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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.
Plantex 🌿 detects plant diseases with 99% accuracy using TensorFlow/Keras 🤖. It offers disease info 📚, product recommendations 🛒, and organic waste exchange 🔄. An AI chatbot 🤖 aids user interaction. Promoting sustainability 🌱 in smart cities.
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.
#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 ...
18 sty 2016 · The large variety of sensor systems available to plant pathologists provides high resolution data of agricultural crop stands and can constitute the basis for early detection and identification of plant diseases.
Using a public dataset of 54,306 images of diseased and healthy plant leaves collected under controlled conditions, we train a deep convolutional neural network to identify 14 crop species and 26 diseases (or absence thereof).
21 kwi 2024 · The investigation’s effectiveness depends significantly on the smooth incorporation of the Plant Village dataset and the YOLOv4 architecture to accurately identify and classify different types of plant leaf diseases.
