用Wav2Lip+GFPGAN创建高质量的唇型合成视频

在这里，我可以提供一个简单的代码示例，演示如何使用Wav2Lip+GFPGAN来创建高质量的唇形合成视频。代码示例如下：

import torch
import numpy as np
import librosa
import os
import cv2
import imageio
from gfpgan.inferenceg import InferencerG
from options.test_options import TestOptions
from models.Wav2Lip import Wav2Lip

# 加载Wav2Lip和GFPGAN模型
options = TestOptions()
options.parse()
wav2lip_model = Wav2Lip(options)
gfpgan_model = InferencerG(options)

# 定义必要的参数
test_audio_path = "test_audio.wav"
test_video_path = "test_video.mp4"
output_path = "output.mp4"
output_fps = 25
input_size = wav2lip_model.img_size

# 处理帧和音频
audio, sr = librosa.load(test_audio_path, sr=16000)
video_cap = cv2.VideoCapture(test_video_path)
frames = []
frame_count = 0

# 生成唇形动作视频
while True:
    ret, img = video_cap.read()
    if not ret:
        break
    img_resized = cv2.resize(img, (input_size, input_size))
    frame_count += 1
    if frame_count % wav2lip_model.face_detect_frequency == 0:
        frames.append(img_resized)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

audio_padded = np.concatenate(( audio, np.zeros((len(frames) * 1600 - len(audio),)) ))
visual_dim = (input_size, input_size)
new_fps = int(video_cap.get(cv2.CAP_PROP_FPS))

out_size = (input_size * 4, input_size)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

with torch.no_grad():
    for i, frame in enumerate(frames):
        audio_chunk = audio_padded[i * 1600:(i + 1) * 1600].astype(np.float32)
        if i % 50 == 0:
            print("Processing frame %d" % i)

        # 预测唇形
        mouth_points, _ = wav2lip_model.get_mouth(frame)
        mouth_image = wav2lip_model.create_mouth_patch(frame, mouth_points).to(device)

        # 使用GFPGAN转换图像
        mouth_image = gfpgan_model.process(mouth_image, resize_out=True, output_shape=out_size)

        # 将唇形和音频同步合并输出
        imageio.imwrite('./temp/input_frames/' + str(i).zfill(5) + '.png', mouth_image)
        wav2lip_model.inference(imageio.imread('./temp/input_frames/' + str(i).zfill(5) + '.png'), audio_chunk, output_path)

# 最终音视频同步输出
command = "ffmpeg -y -r " + str(output_fps) + " -i temp/result/result%05d.png -i " + test_audio_path + " -c:a aac -ac 2 -ar 44100 -c:v libx264 -pix_fmt yuv420p -crf 18 -preset fast -shortest -avoid_negative_ts make_zero " + output_path
os.system(command)

这是一个简单的参考实现，并不能保证所有情况下都适用，但是可以帮助您了解如何使用Wav2Lip+GFPGAN来生成唇形合成视频。