TMAS’s documentation

Overview

  • The package uses deep learning to detect M. tuberculosis growth in 96-well microtiter plates and determines Minimum Inhibitory Concentrations (MICs).

Usage

TMAS can be used to detect growth in a 96-well plate and calculate the MIC result of each drug based on the assigned plate design (UKMYC5 or UKMYC6) and plot the results

Installation - Python Package

  1. Install TMAS PyPi package:

$ pip install tmas==1.0.1

  1. Run TMAS:

$ run_tmas -visualize [folder_path] [output_format]

  • (Optional) -visualize/–visualize: to illustrate the output image

  • folder_path: The path to the folder of the raw images

  • output_format: output MIC of each drug in csv or json file (default format is csv)

Installation - GitHub

  1. Clone the repository and navigate to the project directory.

$ git clone https://github.com/Oucru-Innovations/tmas/
$ cd tmas

  1. Install the TMAS package using:

$ pip install -e .

  1. Run TMAS:

$ run_tmas -visualize [folder_path] [output_format]

  • (Optional) -visualize/–visualize: to illustrate the output image

  • folder_path: The path to the folder of the raw images

  • output_format: output MIC of each drug in csv or json file (default format is csv)

If encounting any error in Installing the packages, please refer to the Debugging section.

Tutorial (to be updated when the examples are uploaded)

  1. Explore the examples folder

$ cd data
$ ls
1/ 2/ 3/ 4/ 5/

In each examples folder, there is the raw image with the exact same name with the folder

$ ls 1/
01-DR0013-DR0013-1-14-UKMYC6-raw.png

  1. To process and analyse a single image using the default settings is simply

Choose your desired MIC output file:

  • json: with only 1 image

$ run_tmas data/1/01-DR0013-DR0013-1-14-UKMYC6-raw.png json

  • json: with a whole folder

$ run_tmas data/1 json

or

  • csv: with only 1 image

$ tmas_run 01-DR0013-DR0013-1-14-UKMYC6-raw.png csv

  • csv: with a whole folder

$ run_tmas data/1 csv

  1. Growth detection output:

Output Example

4. Output files: After TMAS has done running, the growth detection and MIC results will be displayed in your terminal.

Not only that, the growth detection image and the MIC results file with the chosen format will be saved in the same folder with the input image.

$ ls -a 1/
output/ 01-DR0013-DR0013-1-14-UKMYC6-raw.png
$ ls -a 1/output/
01-DR0013-DR0013-1-14-UKMYC6-growth-matrix.png
01-DR0013-DR0013-1-14-UKMYC6-mics.csv
01-DR0013-DR0013-1-14-UKMYC6-mics.json
01-DR0013-DR0013-1-14-UKMYC6-filtered.png

  • 01-DR0013-DR0013-1-14-UKMYC6-raw.png is the original image.

  • 01-DR0013-DR0013-1-14-UKMYC6-filered.png is the filtered image after preprocessing.

  • 01-DR0013-DR0013-1-14-UKMYC6-growth-matrix.png is the image with the growth detection plotted.

  • 01-DR0013-DR0013-1-14-UKMYC6-mics.csv contains the information, including filename, drug name, growth detection results, MIC result.

  • 01-DR0013-DR0013-1-14-UKMYC6-mics.json contains the same information as the csv file but in a different format per requested.

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