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import os
import torch
import numpy as np
from moviepy.editor import VideoFileClip
import pickle
from vggish_modified import VGGish as VGGish_modified # 修改后的VGGish代码
# 定义输入视频文件夹和输出特征文件路径
video_folder_path = '/mnt/data10t/dazuoye/GROUP2024-GEN6/FakeSV/dataset/videos'
feature_path = '/mnt/data10t/dazuoye/GROUP2024-GEN6/FakeSV/code/VGGish_Feature_Extractor/my_dict_vid_audioconvfea.pkl'
# 加载模型
urls = {
'vggish': 'https://github.com/harritaylor/torchvggish/releases/download/v0.1/vggish-10086976.pth',
'pca': 'https://github.com/harritaylor/torchvggish/releases/download/v0.1/vggish_pca_params-970ea276.pth'
}
vggish_model = VGGish_modified(urls, pretrained=True)
# 初始化保存特征的字典
features_dict = {}
audio_file_path = '/mnt/data10t/dazuoye/GROUP2024-GEN6/FakeSV/dataset/1.wav'
# 遍历视频文件夹中的所有视频文件
for video_file_name in os.listdir(video_folder_path):
video_file_path = os.path.join(video_folder_path, video_file_name)
# 提取视频文件名（不包括扩展名）作为视频ID
video_id = os.path.splitext(video_file_name)[0]
# video_id = video_file_name.split('_')[1].split('.')[0]
try:
# 从视频中提取音频
video = VideoFileClip(video_file_path)
video.audio.write_audiofile(audio_file_path)
# 提取特征
features = vggish_model(audio_file_path)
# 保存特征到字典中
features_dict[video_id] = features.cpu().detach().numpy()
except Exception as e:
print(f"Error processing {video_file_name}: {e}")
# 保存特征字典到文件
with open(feature_path, 'wb') as f:
pickle.dump(features_dict, f)
print(f"Audio features have been saved to {feature_path}")
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