This repository consists of files required for end to end implementation and deployment of Deep Learning Tomato Leaf Disease Prediction API application deployed with flask you can find the Frontend here https://github.com/Tigo-cmd/CNN_Based_Tomatoe_diease_Classifier.
The Tomato Leaf Disease Predictor is a flask API which classifies a plant/leaf image into 10 categories. 'Tomato_mosaic_virus', 'Early_blight', 'Septoria_leaf_spot', 'Bacterial_spot', 'Target_Spot', 'Spider_mites Two spotted_spider_mite', 'Tomato_Yellow_Leaf_Curl_Virus', 'Late_blight', 'Healthy', and 'Leaf_Mold'. The code is written in Python 3.6.10 and makes use of Keras and Tensorflow libraries in developing an InceptionV3 based image classification web application.
If you don't have Python installed, you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after cloning the repository:
pip install -r requirements.txt
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