Pretraining) model, it offers a powerful solution for image-to-text tasks, making it ideal for applications in content creation, accessibility, and more.
• Multi-Model Support: Works seamlessly with multiple CLIP variants for diverse use cases.
• Batch Processing: Generate captions for multiple images simultaneously.
• Customizable Prompts: Fine-tune prompts for specific outputs.
• Integration Capabilities: Easily integrates with other tools and workflows.
• Efficiency: Optimized for fast and accurate results.
• Cross-Modal Search: Enables searching for images based on text or vice versa.
For example:
from clip_interrogator import interrogator
# Initialize interrogator
interrogate = interrogator.Interrogator()
# Generate caption
caption = interrogate("path_to_your_image.jpg")
print(caption)
What models does CLIP Interrogator 2 support?
CLIP Interrogator 2 supports a variety of CLIP models, including ViT-B/32, RN50, and more, depending on your specific needs.
How accurate are the generated captions?
The accuracy of captions depends on the quality of the input image and the chosen model. CLIP Interrogator 2 is designed to provide highly accurate descriptions.
Can I use CLIP Interrogator 2 for commercial projects?
Yes, CLIP Interrogator 2 is suitable for both personal and commercial use, depending on the licensing terms of the underlying models.