High-Res Image Finder
Use cases
Uses Google Vision API reverse image search to find full, partial, and visually similar matches.
Scores results by (new_pixels / original_pixels) × aspect_similarity, filtering for 1.2× minimum improvement.
Features domain-specific rate limiting (3-5s), human-like breaks every 20 requests, and Playwright browser fallback for blocked domains.
Platform
Python script (requires Python 3.x)
Input
Image URLs CSV
Google Vision API credentials
Output
Excel with matched high-res images
Features
- Four match types: full, partial, visually similar, page-based
- Resolution scoring with 1.2× improvement threshold
- Domain-specific rate limiting with random jitter
- Playwright headless browser fallback for blocked sites
- Incremental Excel saves every 100 images
- Concurrent processing (2 workers, thread-safe)
How to use
- 1 Prepare CSV with image URLs
- 2 Configure Google Vision API credentials
- 3 Set MIN_RESOLUTION (default 1000×1000) and MIN_IMPROVEMENT_RATIO (1.2)
- 4 Run script with incremental saves
- 5 Review Excel output with match categories
Want me to run this for you?
I offer this as a managed service. You get the insights without touching the tool.
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