📷Author Automates 35mm Film Scanning Pipeline with AI
AI saves hours of manual film scanning
TL;DR
An author automated their 35mm film scanning pipeline using AI, saving hours of manual work. They developed tools for scanning, processing, and indexing, with VueScan and LaMa for dust removal. The system now drafts tags for each frame in about 5 seconds.
An author automated their 35mm film scanning pipeline, saving hours of manual work. They started by scanning a roll of 36 photos in 4 hours, then looked for ways to streamline the process. Using VueScan and LaMa for dust removal, they developed a full suite of tools for scanning, processing, and indexing. The system now drafts tags for each frame in about 5 seconds, making it easier to search and share images. This automation reduces the time spent on manual tasks, improving efficiency for photographers and archivists working with film.
Key Points
Author spent 4 hours scanning a roll of 36 photos and completing edits
Developed a full suite of tools for scanning, processing, and indexing
Used LaMa to fill in dust spots, setting a custom threshold for review
Metadata indexing system drafts tags for each frame in about 5 seconds
Author uses Cloudflare to upload images to an R2 bucket for sharing
Why It Matters
Photographers and archivists working with 35mm film can save hours of manual work by automating their scanning pipeline. The author's system, using VueScan and LaMa for dust removal, drafts tags for each frame in about 5 seconds, making it easier to search and share images. This automation significantly improves efficiency for anyone dealing with large film archives.
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