docs: def image_predict(self, X):
          """
          Predicts class label for the entire image.
  
          Parameters:
          -----------
  
          X: array, shape = [n_samples, n_pixels_y, n_pixels_x, n_bands]
              Array of training images
  
          y: array, shape = [n_samples] or [n_samples, n_pixels_y, n_pixels_x]
              Target labels or masks.
          """
          self._check_image(X)
  
          new_shape = (X.shape[0] * X.shape[1] * X.shape[2],)
  
          if len(X.shape) == 4:
              new_shape += (X.shape[3],)
  
          pixels = X.reshape(new_shape)
  
          predictions = self.classifier.predict(self._transform_input(pixels))
  
          return predictions.reshape(X.shape[0], X.shape[1], X.shape[2])