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Running
on
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Running
on
Zero
File size: 2,187 Bytes
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# Copyright 2024-2025 The Alibaba Wan Team Authors. All rights reserved.
import argparse
import binascii
import os
import os.path as osp
import json
from omegaconf import OmegaConf
import imageio
import torch
import torchvision
from moviepy.editor import AudioFileClip, VideoClip
__all__ = ['tensor_to_video', 'prepare_json_dataset']
from moviepy.editor import AudioFileClip, VideoClip
def tensor_to_video(tensor, output_video_path, input_audio_path, fps=25):
"""
tensor: shape [f, h, w, c] (as your code expects)
"""
def make_frame(t):
frame_index = min(int(t * fps), tensor.shape[0] - 1)
return tensor[frame_index]
video_duration = tensor.shape[0] / fps
audio_clip = None
audio_subclip = None
video_clip = None
try:
# Load audio
audio_clip = AudioFileClip(input_audio_path)
audio_duration = audio_clip.duration
final_duration = min(video_duration, audio_duration)
# Trim audio
audio_subclip = audio_clip.subclip(0, final_duration)
# Build video
video_clip = VideoClip(make_frame, duration=final_duration)
video_clip = video_clip.set_audio(audio_subclip)
# Write file (this can spawn ffmpeg)
video_clip.write_videofile(
output_video_path,
fps=fps,
audio_codec="aac"
)
finally:
# Make absolutely sure everything is closed
if video_clip is not None:
video_clip.close()
if audio_subclip is not None:
audio_subclip.close()
if audio_clip is not None:
audio_clip.close()
def prepare_json_dataset(json_path):
samples = []
with open(json_path, "rb") as f:
data = json.load(f)
for itemname, row in data.items():
text = row['prompt'].strip().replace("_", " ").strip('"')
audio_path = row['audio_path']
ref_img_path = [x for x in row['img_paths']]
samples.append({
"text": text,
"ref_img": ref_img_path,
"audio": audio_path,
"itemname": itemname
})
samples = OmegaConf.create(samples)
return samples |