import sys import argparse import re import os from numpy import array, zeros, mean, std, sort, add, subtract, divide, dot, sqrt from numpy import linalg as la from scipy.cluster.vq import vq, kmeans, whiten import vlad parser = argparse.ArgumentParser(description = 'K-means clustering util for image feature processing.') parser.add_argument('-d', help = 'The directory of vlad feature files.') parser.add_argument('-o', help = 'The output file.') args = parser.parse_args() photos = vlad.list_files(args.d) dist = vlad.do_query(photos, photos.keys()) vlad.write_out_distance(dist, args.o)
from scipy.cluster.vq import vq, kmeans, whiten import vlad parser = argparse.ArgumentParser(description = 'K-means clustering util for image feature processing.') parser.add_argument('-d', help = 'The directory of vlad feature files.') parser.add_argument('-q', help = 'The filename of query photo id list.') parser.add_argument('-g', help = 'The filename of groundtruth photo id list.') parser.add_argument('-o', help = 'The output file.') args = parser.parse_args() photos = vlad.list_files(args.d) query = vlad.load_list(args.q) groundtruth = [] if args.g != None: groundtruth = vlad.load_list(args.g) else: groundtruth = query dist = vlad.do_query(photos, query) (ap, map_value) = vlad.validate(dist, query, groundtruth) print("AP: ") print(ap) print("MAP: ") print(map_value)
from numpy import linalg as la from scipy.cluster.vq import vq, kmeans, whiten import vlad parser = argparse.ArgumentParser( description='K-means clustering util for image feature processing.') parser.add_argument('-d', help='The directory of vlad feature files.') parser.add_argument('-q', help='The filename of query photo id list.') parser.add_argument('-g', help='The filename of groundtruth photo id list.') parser.add_argument('-o', help='The output file.') args = parser.parse_args() photos = vlad.list_files(args.d) query = vlad.load_list(args.q) groundtruth = [] if args.g != None: groundtruth = vlad.load_list(args.g) else: groundtruth = query dist = vlad.do_query(photos, query) (ap, map_value) = vlad.validate(dist, query, groundtruth) print("AP: ") print(ap) print("MAP: ") print(map_value)
import sys import argparse import re import os from numpy import array, zeros, mean, std, sort, add, subtract, divide, dot, sqrt from numpy import linalg as la from scipy.cluster.vq import vq, kmeans, whiten import vlad parser = argparse.ArgumentParser( description='K-means clustering util for image feature processing.') parser.add_argument('-d', help='The directory of vlad feature files.') parser.add_argument('-o', help='The output file.') args = parser.parse_args() photos = vlad.list_files(args.d) dist = vlad.do_query(photos, photos.keys()) vlad.write_out_distance(dist, args.o)