mirror of
https://github.com/modelscope/DiffSynth-Studio.git
synced 2026-03-20 15:48:20 +00:00
add fun-v1.1-1.3B-control-camera
This commit is contained in:
lzw478614@alibaba-inc.com
@@ -15,7 +15,7 @@
|
||||
|[PAI/Wan2.1-Fun-V1.1-14B-Control](https://modelscope.cn/models/PAI/Wan2.1-Fun-V1.1-14B-Control)|基础模型|`control_video`, `reference_image`|[code](./model_inference/Wan2.1-Fun-V1.1-14B-Control.py)|[code](./model_training/full/Wan2.1-Fun-V1.1-14B-Control.sh)|[code](./model_training/validate_full/Wan2.1-Fun-V1.1-14B-Control.py)|[code](./model_training/lora/Wan2.1-Fun-V1.1-14B-Control.sh)|[code](./model_training/validate_lora/Wan2.1-Fun-V1.1-14B-Control.py)|
|
||||
|[PAI/Wan2.1-Fun-V1.1-1.3B-InP](https://modelscope.cn/models/PAI/Wan2.1-Fun-V1.1-1.3B-InP)|基础模型|`input_image`, `end_image`||||||
|
||||
|[PAI/Wan2.1-Fun-V1.1-14B-InP](https://modelscope.cn/models/PAI/Wan2.1-Fun-V1.1-14B-InP)|基础模型|`input_image`, `end_image`||||||
|
||||
|[PAI/Wan2.1-Fun-V1.1-1.3B-Control-Camera](https://modelscope.cn/models/PAI/Wan2.1-Fun-V1.1-1.3B-Control-Camera)|基础模型|||||||
|
||||
|[PAI/Wan2.1-Fun-V1.1-1.3B-Control-Camera](https://modelscope.cn/models/PAI/Wan2.1-Fun-V1.1-1.3B-Control-Camera)|基础模型|`control_camera_video`, `input_image`|[code](./model_inference/Wan2.1-Fun-V1.1-1.3B-Control-Camera.py)|||||
|
||||
|[PAI/Wan2.1-Fun-V1.1-14B-Control-Camera](https://modelscope.cn/models/PAI/Wan2.1-Fun-V1.1-14B-Control-Camera)|基础模型|||||||
|
||||
|[iic/VACE-Wan2.1-1.3B-Preview](https://modelscope.cn/models/iic/VACE-Wan2.1-1.3B-Preview)|适配器|`vace_control_video`, `vace_reference_image`|[code](./model_inference/Wan2.1-VACE-1.3B-Preview.py)|[code](./model_training/full/VACE-Wan2.1-1.3B-Preview.sh)|[code](./model_training/validate_full/VACE-Wan2.1-1.3B-Preview.py)|[code](./model_training/lora/VACE-Wan2.1-1.3B-Preview.sh)|[code](./model_training/validate_lora/VACE-Wan2.1-1.3B-Preview.py)|
|
||||
|[Wan-AI/Wan2.1-VACE-1.3B](https://modelscope.cn/models/Wan-AI/Wan2.1-VACE-1.3B)|适配器|`vace_control_video`, `vace_reference_image`|[code](./model_inference/Wan2.1-VACE-1.3B.py)|||||
|
||||
|
||||
@@ -0,0 +1,129 @@
|
||||
import torch
|
||||
from PIL import Image
|
||||
from diffsynth import save_video, VideoData
|
||||
from diffsynth.pipelines.wan_video_new import WanVideoPipeline, ModelConfig
|
||||
from modelscope import dataset_snapshot_download
|
||||
from diffsynth.models.wan_video_camera_controller import process_pose_file
|
||||
|
||||
pipe = WanVideoPipeline.from_pretrained(
|
||||
torch_dtype=torch.bfloat16,
|
||||
device="cuda",
|
||||
model_configs=[
|
||||
ModelConfig(model_id="PAI/Wan2.1-Fun-V1.1-1.3B-Control-Camera", origin_file_pattern="diffusion_pytorch_model*.safetensors", offload_device="cpu"),
|
||||
ModelConfig(model_id="PAI/Wan2.1-Fun-V1.1-1.3B-Control-Camera", origin_file_pattern="models_t5_umt5-xxl-enc-bf16.pth", offload_device="cpu"),
|
||||
ModelConfig(model_id="PAI/Wan2.1-Fun-V1.1-1.3B-Control-Camera", origin_file_pattern="Wan2.1_VAE.pth", offload_device="cpu"),
|
||||
ModelConfig(model_id="PAI/Wan2.1-Fun-V1.1-1.3B-Control-Camera", origin_file_pattern="models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth", offload_device="cpu"),
|
||||
],
|
||||
)
|
||||
pipe.enable_vram_management()
|
||||
|
||||
|
||||
# Control camera video
|
||||
# text or txt file path, e.g. control_camera_text = "Pan_Left.txt"
|
||||
control_camera_text = '''
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.018518518518518517 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.037037037037037035 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.05555555555555555 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.07407407407407407 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.09259259259259259 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.1111111111111111 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.12962962962962962 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.14814814814814814 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.16666666666666666 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.18518518518518517 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.2037037037037037 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.2222222222222222 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.24074074074074073 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.25925925925925924 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.2777777777777778 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.2962962962962963 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.31481481481481477 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.3333333333333333 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.35185185185185186 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.37037037037037035 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.38888888888888884 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.4074074074074074 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.42592592592592593 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.4444444444444444 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.4629629629629629 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.48148148148148145 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.5 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.5185185185185185 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.537037037037037 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.5555555555555556 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.5740740740740741 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.5925925925925926 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.611111111111111 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.6296296296296295 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.6481481481481481 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.6666666666666666 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.6851851851851851 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.7037037037037037 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.7222222222222222 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.7407407407407407 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.7592592592592593 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.7777777777777777 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.7962962962962963 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.8148148148148148 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.8333333333333334 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.8518518518518519 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.8703703703703705 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.8888888888888888 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.9074074074074074 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.9259259259259258 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.9444444444444444 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.9629629629629629 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 0.9814814814814815 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.0185185185185186 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.037037037037037 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.0555555555555556 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.074074074074074 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.0925925925925926 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.1111111111111112 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.1296296296296298 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.1481481481481481 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.1666666666666667 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.1851851851851851 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.2037037037037037 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.222222222222222 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.2407407407407407 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.259259259259259 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.2777777777777777 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.2962962962962963 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.3148148148148149 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.3333333333333333 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.3518518518518519 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.3703703703703702 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.3888888888888888 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.4074074074074074 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.425925925925926 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.4444444444444444 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.462962962962963 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
0 0.532139961 0.946026558 0.5 0.5 0 0 1.0 0.0 0.0 1.4814814814814814 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0
|
||||
'''
|
||||
|
||||
dataset_snapshot_download(
|
||||
dataset_id="DiffSynth-Studio/examples_in_diffsynth",
|
||||
local_dir="./",
|
||||
allow_file_pattern=f"data/examples/wan/input_image.jpg"
|
||||
)
|
||||
input_image = Image.open("data/examples/wan/input_image.jpg")
|
||||
|
||||
height = 480
|
||||
width = 832
|
||||
|
||||
control_camera_video = process_pose_file(control_camera_text, width, height)
|
||||
|
||||
|
||||
|
||||
video = pipe(
|
||||
prompt="一艘小船正勇敢地乘风破浪前行。蔚蓝的大海波涛汹涌，白色的浪花拍打着船身，但小船毫不畏惧，坚定地驶向远方。阳光洒在水面上，闪烁着金色的光芒，为这壮丽的场景增添了一抹温暖。镜头拉近，可以看到船上的旗帜迎风飘扬，象征着不屈的精神与冒险的勇气。这段画面充满力量，激励人心，展现了面对挑战时的无畏与执着。",
|
||||
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，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走",
|
||||
height=height, width=width, num_frames=81,
|
||||
seed=43, tiled=True,
|
||||
control_camera_video = control_camera_video,
|
||||
input_image = input_image,
|
||||
)
|
||||
save_video(video, "video.mp4", fps=15, quality=5)
|
||||
Reference in New Issue
Block a user