Breaking the Barrier to Entry: Automatic Annotation
One of the longest-running line items for incorporating computer vision into infrastructure has been the hidden labor costs behind labeling tens of thousands of images. Paid annotation and labelling costs roughly $1 per image, with each object requiring 200-300 images per class. IN 2023, the Wall Street Journal reported that "computer vision...is still too expensive for widespread use for self-checkout and inventory management."
For retailers, especially in food manufacturing and QSR, while the results would be staggering - 4X faster checkout, 40% increase in throughput, elimination of waste and slippage, the cost and time has proven prohibitive, beyond experimentation and small samples.
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While using synthetic data and pre-trained models can provide automation for annotation and labeling, accuracy falls between 70-80%, and still requires "light touch" review by engineers checking for false positives and at times frame-by-frame review. Â
Amniscient's platform includes automatic annotation and data collection, without sacrificing accuracy, saving customers hundreds of thousands of dollars in labor and fast tracking timelines to days instead of years.
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