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By using deep learning algorithms, the project seeks to assist farmers and agricultural experts in early disease detection, enabling them to take necessary measures to protect their potato crops and improve overall yield.\n\n# Dataset used\nhttps://www.kaggle.com/datasets/emmarex/plantdisease\n\n# Tech stack used\n\nModel building - Jupyter notebook using tensorflow, keras, python\n\nFrontend- ReactJs\n\nBackend- FastAPI\n\n# How to run the project on your system\n\n1) Clone the repo\n2) Install requirements.txt using command- pip install -r requirements.txt\n3) Go to frontend folder in the terminal and write- npm start\n4) For backend just run main.py in the api folder.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Favnigoyal25%2Fpotato-disease-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Favnigoyal25%2Fpotato-disease-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Favnigoyal25%2Fpotato-disease-classification/lists"}