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I Built a CLI That Detects 3D Print Defects from a Single Photo — No ML Required

DEV Community·keeper·21 days ago
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A few weeks ago, I launched SupportSage (AI-optimized support structures) and FilamentDB (filament parameter database). Together they covered pre-print optimization: what settings to use and how to slice . But the feedback loop was incomplete. You optimize, slice, print — and then what? How do you know if the print is actually good? You eyeball it. Maybe post to r/3Dprinting and ask "what's wrong with my print?". I wanted a programmatic answer. One CLI command, one photo. Meet Printsight 🖨️👁️ pip install https://github.com/bossman-lab/printsight/releases/download/v0.1.0/printsight-0.1.0-py3-none-any.whl printsight my_print.jpg Enter fullscreen mode Exit fullscreen mode The Three Detectable Defects Printsight v0.1 detects three of the most common print quality issues, all with pure OpenCV — no ML, no training data, no GPU: 1. Stringing (Score 0.0–1.0) Stringing happens when molten plastic oozes during travel moves, leaving thin wisps across your print.…

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