Python Image Processing Project - Apple Leaf Disease Classification - ClickMyProject
Leaf diseases are not only influence the economic importance of the fruit and its products, but also abate their ecological prominence. Apple fruit, specifically the fruits and the leaves are highly affected by the fungal disease named as Anthracnose.
The main aim of this process is to develop an appropriate and effective method for diagnosis of the disease espousing a suitable system for an early and cost-effective solution of this problem.
Over the last few years, due to their higher performance capability in terms of computation and accuracy, computer vision, and deep learning methodologies have gained popularity in assorted fungal diseases classification. Apple is widely cultivated as a kind of leaf.
In the whole growth cycle of apples, there are many types of apple leaf diseases and pests, therefore, the detection and diagnosis of these diseases are very necessary. The Deep learning algorithm like Convolutional Neural Network algorithms are used to predict the disease from apple leaf.
In this process, deep learning is used to reduce the size of the training data, the time and the computational costs when building deep learning. Dataset contains both healthy and infected apple leaf images. Results envisage the higher classification accuracy of the proposed CNN model. The result will be generated in the form of accuracy, precision, recall.
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