voxceleb_list = "Data/voxceleb.npy" voxceleb_dev_list = "Data/voxceleb_dev.npy" voxceleb_dev_10k_list = "Data/voxceleb_dev_10k.npy" if os.path.isfile(voxceleb_list): voxceleb = np.load(voxceleb_list, allow_pickle=True) else: voxceleb = read_my_voxceleb_structure(args.dataroot) np.save(voxceleb_list, voxceleb) # Make fbank feature if not yet. if args.makemfb: #pbar = tqdm(voxceleb) for datum in voxceleb: # print(datum['filename']) mk_MFB((args.dataroot + '/' + datum['filename'] + '.wav')) print("Complete convert") # Create file loader for dataset if args.mfb: transform = transforms.Compose([truncatedinputfromMFB(), totensor()]) transform_T = transforms.Compose([ truncatedinputfromMFB(input_per_file=args.test_input_per_file), totensor() ]) file_loader = read_MFB else: transform = transforms.Compose([ truncatedinput(), toMFB(), totensor(),
# create logger logger = Logger(LOG_DIR) # Define visulaize SummaryWriter instance writer = SummaryWriter('Log/amsoftmax_res10', comment='margin0.3') kwargs = {'num_workers': 0, 'pin_memory': True} if args.cuda else {} if args.cos_sim: l2_dist = nn.CosineSimilarity(dim=1, eps=1e-6) else: l2_dist = PairwiseDistance(2) voxceleb, voxceleb_dev = wav_list_reader(args.dataroot) if args.makemfb: # pbar = tqdm(voxceleb) for datum in voxceleb: mk_MFB( (args.dataroot + '/voxceleb1_wav/' + datum['filename'] + '.wav')) print("Complete convert") if args.mfb: transform = transforms.Compose([ concateinputfromMFB(), # truncatedinputfromMFB(), totensor() ]) transform_T = transforms.Compose([ concateinputfromMFB(input_per_file=args.test_input_per_file), # truncatedinputfromMFB(input_per_file=args.test_input_per_file), totensor() ]) file_loader = read_MFB else:
os.makedirs(EXT_DIR) # create logger logger = Logger(LOG_DIR) kwargs = {'num_workers': 0, 'pin_memory': True} if args.cuda else {} l2_dist = PairwiseDistance(2) audio_set = [] audio_set = if_load_npy(dataroot, data_set_list) if args.makemfb: #pbar = tqdm(voxceleb) for datum in audio_set: # print(datum['filename']) mk_MFB((datum['filename']+'.wav')) print("Complete convert") if args.mfb: transform = transforms.Compose([ concateinputfromMFB(), to4tensor() # truncatedinputfromMFB(), # totensor() ]) transform_T = transforms.Compose([ truncatedinputfromMFB(input_per_file=args.test_input_per_file), totensor() ]) file_loader = read_MFB else: