def main():
centers = __load_cnnv_centers__()
cnnvfa = CNNVFeatureAggregation(centers)
video_lists = get_video_id()
cnnvfa.start(video_lists)
cnnvfa.stop()
cnnvfa.get_results()
logger.info('all done')
def main():
video_lists = get_video_id(dtype='labeled-data')
pos_video_lists = None
cfs = CNNLVFrameSampler(pos_video_lists)
cfs.start(video_lists)
cfs.stop()
features, mean_feature = cfs.get_results()
filepath = os.path.join(opt['featurepath'], 'cnnlv-sampling-features.h5')
fp = h5py.File(filepath, mode='w')
fp.create_dataset(name='features', data=features)
fp.create_dataset(name='mean_features', data=mean_feature)
fp.close()
logger.info('all done')
def main():
unlabeled_keys = get_video_id(dtype='unlabeled-data')
gt_file = os.path.join(opt['metadatapath'], 'test_groundtruth')
gnds = load_groundtruth(gt_file)
featurepath = os.path.join(opt['featurepath'], 'cnnv-agg-features.h5')
all_features, _ = load_features(featurepath)
logger.info('load features done')
map = calc_euclidean_search(all_features, unlabeled_keys, gnds)
logger.info('map: {:.4f}'.format(map))
logger.info('all done')
def main():
# load features
features = load_features()
logger.info('loading features done. #videos: {}'.format(len(features)))
# load groundtruth and unlabeled-keys
gnds = load_groundtruth('test_groundtruth')
unlabeled_keys = get_video_id('unlabeled-data')
logger.info('load gnds and unlabeled keys done. #query: {}'.format(len(gnds)))
# calculate map
map = calc_euclidean_search(features, unlabeled_keys, gnds)
logger.info('map: {:.4f}'.format(map))
logger.info('all done')