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The idea of this project is to build an image classifier to find out healthy and diseased cassava leaves.

There are 4 different classes of leaf diseases namely -Cassava Bacterial Blight (CBB),Cassava Brown Streak Disease (CBSD),Cassava Green Mottle (CGM) and Cassava Mosaic Disease (CMD).

pip install cassava-classifier

importPILimportImagefromcassava.pretrainedimportget_modelimage=Image.open("<insert your image path here>")# Use cassava.list_models() to list of available trained modelsmodel=get_model(name:str)model.predict_as_json(image:np.array)>> {"class_name":str,"confidence":np.float}

Try out the inference code either on google colab or kaggle.

• Training data can be found on theKaggle competition page

• Streamlit app code can be foundhere.

Github discussion forum

[Medium link]

We would like to thank Kaggle community as a whole for providing an avenue to learn and discuss latest data science/machine learning advancements but a hat tip to whose code was used / who inspired us.

1. Vladimir Iglovikov for his wonderful article"I trained a model. What is next?"

2. Y. Nakama for the baseline code.