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dt0ur.online Image Captioning (ViT-GPT2)
x402
dt0ur.online Image Captioning (ViT-GPT2) is a paid API for AI agents from dt0ur.online, paid per call via x402, $0.15/call, status unknown (last checked 2026-10-03).
Generates descriptive, context-aware natural language captions from a public image URL using ViT-GPT2 vision-language models.
Price / call$0.15
Success—
StatusUnknown
How this service works
Generates descriptive, context-aware natural language captions from image URLs using ViT-GPT2 vision-language models.
Output
A natural language string describing the visual content of the image — generated by a ViT-GPT2 vision-language model — capturing objects, scenes, actions, and contextual details visible in the image.
Example use cases
Auto alt-text for product images
“Generate an accessibility caption for this product photo so I can add it as alt text on our website: https://example-store.com/images/red-running-shoes.jpg”
Social media post captioning
“Write me a natural language description of this photo I want to post — https://mycdn.com/photos/sunset-beach-2024.jpg — so I can use it as a caption or embed it in a blog post.”
Image content audit pipeline
“What's in this image? Give me a plain English description of https://cdn.newssite.com/article-header-photo.jpg so I can tag and categorize it automatically.”
Technical details
Endpoint
POSThttps://dt0ur.online/api/inference/caption?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, automated natural language descriptions of images from public URLs without setting up your own vision model infrastructure. It is well-suited for accessibility alt-text generation, content tagging pipelines, or any workflow where images need to be described in plain English. Prefer this over general-purpose LLM vision calls when you want a dedicated captioning model (ViT-GPT2) optimized specifically for image-to-text description.
Side effects
- Image URL is not publicly accessible or returns a non-200 HTTP status — captioning will fail
- Unsupported image format (e.g. SVG, TIFF, WebP variants) may cause model inference errors
- Very large images may time out or be rejected
- Image contains ambiguous or abstract content — captions may be generic or inaccurate
- Rate limiting or service unavailability if the underlying model host is overloaded
Tags
x402
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