docs: def initial_classification(self, obresult, target_is_sky=False):
          """Classify input frames, """
          # lists of targets and sky frames
  
          with obresult.frames[0].open() as baseimg:
              # Initial checks
              has_bpm_ext = 'BPM' in baseimg
              self.logger.debug('images have BPM extension: %s', has_bpm_ext)
  
          images_info = []
          for f in obresult.frames:
              with f.open() as img:
                  # Getting some metadata from FITS header
                  hdr = img[0].header
  
                  iinfo = ImageInfo(f)
  
                  finfo = {}
                  iinfo.metadata = finfo
  
                  finfo['uuid'] = hdr['UUID']
                  finfo['exposure'] = hdr['EXPTIME']
                  # frame.baseshape = get_image_shape(hdr)
                  finfo['airmass'] = hdr['airmass']
                  finfo['mjd'] = hdr['tstamp']
  
                  iinfo.label = 'result_image_{}'.format(finfo['uuid'])
                  iinfo.mask = nfcom.Extension("BPM")
                  # Insert pixel offsets between frames
                  iinfo.objmask_data = None
                  iinfo.valid_target = False
                  iinfo.valid_sky = False
  
                  # FIXME: hardcode itype for the moment
                  iinfo.itype = 'TARGET'
                  if iinfo.itype == 'TARGET':
                      iinfo.valid_target = True
                      #targetframes.append(iinfo)
                      if target_is_sky:
                          iinfo.valid_sky = True
                          #skyframes.append(iinfo)
                  if iinfo.itype == 'SKY':
                      iinfo.valid_sky = True
                      #skyframes.append(iinfo)
                  images_info.append(iinfo)
  
          return images_info