class_docstr: The predictor class handles prediction, given an input model.
  
  Loads the images in the input directory, executes training given a model
  and saves the results in the output directory.
  Can receive a path for the weights or can let the user browse through the
  weights directory for the desired weights.
  
  Args:
      input_dir: string, path to the input directory.
      output_dir: string, path to the output directory.
      verbose: bool.
  
  Attributes:
      extensions: list of accepted image extensions.
      img_ls: list of image files in input_dir.
  
  Methods:
      get_predictions: given a model and a string containing the weights' path,
          runs the predictions on the images contained in the input directory and
          stores the results in the output directory.
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code: def _forward_pass(self, file_path):
      lr_img = imageio.imread(file_path)
      if lr_img.shape[2] == 3:
          sr_img = self.model.predict(lr_img)
          return sr_img
      else:
          self.logger.error(
              "{} is not an image with 3 channels.".format(file_path)
          )
  
file_path: image-super-resolution/ISR/predict/predictor.py
imports: from time import time
  import imageio
  import yaml
  import numpy
  from pathlib import Path
  from ISR.utils.logger import get_logger
  from ISR.utils.utils import get_timestamp
label_desc: Use image node_id 5 for calling the Predictor obj's underlying member method code with example usage: obj._forward_pass(file_path) and returns: sr_img