docs: def predict_files(self, files):
          '''
          reads files off disk, resizes them
          and then predicts them, files should
          be a list or itrerable of file paths
          that lead to images, they are then
          loaded with opencv, resized, and predicted
          '''
          imgs = [0]*len(files)
          for i, file in enumerate(files):
              img = cv2.imread(file).astype('float64')
              img = cv2.resize(img, (224,224))
              img = preprocess_input(img)
              if img is None:
                  print('failed to open: {}, continuing...'.format(file))
              imgs[i] = img
          return self.model.predict(np.array(imgs))