cvdatasets/scripts/utils/parser.py

from cvargparse import BaseParser, Arg

from cvdatasets.annotations import AnnotationType

from cvdatasets.utils import read_info_file

DEFAULT_INFO_FILE="/home/korsch/Data/info.yml"

info_file = read_info_file(DEFAULT_INFO_FILE)

def parse_args():

	parser = BaseParser([
		Arg("data", default=DEFAULT_INFO_FILE),
		Arg("dataset", choices=info_file.DATASETS.keys()),
		Arg("parts", default="GLOBAL", choices=info_file.PARTS.keys()),

		Arg("--feature_model", "-fm",
			choices=["inception", "inception_tf", "resnet"]),

		Arg("--subset", "-sub",
			help="Possible subsets: train, test",
			choices=["train", "test"],
			default="train", type=str),


		Arg("--start", "-s",
			help="Image id to start with",
			type=int, default=0),

		Arg("--n_images", "-n",
			help="Number of images to display",
			type=int, default=10),

		Arg("--only_class",
			help="display only the given class",
			type=int, default=-1),


		Arg("--rnd",
			help="select random subset of present parts",
			action="store_true"),

		Arg("--no_bboxes",
			help="Do not display bounding boxes",
			action="store_true"),

		Arg("--no_parts",
			help="Do not display parts",
			action="store_true"),

		Arg("--crop_to_bb",
			help="Crop image to the bounding box",
			action="store_true"),

		Arg("--no_center_crop", action="store_true"),

		Arg("--crop_uniform",
			help="Try to extend the bounding box to same height and width",
			action="store_true"),

		Arg("--parts_in_bb",
			help="Only display parts, that are inside the bounding box",
			action="store_true"),


		Arg("--features",
			help="pre-extracted train and test features",
			default=[None, None],
			nargs=2, type=str),


		Arg("--ratio",
			help="Part extraction ratio",
			type=float, default=.2),

		Arg("--rescale_size",
			help="rescales the part positions from this size to original image size",
			type=int, default=-1),

		Arg("--uniform_parts", "-u",
			help="Do not use GT parts, but sample parts uniformly from the image",
			action="store_true"),


		Arg('--seed', type=int, default=12311123,
			help='random seed'),

	])

	parser.init_logger()
	return parser.parse_args()