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)