ymyy307's picture
Upload folder using huggingface_hub (part 4)
3c11df8 verified
Raw History Blame Contribute Delete
2.69 kB
import torch
from PIL import Image
from diffsynth.pipelines.mova_audio_video import ModelConfig, MovaAudioVideoPipeline
from diffsynth.utils.data.audio_video import write_video_audio
from diffsynth.utils.data import VideoData
vram_config = {
"offload_dtype": torch.bfloat16,
"offload_device": "cpu",
"onload_dtype": torch.bfloat16,
"onload_device": "cuda",
"preparing_dtype": torch.bfloat16,
"preparing_device": "cuda",
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
pipe = MovaAudioVideoPipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="openmoss/MOVA-360p", origin_file_pattern="video_dit/diffusion_pytorch_model-*.safetensors", **vram_config),
ModelConfig(model_id="openmoss/MOVA-360p", origin_file_pattern="video_dit_2/diffusion_pytorch_model-*.safetensors", **vram_config),
ModelConfig(model_id="openmoss/MOVA-360p", origin_file_pattern="audio_dit/diffusion_pytorch_model.safetensors", **vram_config),
ModelConfig(model_id="openmoss/MOVA-360p", origin_file_pattern="dual_tower_bridge/diffusion_pytorch_model.safetensors", **vram_config),
ModelConfig(model_id="openmoss/MOVA-720p", origin_file_pattern="audio_vae/diffusion_pytorch_model.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/Wan-Series-Converted-Safetensors", origin_file_pattern="Wan2.1_VAE.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/Wan-Series-Converted-Safetensors", origin_file_pattern="models_t5_umt5-xxl-enc-bf16.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="openmoss/MOVA-720p", origin_file_pattern="tokenizer/"),
)
pipe.load_lora(pipe.video_dit, './models/train/MOVA-360p-I2AV_high_noise_split/epoch-4.safetensors')
negative_prompt = (
"色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,"
"整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指"
)
prompt = "A beautiful sunset over the ocean."
height, width, num_frames = 352, 640, 121
frame_rate = 24
input_image = VideoData("data/example_video_dataset/ltx2/video.mp4", height=height, width=width)[0]
# Image-to-video
video, audio = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
height=height,
width=width,
num_frames=num_frames,
input_image=input_image,
num_inference_steps=50,
seed=0,
tiled=True,
frame_rate=frame_rate,
)
write_video_audio(video, audio, 'split_training_MOVA-360p-I2AV.mp4', fps=24, audio_sample_rate=pipe.audio_vae.sample_rate)