if len(to_pull) == 0:
continue
DB.photos.update({'_id': {'$in': to_pull}},
{'$pull': {'ntags': t}}, multi=True)
removed += len(to_pull)
logging.info(u'from {}, remove {} in {} photos.'.format(u, t,
len(to_pull)))
return removed
def get_freq(tag):
print(tag)
mq.compute_frequency(DB.photos, tag, mq.SF_BBOX, sot, now, plot=False)
if __name__ == '__main__':
import pymongo
import random
client = pymongo.MongoClient('localhost', 27017)
DB = client['flickr']
mq.DB = DB
tmp = mq.load_var('supported')
tags = [v[0] for v in tmp]
random.shuffle(tags)
tt = mq.clock()
p = Pool(4)
p.map(get_freq, tags)
p.close()
print('done in {:.2f}.'.format(mq.clock() - tt))
# logging.info('removed tags in {} photos ({:.2f}).'.format(clean_tags(), mq.clock() - tt))
GRID_SIZE = 80
TOP_K = 2000
MIN_WIDTH = 1
MIN_HEIGHT = 1
MAX_SIZE = 4
MAX_SUPPORT = 250
REJECTED = 0
rectangles, dummy, index_to_rect = k_split_bbox(BBOX, GRID_SIZE)
if __name__ == '__main__':
import sys
# import random
# random.seed(135)
tag = 'museum' if len(sys.argv) <= 1 else sys.argv[1]
tt = clock()
# tmp = persistent.load_var('supported')
# tags = [v[0] for v in tmp]
# random.shuffle(tags)
# tt = clock()
# p = Pool(3)
# p.map(spatial_scan, tags)
# p.map(post_process, tags)
# p.close()
# consolidate(tags)
# print(get_best_tags(Point(-122.409615, 37.7899132)))
spatial_scan(tag)
# sio.savemat('alld', {'d': ALLD})
print(REJECTED)
print('done in {:.2f}.'.format(clock() - tt))
# plot_regions(merged, BBOX, tag)
'ntags': t
}},
multi=True)
removed += len(to_pull)
logging.info(u'from {}, remove {} in {} photos.'.format(
u, t, len(to_pull)))
return removed
def get_freq(tag):
print(tag)
mq.compute_frequency(DB.photos, tag, mq.SF_BBOX, sot, now, plot=False)
if __name__ == '__main__':
import pymongo
import random
client = pymongo.MongoClient('localhost', 27017)
DB = client['flickr']
mq.DB = DB
tmp = mq.load_var('supported')
tags = [v[0] for v in tmp]
random.shuffle(tags)
tt = mq.clock()
p = Pool(4)
p.map(get_freq, tags)
p.close()
print('done in {:.2f}.'.format(mq.clock() - tt))
# logging.info('removed tags in {} photos ({:.2f}).'.format(clean_tags(), mq.clock() - tt))
return sorted(res, key=lambda x: x[1], reverse=True)
GRID_SIZE = 80
TOP_K = 2000
MIN_WIDTH = 1
MIN_HEIGHT = 1
MAX_SIZE = 4
MAX_SUPPORT = 250
REJECTED = 0
rectangles, dummy, index_to_rect = k_split_bbox(BBOX, GRID_SIZE)
if __name__ == '__main__':
import sys
# import random
# random.seed(135)
tag = 'museum' if len(sys.argv) <= 1 else sys.argv[1]
tt = clock()
# tmp = persistent.load_var('supported')
# tags = [v[0] for v in tmp]
# random.shuffle(tags)
# tt = clock()
# p = Pool(3)
# p.map(spatial_scan, tags)
# p.map(post_process, tags)
# p.close()
# consolidate(tags)
# print(get_best_tags(Point(-122.409615, 37.7899132)))
spatial_scan(tag)
# sio.savemat('alld', {'d': ALLD})
print(REJECTED)
print('done in {:.2f}.'.format(clock() - tt))
# plot_regions(merged, BBOX, tag)
