JoshuaMitton/Mosquitoes-CNN

Mosquitoes CNN

Mosquito Age and Species Classification

This is a collection of Keras models for classification of mosquito age and species classification as described in our paper:

https://www.nature.com/articles/s41467-022-28980-8

Installation

conda create --name mosquitoes python=3.6.13
conda activate mosquitoes
python setup.py install

Data

The dataset used in this project can be dowloaded from https://www.nature.com/articles/s41467-022-28980-8.

Download the dataset into the mosquitoes/Data folder and unzip:

unzip .zip

Then process the data with the scripts provdided in mosquitoes/Data/MIMI-project. First run

OPUS dei 2.3.ipynb

then

Loco mosquito 5.0.ipynb

Run the examples

We provide notebooks to train different models for different datasets. To train the CNN model look at the scripts in mosquitoes/Models/CNN/CNN.

To train on LV data

MIMI-Paper-CNN-Lab-Only.ipynb

To train on LV+GV data

MIMI-Paper-CNN-TCField.ipynb

To train on EV data

MIMI-Paper-CNN-TCValie.ipynb

To train on Wild data

MIMI-Paper-CNN-Wild-retrain-v2

There is also the equivalent notebooks for the MLP model in the folder mosquitoes/Models/MLP.

Further, to perform the sensitivity analysis use the notebook in mosquitoes/Models/Sensitivity_Analysis

MIMI-Sensitivity.ipynb

Finally, we initially used UMAP for some early data visualisations. The notebook for this is in mosquitoes/Models/UMAP

UMAP_MIMI_data_w_dates.ipynb

Cite

Please cite our paper if you make use of our work:

@article{siria2022rapid,
  title={Rapid age-grading and species identification of natural mosquitoes for malaria surveillance},
  author={Siria, Doreen J and Sanou, Roger and Mitton, Joshua and Mwanga, Emmanuel P and Niang, Abdoulaye and Sare, Issiaka and Johnson, Paul CD and Foster, Geraldine M and Belem, Adrien MG and Wynne, Klaas and others},
  journal={Nature communications},
  volume={13},
  number={1},
  pages={1--9},
  year={2022},
  publisher={Nature Publishing Group}
}