# from tensorflow.keras.models import load_model
# import os
# import matplotlib.pyplot as plt
# from tensorflow.keras.preprocessing import image
# from tensorflow.keras.applications.vgg19 import preprocess_input
# import numpy as np
# import cv2
#
#
# model=load_model("vgg-rps-final.h5")
#
# path = "Test_img"
# i = 0
#
# img = image.load_img(path + "/ml27.jpg" , target_size=(224, 224))
# # plt.imshow(img)
# # plt.show()
#
# x = image.img_to_array(img)
# x = np.expand_dims(x, axis=0)
# images = np.vstack([x])
# pred = model.predict(images, batch_size=1)
# if pred[0][0] > 0.5:
#     category = "Small"
# elif pred[0][1] > 0.5:
#     category = "Big"
#
# print(category)
