OnePetri Computer Vision Project

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Background Information

This dataset was created by Michael Shamash and contains the images used to train the OnePetri plaque detection model (plaque detection model v1.0).

In microbiology, a plaque is defined as a “clear area on an otherwise opaque field of bacteria that indicates the inhibition or dissolution of the bacterial cells by some agent, either a virus or an antibiotic. Plaques are a sensitive laboratory indicator of the presence of some anti-bacterial factor.”
When working with bacteriophages (phages), viruses which can only infect and kill bacteria, scientists often need to perform the time-intensive monotonous task of counting plaques on Petri dishes. To help solve this problem I developed OnePetri, a set of machine learning models and a mobile phone application (currently iOS-only) that accelerates common microbiological Petri dish assays using AI.

A task that once took microbiologists several minutes to do per Petri dish (adds up quickly considering there are often tens of Petri dishes to analyze at a time!) could now be mostly automated thanks to computer vision, and completed in a matter of seconds.

App in Action

Video Clip

Petri Dish

Example Image

Plaque Detection

A total of 43 source images were used in this dataset with the following split: 29 training, 9 validation, 5 testing (2505 images after preprocessing and augmentations are applied).

OnePetri is a mobile phone application (currently iOS-only) which accelerates common microbiological Petri dish assays using AI. OnePetri's YOLOv5s plaque detection model was trained on a diverse set of images from the HHMI's SEA-PHAGES program, many of which are included in this dataset. This project wouldn't be possible without their support!

The following pre-processing options were applied:

  1. Auto-orient
  2. Tile image into 5 rows x 5 columns
  3. Resize tiles to 416px x 416px

The following augmentation options were applied:

  1. Grayscale (35% of images)
  2. Hue shift (-45deg to +45deg)
  3. Blur up to 2px
  4. Mosaic

OnePetri App In Action

For more information and to download OnePetri please visit: https://onepetri.ai/.

Cite this Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ onepetri_dataset,
    title = { OnePetri Dataset },
    type = { Open Source Dataset },
    author = { Michael Shamash RF Universe },
    howpublished = { \url{ https://universe.roboflow.com/michael-shamash-rf-universe/onepetri } },
    url = { https://universe.roboflow.com/michael-shamash-rf-universe/onepetri },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { aug },
    note = { visited on 2022-11-23 },
}

Last Updated

4 months ago

Project Type

Object Detection

Subject

plaques

Classes

plaque

License

BY-NC-SA 4.0