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ePillID

Benchmark for pill identification

ePillID

ePillID is a benchmark for developing and evaluating computer vision models for pill identification. The ePillID benchmark is designed as a low-shot fine-grained benchmark, reflecting real-world challenges for developing image-based pill identification systems. The characteristics of the ePillID benchmark include:Reference and consumer images: The reference images are taken with controlled lighting and backgrounds, and with professional equipment. The consumer images are taken with real-world settings including different lighting, backgrounds, and equipment. For most of the pills, one image per side (two images per pill type) is available from the NIH Pillbox dataset.Low-shot and fine-grained setting: 13k images representing 9804 appearance classes (two sides for 4902 pill types). For most of the appearance classes, there exists only one reference image, making it a challenging low-shot recognition setting.

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IEEE
https://www.ieee.org
Task
Image Classification
Annotation Types
Classification Tags
4902
Items
9804
Classes
13000
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
Research Only
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