In this study the disease detections in fruits and vegetables are identified by Machine Learning. The samples of vegetables and fruit leaves with abnormalities are taken into consideration in this inquiry. Farmers can quickly identify illnesses based on the early signs by using these disorder samples of these leaves. Fruit detection and category stays tough because of the texture, color, and form of various fruit categories. To enhance the quality of the vegetable and fruit leaf samples, they are first scaled to 256 by 256 pixels and then subjected to histogram equalization. For the purpose of dividing up dataspace into Polygon cells, the K-means clustering is introduced. Utilizing outline m... More >