import gradio as gr
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
from tensorflow.keras.models import Sequential
from tensorflow.keras.models import load_model
from keras.preprocessing import image

model3 = load_model('best_beans.h5')

leaf_class=['angular_leaf_spot', 'bean_rust', 'healthy']


def classify_image(img):
  img_width, img_height = 224, 224
  img = image.load_img(img, target_size = (img_width, img_height))
  img = image.img_to_array(img)
  img = np.expand_dims(img, axis = 0)
  prediction = model3.predict(img)[0]
  return {leaf_class[i]: float(prediction[i]) for i in range(3)}

gr.Interface(fn=classify_image,
             inputs=gr.Image( type ="filepath"),
             outputs=gr.Label(num_top_classes=1)).launch(debug=True)