Plant disease detection using tenorflow and streamlit

— The changes in the environment and climate lead to various diseases in plants. These diseases are sometimes difficult to identify without the right knowledge and expertise. The farmers and other plantation growers do not possess the expertise and resources to correctly identify the diseases of plants and their remedies. To handle this problem machine learning technology can be used, which can correctly identify the disease of the plants and display the remedies to the end-user. Any new emerging disease can be added by proper botanist and their associations for the awareness of farmers. The machine learning system learns about the plant diseases from large datasets and gets trained to correctly identify new test cases given as an input by the farmers through the camera images. Here we propose the methodology uses TensorFlow incorporated with streamlit webapp which can suggest the user about the disease.