| import gradio as gr | |
| import numpy as np | |
| import pandas as pd | |
| from tensorflow import keras | |
| model = keras.models.load_model('model.h5') | |
| classes = ['Mild_Demented', 'Moderate_Demented', 'Non_Demented', 'Very_Mild_Demented'] | |
| def analyse(image): | |
| data = image.reshape((1, 128, 128, 3)) | |
| predict = model.predict(data)[0] | |
| return classes[np.argmax(predict)] | |
| iface = gradio.Interface( | |
| analyse, | |
| gradio.inputs.Image(shape=(128,128)), | |
| "text", | |
| examples=[ | |
| 'Dataset/Non_Demented/non.jpg', | |
| 'Dataset/Moderate_Demented/moderate.jpg', | |
| 'Dataset/Mild_Demented/mild.jpg', | |
| 'Dataset/Very_Mild_Demented/verymild.jpg'], | |
| ) | |
| iface.launch() |