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CropCareAI is an AI-powered web application built using Flask to assist plant enthusiasts, farmers, and researchers in identifying and diagnosing plant diseases using pretrained Machine Learning models.
CropCareAI is an AI-powered web application built using Flask to assist plant enthusiasts, farmers, and researchers in identifying and diagnosing plant diseases using pretrained Machine Learning models.
This model learns all the features of 48 different kinds of plants (Healthy and diseased) from the PlantVillage Dataset, and identifies the type of disease and the plant when you input any image in the model.
10th Edition•ISBN: 9780470458365(4 more)Erwin Kreyszig. 4,134 solutions. Terms in this set (27) Plant diseases can be detected by. stunted growth. Plant diseases can be detected by. spots on leaves. Plant diseases can be detected by. areas of decay.
#Importing Library import numpy as np import pandas as pd import matplotlib.pyplot as plt from matplotlib.image import imread import cv2 import random import os from os import listdir from PIL import Image from sklearn.preprocessing import label_binarize, LabelBinarizer from keras.preprocessing import image from keras_preprocessing.image import img_to_array, array_to_img #instead of keras ...
This project presents a Plant Disease Detection System designed to enhance agricultural practices by utilizing machine learning for the early identification of plant diseases. The system is developed using TensorFlow and Streamlit.
This project aims to detect plant diseases from plant leaf images. To achieve this goal we preprocessed images using the grabcut algorithm and trained a CNN model using the plant disease dataset from kaggle. Our model successfully classifies 38 different types of disease with an accuracy up to 97%.
