code: def fetch_images(self, images, depth_level):
          
          image_results = {}
          initial_area = float(0.0)
          total_score = float(0.0)
          cnt = float(1.0)
          MIN_WIDTH = 50
          for image in images[:30]:
              src = self.parser.getAttribute(image, attr='src')
              src = self.build_image_path(src)
              local_image = self.get_local_image(src)
              width = local_image.width
              height = local_image.height
              src = local_image.src
              file_extension = local_image.file_extension
  
              if file_extension != '.gif' or file_extension != 'NA':
                  if (depth_level >= 1 and local_image.width > 300) or depth_level < 1:
                      if not self.is_banner_dimensions(width, height):
                          if width > MIN_WIDTH:
                              sequence_score = float(1.0 / cnt)
                              area = float(width * height)
                              total_score = float(0.0)
  
                              if initial_area == 0:
                                  initial_area = area * float(1.48)
                                  total_score = 1
                              else:
                                  area_difference = float(area / initial_area)
                                  total_score = sequence_score * area_difference
  
                              image_results.update({local_image: total_score})
                              cnt += 1
                              cnt += 1
          return image_results
docs: \
          download the images to temp disk and set their dimensions
          - we're going to score the images in the order in which
            they appear so images higher up will have more importance,
          - we'll count the area of the 1st image as a score
            of 1 and then calculate how much larger or small each image after it is
          - we'll also make sure to try and weed out banner
            type ad blocks that have big widths and small heights or vice versa
          - so if the image is 3rd found in the dom it's
            sequence score would be 1 / 3 = .33 * diff
            in area from the first image