from .base_options import BaseOptions

class DatasetOptions(BaseOptions):
    def initialize(self, args=None):
        # BaseOptions.initialize(self)
        # type = int, float, str OR action='store_true'

        # self.parser.add_argument(
        #   '--',
        #   type=int,
        #   default=0,
        #   help=''
        # )

        required = args is None

        self.parser.add_argument(
          '--in_dir',
          type=str,
          required=required,
          help='input directory'
        )

        self.parser.add_argument(
          '--out_dir',
          type=str,
          required=required,
          help='output directory'
        )

        self.parser.add_argument(
          '--split',
          action='store_true',
          help='construct train/test/split for this output, as A'
        )

        self.parser.add_argument(
          '--ab',
          action='store_true',
          help='construct test split into directory A and B, where B = in_dir'
        )

        self.parser.add_argument(
          '--mov',
          action='store_true',
          help='generate video from output directory'
        )

        self.parser.add_argument(
          '--scp',
          action='store_true',
          help='scp this file somewhere'
        )

        self.parser.add_argument(
          '--scp-to',
          type=str,
          default="jules@asdf.us:asdf/neural/",
          help='scp destination'
        )

        self.parser.add_argument(
          '--experiment',
          type=str,
          default="",
          help='experiment name'
        )

        ## IMAGE FILTERS

        ### RECURSION

        self.parser.add_argument(
          '--recursive',
          action='store_true',
          help='recurse on previous output'
        )

        self.parser.add_argument(
          '--recursive-frac',
          default=0.5,
          type=float,
          help='amount of previous step to use in recursion'
        )

        ### GRAYSCALE

        self.parser.add_argument(
          '--grayscale',
          action='store_true',
          help='convert image to grayscale first'
        )

        ### CLAHE

        self.parser.add_argument(
          '--clahe',
          action='store_true',
          help='apply clahe contrast correction'
        )

        self.parser.add_argument(
          '--clip-limit',
          default=2.0,
          type=float,
          help='clip limit for clahe algorithm (1.0 is subtle, 4.0 is aggressive)'
        )

        ### POSTERIZE

        self.parser.add_argument(
          '--posterize',
          action='store_true',
          help='posterize image'
        )

        self.parser.add_argument(
          '--spatial-window',
          default=16,
          type=int,
          help='spatial window for quantize'
        )

        self.parser.add_argument(
          '--color-window',
          default=64,
          type=int,
          help='color window for quantize'
        )

        ### BRIGHTNESS GRADIENT

        self.parser.add_argument(
          '--brightness-gradient',
          action='store_true',
          help='gradiate from first frame to last (done in Lab colorspace)'
        )

        self.parser.add_argument(
          '--brightness-sigma',
          default=64,
          type=int,
          help='width of brightness gradient along L axis'
        )

        ### BLUR

        self.parser.add_argument(
          '--blur',
          action='store_true',
          help='blur image by N'
        )

        self.parser.add_argument(
          '--blur-radius',
          default=3,
          type=int,
          help='blur sigma'
        )

        self.parser.add_argument(
          '--blur-sigma',
          default=0.0,
          type=float,
          help='blur sigma'
        )

        ### CANNY EDGE DETECTION

        self.parser.add_argument(
          '--canny',
          action='store_true',
          help='do canny edge detection on image'
        )

        self.parser.add_argument(
          '--canny-lo',
          default=100,
          type=int,
          help='canny low threshold'
        )

        self.parser.add_argument(
          '--canny-hi',
          default=200,
          type=int,
          help='canny high threshold'
        )

    def parse(self, args=None):
        if not self.initialized:
            self.initialize(args)
        if args is not None:
          self.opt, unknown = self.parser.parse_known_args(args)
        else:
          self.opt, unknown = self.parser.parse_known_args()

        argz = vars(self.opt)
        print('------------ Options -------------')
        for k, v in sorted(argz.items()):
            print('%s: %s' % (str(k), str(v)))
        print('-------------- End ----------------')

        return self.opt