Python
Vision Tagger
Auto-tag and caption images using vision-language models.
4.6 (6.500) 6.5k booked v2.0 · updated recently
Starting from$29
Final price depends on your requirements, integrations and timeline.
Tailored to your stack · NDA available
Python
Vision Tagger
v2.0 · MIT
Overview
Vision Tagger is a lightweight but highly useful computer vision automation script for products that need scalable visual metadata generation. A practical tagging and description engine that analyzes images, generates category labels, detects useful themes, and produces structured outputs improving organization, searchability, moderation readiness, and accessibility. A strong fit for media libraries, ecommerce back offices, UGC platforms, content operations, and DAM systems.
Common use cases
Bulk product taggingNews photo indexingUGC enrichmentArchive restorationDataset labelingContent ops
What's inside
- Tailored to your stackBuilt around your chosen language, framework, providers and deployment target.
- Production-ready patternsStreaming, retries, observability and guardrails baked in for real traffic.
- Multi-provider readySwap between OpenAI, Anthropic, Mistral, Azure or local models with one config.
- Deployment recipesDrop-in guides for Vercel, Fly.io, Cloudflare Workers, Docker and Kubernetes.
- Docs, tests & example appComprehensive docs, integration tests and a reference app to learn from.
- Priority implementation supportDirect help from the team that built it during integration and rollout.
Why developers love it
Fast
Streaming responses and low-latency patterns out of the box.
Readable
Idiomatic, well-commented code your team can own.
Safe
Input validation, retries and cost guardrails included.