text: # from tensorflow.keras.models import load_model
  import numpy as np
  # import cv2
  # from keras.backend import clear_session
  from skimage.transform import resize
  from skimage import io
  
  img = io.imread("./test.jpg")
  io.imshow(img)
  
  # categories=['Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot','Corn_(maize)___Common_rust_','Corn_(maize)___healthy','Peach___Bacterial_spot','Peach___healthy']
   
  # model = load_model('model.h5')
  
  # def getPrediction():
  #     img = cv2.imread('uploads/test.jpg')
  #     resImage = resize(img,(28,28))
  #     prob = model.predict(np.array([resImage],))
  #     sortProb = np.argsort(prob[0,:])
  #     return categories[sortProb[-1]]
  
  # print(getPrediction())
  