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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 ...
We will download a public dataset of 54,305 images of diseased and healthy plant leaves collected under controlled conditions ( PlantVillage Dataset). The images cover 14 species of crops,...
Identify Plant Diseases We use the PlantVillage dataset [1] by Hughes et al. consists of about 87,000 healthy and unhealthy leaf images divided into 38 categories by species and disease....
6 wrz 2021 · We introduce a new dataset in the literature for the diagnosis and monitoring of plant symptoms, called DiaMOS Plant. It is a dataset collected under realistic field conditions, composed of 3505 images depicting 4 leaf stresses and 3 stages of fruit development: fruit set, growth and ripening.
