Using Computer Vision to Accelerate Microbiology Research and Combat Antibiotic Resistance

Michael Shamash, a graduate student at McGill University, developed OnePetri, an innovative iOS app designed to automate the labor-intensive task of counting bacteriophage plaques on Petri dishes, significantly accelerating microbiological assays through computer vision and AI. Utilizing Roboflow's annotation and image processing tools, Shamash successfully transitioned from concept to a working app within five weeks, employing two YOLOv5s object detection models for precise plaque identification. OnePetri operates entirely on-device, enabling its use without internet access, and the app, along with its source code and trained models, is freely available to researchers, supporting further development and collaboration. By automating this previously manual process, OnePetri aims to streamline bacteriophage research and combat antibiotic-resistant infections, with future enhancements planned to expand its capabilities and platform accessibility.

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