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