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import os
import numpy as np
from scipy.misc import face
import torch
from tqdm import trange
import pickle
from copy import deepcopy
from data_util.face3d_helper import Face3DHelper
from utils.commons.indexed_datasets import IndexedDataset, IndexedDatasetBuilder
def load_video_npy(fn):
assert fn.endswith(".npy")
ret_dict = np.load(fn,allow_pickle=True).item()
video_dict = {
'coeff': ret_dict['coeff'], # [T, h]
'lm68': ret_dict['lm68'], # [T, 68, 2]
'lm5': ret_dict['lm5'], # [T, 5, 2]
}
return video_dict
def cal_lm3d_in_video_dict(video_dict, face3d_helper):
coeff = torch.from_numpy(video_dict['coeff']).float()
identity = coeff[:, 0:80]
exp = coeff[:, 80:144]
idexp_lm3d = face3d_helper.reconstruct_idexp_lm3d(identity, exp).cpu().numpy()
video_dict['idexp_lm3d'] = idexp_lm3d
def load_audio_npy(fn):
assert fn.endswith(".npy")
ret_dict = np.load(fn,allow_pickle=True).item()
audio_dict = {
"mel": ret_dict['mel'], # [T, 80]
"f0": ret_dict['f0'], # [T,1]
}
return audio_dict
if __name__ == '__main__':
face3d_helper = Face3DHelper(use_gpu=False)
import glob,tqdm
prefixs = ['val', 'train']
binarized_ds_path = "data/binary/lrs3"
os.makedirs(binarized_ds_path, exist_ok=True)
for prefix in prefixs:
databuilder = IndexedDatasetBuilder(os.path.join(binarized_ds_path, prefix), gzip=False)
raw_base_dir = '/home/yezhenhui/datasets/raw/lrs3_raw'
spk_ids = sorted([dir_name.split("/")[-1] for dir_name in glob.glob(raw_base_dir + "/*")])
spk_id2spk_idx = {spk_id : i for i,spk_id in enumerate(spk_ids) }
np.save(os.path.join(binarized_ds_path, "spk_id2spk_idx.npy"), spk_id2spk_idx, allow_pickle=True)
mp4_names = glob.glob(raw_base_dir + "/*/*.mp4")
cnt = 0
for i, mp4_name in tqdm.tqdm(enumerate(mp4_names), total=len(mp4_names)):
if prefix == 'train':
if i % 100 == 0:
continue
else:
if i % 100 != 0:
continue
lst = mp4_name.split("/")
spk_id = lst[-2]
clip_id = lst[-1][:-4]
audio_npy_name = os.path.join(raw_base_dir, spk_id, clip_id+"_audio.npy")
hubert_npy_name = os.path.join(raw_base_dir, spk_id, clip_id+"_hubert.npy")
video_npy_name = os.path.join(raw_base_dir, spk_id, clip_id+"_coeff_pt.npy")
if (not os.path.exists(audio_npy_name)) or (not os.path.exists(video_npy_name)):
print(f"Skip item for not found.")
continue
if (not os.path.exists(hubert_npy_name)):
print(f"Skip item for hubert_npy not found.")
continue
audio_dict = load_audio_npy(audio_npy_name)
hubert = np.load(hubert_npy_name)
video_dict = load_video_npy(video_npy_name)
cal_lm3d_in_video_dict(video_dict, face3d_helper)
mel = audio_dict['mel']
if mel.shape[0] < 64: # the video is shorter than 0.6s
print(f"Skip item for too short.")
continue
audio_dict.update(video_dict)
audio_dict['spk_id'] = spk_id
audio_dict['spk_idx'] = spk_id2spk_idx[spk_id]
audio_dict['item_id'] = spk_id + "_" + clip_id
audio_dict['hubert'] = hubert # [T_x, hid=1024]
databuilder.add_item(audio_dict)
cnt += 1
databuilder.finalize()
print(f"{prefix} set has {cnt} samples!") |