theluyuan/DiffSynth-Studio
1
0
Fork 0
mirror of https://github.com/modelscope/DiffSynth-Studio.git synced 2026-03-24 18:28:10 +00:00
Code Issues Packages Projects Releases Wiki Activity

DiffSynth-Studio 2.0 major update

Browse Source
This commit is contained in:
root
2025-12-04 16:33:07 +08:00
parent afd101f345
commit 72af7122b3
758 changed files with 26462 additions and 2221398 deletions
Download Patch File Download Diff File Expand all files Collapse all files

74
examples/wanvideo/model_inference_low_vram/Wan2.2-Animate-14B.py Normal file
View File

@@ -0,0 +1,74 @@
import torch
from PIL import Image
from diffsynth.core import load_state_dict
from diffsynth.utils.data import save_video, VideoData
from diffsynth.pipelines.wan_video import WanVideoPipeline, ModelConfig
from modelscope import dataset_snapshot_download, snapshot_download
vram_config = {
"offload_dtype": "disk",
"offload_device": "disk",
"onload_dtype": torch.bfloat16,
"onload_device": "cpu",
"preparing_dtype": torch.bfloat16,
"preparing_device": "cuda",
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
pipe = WanVideoPipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="Wan-AI/Wan2.2-Animate-14B", origin_file_pattern="diffusion_pytorch_model*.safetensors", **vram_config),
ModelConfig(model_id="Wan-AI/Wan2.2-Animate-14B", origin_file_pattern="models_t5_umt5-xxl-enc-bf16.pth", **vram_config),
ModelConfig(model_id="Wan-AI/Wan2.2-Animate-14B", origin_file_pattern="Wan2.1_VAE.pth", **vram_config),
ModelConfig(model_id="Wan-AI/Wan2.2-Animate-14B", origin_file_pattern="models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth", **vram_config),
],
tokenizer_config=ModelConfig(model_id="Wan-AI/Wan2.1-T2V-1.3B", origin_file_pattern="google/umt5-xxl/"),
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 2,
)
dataset_snapshot_download(
dataset_id="DiffSynth-Studio/examples_in_diffsynth",
local_dir="./",
allow_file_pattern="data/examples/wan/animate/*",
)
# Animate
input_image = Image.open("data/examples/wan/animate/animate_input_image.png")
animate_pose_video = VideoData("data/examples/wan/animate/animate_pose_video.mp4").raw_data()[:81-4]
animate_face_video = VideoData("data/examples/wan/animate/animate_face_video.mp4").raw_data()[:81-4]
video = pipe(
prompt="视频中的人在做动作",
seed=0, tiled=True,
input_image=input_image,
animate_pose_video=animate_pose_video,
animate_face_video=animate_face_video,
num_frames=81, height=720, width=1280,
num_inference_steps=20, cfg_scale=1,
)
save_video(video, "video_1_Wan2.2-Animate-14B.mp4", fps=15, quality=5)
# Replace
snapshot_download("Wan-AI/Wan2.2-Animate-14B", allow_file_pattern="relighting_lora.ckpt", local_dir="models/Wan-AI/Wan2.2-Animate-14B")
lora_state_dict = load_state_dict("models/Wan-AI/Wan2.2-Animate-14B/relighting_lora.ckpt", torch_dtype=torch.bfloat16, device="cuda")["state_dict"]
lora_state_dict = {i: lora_state_dict[i].to(torch.bfloat16) for i in lora_state_dict}
pipe.load_lora(pipe.dit, state_dict=lora_state_dict)
input_image = Image.open("data/examples/wan/animate/replace_input_image.png")
animate_pose_video = VideoData("data/examples/wan/animate/replace_pose_video.mp4").raw_data()[:81-4]
animate_face_video = VideoData("data/examples/wan/animate/replace_face_video.mp4").raw_data()[:81-4]
animate_inpaint_video = VideoData("data/examples/wan/animate/replace_inpaint_video.mp4").raw_data()[:81-4]
animate_mask_video = VideoData("data/examples/wan/animate/replace_mask_video.mp4").raw_data()[:81-4]
video = pipe(
prompt="视频中的人在做动作",
seed=0, tiled=True,
input_image=input_image,
animate_pose_video=animate_pose_video,
animate_face_video=animate_face_video,
animate_inpaint_video=animate_inpaint_video,
animate_mask_video=animate_mask_video,
num_frames=81, height=720, width=1280,
num_inference_steps=20, cfg_scale=1,
)
save_video(video, "video_2_Wan2.2-Animate-14B.mp4", fps=15, quality=5)