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Differentiate Cassava leaf diseases from a healthy one with a solution as simple as pip install cassava-classifier. πŸƒπŸ‚

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Cassava leaf disease classification

PyPI version shields.io Downloads

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).

Web app

Open Web App in Streamlit inference

Swagger documentation for API

API Link inference

Installation

pip install cassava-classifier

Inference example

import PIL import Image
from cassava.pretrained import get_model

image = Image.open("<insert your image path here>")

# Use cassava.list_models() to list of available trained models
model = 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.

Open In Colab Kaggle

Other details

Github discussion forum

Blog

[Medium link]

Acknowledgements

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.

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Differentiate Cassava leaf diseases from a healthy one with a solution as simple as pip install cassava-classifier. πŸƒπŸ‚

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