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AI models struggle to accurately count fabric threads from smartphone photos

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method for measuring fabric thread density using smartphone photos taken through a pick glass, aiming for a $\pm$5% accuracy tolerance. They benchmarked several AI models, including Molmo2-4B and GPT-6.1-sol, against human annotators and a spectral counter (PG-Lattice). While no method achieved the desired accuracy, the tuned Molmo2-4B model performed comparably to GPT-6.1-sol, both outperforming non-expert human counts. The study highlights that image quality, particularly reliability across multiple photos, is crucial for accurate thread counting, and current generative enhancements do not consistently improve results. AI

IMPACT Highlights limitations of current AI models in precise visual measurement tasks and the importance of image quality for reliability.

RANK_REASON Academic paper detailing a new method and benchmarking AI models on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI models struggle to accurately count fabric threads from smartphone photos

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34 / 100
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Academic paper detailing a new method and benchmarking AI models on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Anoubhav Agarwaal ·

    Image Quality and the Reliability of Fabric-Density Measurement: Counting Threads from Smartphone Photos Through a Pick Glass

    arXiv:2611.13200v1 Announce Type: new Abstract: Thread density, the threads per inch along and across a woven fabric, is a basic specification that buyers check whenever fabric is sold. Without laboratory instruments, inspectors count it slowly, by eye, through a pick glass, a fo…

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