import numpy as np

import pandas as pd

import os

import sys

import argparse

from collections import defaultdict

import subprocess

import aux

import matplotlib

matplotlib.use('Agg')

import matplotlib as mpl

import matplotlib.pyplot as plt

import matplotlib.image as mpimg

from matplotlib import cm

from shapely.geometry import Polygon

import operator

import re

from nltk.corpus import wordnet as wn

import nltk

def main(arguments):

extractor = RCNNObjectExtractor(arguments)

extractor.process_hdf()

class RCNNObjectExtractor:

return False

if __name__ == "__main__":

parser = argparse.ArgumentParser(description='Extract the RCNN object region proposals from an HDF file.')

parser.add_argument('--hdffile', help='the HDF file to read the data from')

parser.add_argument('-n', type=int, help='number of detections to return', default=5)

parser.add_argument('--output', required=0, help='optional location to write the LabelMe compatible XML output')

parser.add_argument('--clustersfile', required=0, help="Optional list of objects to extract, if not provided then all object types will be deemed acceptable.")

parser.add_argument("--sub", required=0, help="Look for a specific subject?")

parser.add_argument("--obj", required=0, help="Look for a specific object?")

parser.add_argument("--image", required=0, help="Extract from a specific image?")

parser.add_argument("--verbose", help="Should the output be verbose?", action="store_true")

parser.add_argument("--training", help="Are we extracting training data or test data?", action="store_true", default=True)

if len(sys.argv)==1:

parser.print_help()

sys.exit(1)

main(parse.parse_args())