streamlit_vgg.py

  #load weights of the trained model.
  input_shape = (224, 224, 3)
  optim_1 = Adam(learning_rate=0.0001)
  n_classes=6
  vgg_model = model(input_shape, n_classes, optim_1, fine_tune=2)
  vgg_model.load_weights('/content/drive/MyDrive/vgg/tune_model19.weights.best.hdf5')

  # prediction on model
  vgg_preds = vgg_model.predict(img)
  vgg_pred_classes = np.argmax(vgg_preds, axis=1)
  c2.header('Output')
  c2.subheader('Predicted class :')
  c2.write(classes[vgg_pred_classes[0]] )