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songkey-win
2025-06-26 00:47:24 +08:00
parent f7ece3f7d4
commit bd8c9d8534
10 changed files with 98 additions and 167 deletions
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hellomeme/pipelines/pipline_hm3_image.py
+13 -20
View File
@@ -21,6 +21,8 @@ from diffusers.pipelines.stable_diffusion.pipeline_output import StableDiffusion
from diffusers import DPMSolverMultistepScheduler
from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img import retrieve_timesteps, retrieve_latents
from ..models import HM3Denoising3D, HMV3ControlNet, HMPipeline, HM3ReferenceAdapter, HMControlNetBase, HM4SD15ControlProj
from ..tools.utils import creat_model_from_cloud
class HM3ImagePipeline(HMPipeline):
def caryomitosis(self, **kwargs):
@@ -44,26 +46,17 @@ class HM3ImagePipeline(HMPipeline):
def insert_hm_modules(self, version='v3', dtype=torch.float16, modelscope=False):
self.version = version
if modelscope:
from modelscope import snapshot_download
if version == 'v3':
hm_reference_dir = snapshot_download('songkey/hm3_reference')
hm_control_dir = snapshot_download('songkey/hm3_control_mix')
else:
hm_reference_dir = snapshot_download('songkey/hm4_reference')
hm_control_dir = snapshot_download('songkey/hm_control_base')
hm_control_proj_dir = snapshot_download('songkey/hm4_control_proj')
if version == 'v3':
hm_reference_dir = 'songkey/hm3_reference'
hm_control_dir = 'songkey/hm3_control_mix'
else:
if version == 'v3':
hm_reference_dir = 'songkey/hm3_reference'
hm_control_dir = 'songkey/hm3_control_mix'
else:
hm_reference_dir = 'songkey/hm4_reference'
hm_control_dir = 'songkey/hm_control_base'
hm_control_proj_dir = 'songkey/hm4_control_proj'
hm_reference_dir = 'songkey/hm4_reference'
hm_control_dir = 'songkey/hm_control_base'
hm_control_proj_dir = 'songkey/hm4_control_proj'
if isinstance(self.unet, HM3Denoising3D):
hm_adapter = HM3ReferenceAdapter.from_pretrained(hm_reference_dir)
hm_adapter = creat_model_from_cloud(HM3ReferenceAdapter, hm_reference_dir, modelscope=modelscope)
self.unet.insert_reference_adapter(hm_adapter)
self.unet.to(device='cpu', dtype=dtype).eval()
@@ -77,10 +70,10 @@ class HM3ImagePipeline(HMPipeline):
del self.mp_control_proj
if version == 'v3':
self.mp_control = HMV3ControlNet.from_pretrained(hm_control_dir)
self.mp_control = creat_model_from_cloud(HMV3ControlNet, hm_control_dir, modelscope=modelscope)
else:
self.mp_control = HMControlNetBase.from_pretrained(hm_control_dir)
self.mp_control_proj = HM4SD15ControlProj.from_pretrained(hm_control_proj_dir)
self.mp_control = creat_model_from_cloud(HMControlNetBase, hm_control_dir, modelscope=modelscope)
self.mp_control_proj = creat_model_from_cloud(HM4SD15ControlProj, hm_control_proj_dir, modelscope=modelscope)
self.mp_control_proj.to(device='cpu', dtype=dtype).eval()
hellomeme/pipelines/pipline_hm3_video.py
+21 -37
View File
@@ -24,7 +24,10 @@ from diffusers import MotionAdapter, EulerDiscreteScheduler # DPMSolverMultistep
from diffusers.utils.torch_utils import randn_tensor
from ..models import (HM3Denoising3D, HM3DenoisingMotion, HM3MotionAdapter,
HMV3ControlNet, HM3ReferenceAdapter, HMPipeline, HMControlNetBase, HM4SD15ControlProj)
HMV3ControlNet, HM3ReferenceAdapter, HMPipeline,
HMControlNetBase, HM4SD15ControlProj)
from ..tools.utils import creat_model_from_cloud
class HM3VideoPipeline(HMPipeline):
def caryomitosis(self, version='v3', modelscope=False, **kwargs):
@@ -38,21 +41,14 @@ class HM3VideoPipeline(HMPipeline):
self.unet_pre = HM3Denoising3D.from_unet2d(self.unet)
self.unet_pre.cpu()
if modelscope:
from modelscope import snapshot_download
if version == 'v3':
hm_animatediff_dir = snapshot_download('songkey/hm3_animatediff')
else:
hm_animatediff_dir = snapshot_download('songkey/hm4_animatediff')
if version == 'v3':
hm_animatediff_dir = 'songkey/hm3_animatediff'
else:
if version == 'v3':
hm_animatediff_dir = 'songkey/hm3_animatediff'
else:
hm_animatediff_dir = 'songkey/hm4_animatediff'
hm_animatediff_dir = 'songkey/hm4_animatediff'
self.num_frames = 12
adapter = MotionAdapter.from_pretrained(hm_animatediff_dir, torch_dtype=torch.float16)
adapter = creat_model_from_cloud(MotionAdapter, hm_animatediff_dir, modelscope=modelscope)
unet = HM3DenoisingMotion.from_unet2d(unet=self.unet, motion_adapter=adapter, load_weights=True)
del self.unet
@@ -67,30 +63,18 @@ class HM3VideoPipeline(HMPipeline):
def insert_hm_modules(self, version='v3', dtype=torch.float16, modelscope=False):
self.version = version
if modelscope:
from modelscope import snapshot_download
if version == 'v3':
hm_reference_dir = snapshot_download('songkey/hm3_reference')
hm_control_dir = snapshot_download('songkey/hm3_control_mix')
hm_motion_dir = snapshot_download('songkey/hm3_motion')
else:
hm_reference_dir = snapshot_download('songkey/hm4_reference')
hm_control_dir = snapshot_download('songkey/hm_control_base')
hm_control_proj_dir = snapshot_download('songkey/hm4_control_proj')
hm_motion_dir = snapshot_download('songkey/hm4_motion')
if version == 'v3':
hm_reference_dir = 'songkey/hm3_reference'
hm_control_dir = 'songkey/hm3_control_mix'
hm_motion_dir = 'songkey/hm3_motion'
else:
if version == 'v3':
hm_reference_dir = 'songkey/hm3_reference'
hm_control_dir = 'songkey/hm3_control_mix'
hm_motion_dir = 'songkey/hm3_motion'
else:
hm_reference_dir = 'songkey/hm4_reference'
hm_control_dir = 'songkey/hm_control_base'
hm_control_proj_dir = 'songkey/hm4_control_proj'
hm_motion_dir = 'songkey/hm4_motion'
hm_reference_dir = 'songkey/hm4_reference'
hm_control_dir = 'songkey/hm_control_base'
hm_control_proj_dir = 'songkey/hm4_control_proj'
hm_motion_dir = 'songkey/hm4_motion'
hm_adapter = HM3ReferenceAdapter.from_pretrained(hm_reference_dir)
motion_adapter = HM3MotionAdapter.from_pretrained(hm_motion_dir)
hm_adapter = creat_model_from_cloud(HM3ReferenceAdapter, hm_reference_dir, modelscope=modelscope)
motion_adapter = creat_model_from_cloud(HM3MotionAdapter, hm_motion_dir, modelscope=modelscope)
if isinstance(self.unet, HM3DenoisingMotion):
self.unet.insert_reference_adapter(hm_adapter)
@@ -111,10 +95,10 @@ class HM3VideoPipeline(HMPipeline):
del self.mp_control_proj
if version == 'v3':
self.mp_control = HMV3ControlNet.from_pretrained(hm_control_dir)
self.mp_control = creat_model_from_cloud(HMV3ControlNet, hm_control_dir, modelscope=modelscope)
else:
self.mp_control = HMControlNetBase.from_pretrained(hm_control_dir)
self.mp_control_proj = HM4SD15ControlProj.from_pretrained(hm_control_proj_dir)
self.mp_control = creat_model_from_cloud(HMControlNetBase, hm_control_dir, modelscope=modelscope)
self.mp_control_proj = creat_model_from_cloud(HM4SD15ControlProj, hm_control_proj_dir, modelscope=modelscope)
self.mp_control_proj.to(device='cpu', dtype=dtype).eval()
self.mp_control.to(device='cpu', dtype=dtype).eval()
hellomeme/pipelines/pipline_hm5_image.py
+13 -18
View File
@@ -22,6 +22,9 @@ from diffusers import DPMSolverMultistepScheduler
from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img import retrieve_timesteps, retrieve_latents
from ..models import (HM3Denoising3D, HMPipeline, HM5ReferenceAdapter,
HM5bReferenceAdapter, HM5ControlNetBase, HM5SD15ControlProj)
from ..tools.utils import creat_model_from_cloud
class HM5ImagePipeline(HMPipeline):
def caryomitosis(self, **kwargs):
@@ -45,27 +48,19 @@ class HM5ImagePipeline(HMPipeline):
def insert_hm_modules(self, version='v5', dtype=torch.float16, modelscope=False):
self.version = version
if modelscope:
from modelscope import snapshot_download
if version == 'v5b':
hm_reference_dir = snapshot_download('songkey/hm5b_reference')
else:
hm_reference_dir = snapshot_download('songkey/hm5_reference')
hm_control_dir = snapshot_download('songkey/hm5_control_base')
hm_control_proj_dir = snapshot_download('songkey/hm5_control_proj')
if version == 'v5b':
hm_reference_dir = 'songkey/hm5b_reference'
else:
if version == 'v5b':
hm_reference_dir = 'songkey/hm5b_reference'
else:
hm_reference_dir = 'songkey/hm5_reference'
hm_control_dir = 'songkey/hm5_control_base'
hm_control_proj_dir = 'songkey/hm5_control_proj'
hm_reference_dir = 'songkey/hm5_reference'
hm_control_dir = 'songkey/hm5_control_base'
hm_control_proj_dir = 'songkey/hm5_control_proj'
if isinstance(self.unet, HM3Denoising3D):
if version == 'v5b':
hm_adapter = HM5bReferenceAdapter.from_pretrained(hm_reference_dir)
hm_adapter = creat_model_from_cloud(HM5bReferenceAdapter, hm_reference_dir, modelscope=modelscope)
else:
hm_adapter = HM5ReferenceAdapter.from_pretrained(hm_reference_dir)
hm_adapter = creat_model_from_cloud(HM5ReferenceAdapter, hm_reference_dir, modelscope=modelscope)
self.unet.insert_reference_adapter(hm_adapter)
self.unet.to(device='cpu', dtype=dtype).eval()
@@ -79,8 +74,8 @@ class HM5ImagePipeline(HMPipeline):
if hasattr(self, "mp_control_proj"):
del self.mp_control_proj
self.mp_control = HM5ControlNetBase.from_pretrained(hm_control_dir)
self.mp_control_proj = HM5SD15ControlProj.from_pretrained(hm_control_proj_dir)
self.mp_control = creat_model_from_cloud(HM5ControlNetBase, hm_control_dir, modelscope=modelscope)
self.mp_control_proj = creat_model_from_cloud(HM5SD15ControlProj, hm_control_proj_dir, modelscope=modelscope)
self.mp_control.to(device='cpu', dtype=dtype).eval()
self.mp_control_proj.to(device='cpu', dtype=dtype).eval()
hellomeme/pipelines/pipline_hm5_video.py
+13 -22
View File
@@ -26,6 +26,8 @@ from diffusers.utils.torch_utils import randn_tensor
from ..models import (HM3Denoising3D, HM5MotionAdapter,
HM5ReferenceAdapter, HM5bReferenceAdapter,
HMPipeline, HM5ControlNetBase, HM5SD15ControlProj)
from ..tools.utils import creat_model_from_cloud
class HM5VideoPipeline(HMPipeline):
def caryomitosis(self, version='v5', modelscope=False, **kwargs):
@@ -52,30 +54,19 @@ class HM5VideoPipeline(HMPipeline):
def insert_hm_modules(self, version='v5', dtype=torch.float16, modelscope=False):
self.version = version
if modelscope:
from modelscope import snapshot_download
if version == 'v5b':
hm_reference_dir = snapshot_download('songkey/hm5b_reference')
else:
hm_reference_dir = snapshot_download('songkey/hm5_reference')
hm_control_dir = snapshot_download('songkey/hm5_control_base')
hm_control_proj_dir = snapshot_download('songkey/hm5_control_proj')
hm_motion_dir = snapshot_download('songkey/hm5_motion')
if version == 'v5b':
hm_reference_dir = 'songkey/hm5b_reference'
else:
if version == 'v5b':
hm_reference_dir = 'songkey/hm5b_reference'
else:
hm_reference_dir = 'songkey/hm5_reference'
hm_control_dir = 'songkey/hm5_control_base'
hm_control_proj_dir = 'songkey/hm5_control_proj'
hm_motion_dir = 'songkey/hm5_motion'
hm_reference_dir = 'songkey/hm5_reference'
hm_control_dir = 'songkey/hm5_control_base'
hm_control_proj_dir = 'songkey/hm5_control_proj'
hm_motion_dir = 'songkey/hm5_motion'
if version == 'v5b':
hm_adapter = HM5bReferenceAdapter.from_pretrained(hm_reference_dir)
hm_adapter = creat_model_from_cloud(HM5bReferenceAdapter, hm_reference_dir, modelscope=modelscope)
else:
hm_adapter = HM5ReferenceAdapter.from_pretrained(hm_reference_dir)
motion_adapter = HM5MotionAdapter.from_pretrained(hm_motion_dir)
hm_adapter = creat_model_from_cloud(HM5ReferenceAdapter, hm_reference_dir, modelscope=modelscope)
motion_adapter = creat_model_from_cloud(HM5MotionAdapter, hm_motion_dir, modelscope=modelscope)
if isinstance(self.unet, HM3Denoising3D):
self.unet.insert_reference_adapter(hm_adapter)
@@ -90,8 +81,8 @@ class HM5VideoPipeline(HMPipeline):
if hasattr(self, "mp_control_proj"):
del self.mp_control_proj
self.mp_control = HM5ControlNetBase.from_pretrained(hm_control_dir)
self.mp_control_proj = HM5SD15ControlProj.from_pretrained(hm_control_proj_dir)
self.mp_control = creat_model_from_cloud(HM5ControlNetBase, hm_control_dir, modelscope=modelscope)
self.mp_control_proj = creat_model_from_cloud(HM5SD15ControlProj, hm_control_proj_dir, modelscope=modelscope)
self.mp_control_proj.to(device='cpu', dtype=dtype).eval()
self.mp_control.to(device='cpu', dtype=dtype).eval()
hellomeme/pipelines/pipline_hm_image.py
+13 -20
View File
@@ -23,6 +23,8 @@ from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img impo
from ..models import HMDenoising3D, HMControlNet, HMControlNet2, HMV2ControlNet, HMV2ControlNet2, HMPipeline
from ..models import HMReferenceAdapter
from ..tools.utils import creat_model_from_cloud
class HMImagePipeline(HMPipeline):
def caryomitosis(self, **kwargs):
@@ -46,27 +48,18 @@ class HMImagePipeline(HMPipeline):
def insert_hm_modules(self, version, dtype, modelscope=False):
self.version = version
if modelscope:
from modelscope import snapshot_download
hm_reference_dir = snapshot_download('songkey/hm_reference')
hm2_reference_dir = snapshot_download('songkey/hm2_reference')
hm_control_dir = snapshot_download('songkey/hm_control')
hm_control2_dir = snapshot_download('songkey/hm_control2')
hm2_control_dir = snapshot_download('songkey/hm2_control')
hm2_control2_dir = snapshot_download('songkey/hm2_control2')
else:
if version == 'v1':
hm_reference_dir = 'songkey/hm_reference'
hm2_reference_dir = 'songkey/hm2_reference'
hm_control_dir = 'songkey/hm_control'
hm_control2_dir = 'songkey/hm_control2'
hm2_control_dir = 'songkey/hm2_control'
hm2_control2_dir = 'songkey/hm2_control2'
else:
hm_reference_dir = 'songkey/hm2_reference'
hm_control_dir = 'songkey/hm2_control'
hm_control2_dir = 'songkey/hm2_control2'
if isinstance(self.unet, HMDenoising3D):
if version == 'v1':
hm_adapter = HMReferenceAdapter.from_pretrained(hm_reference_dir)
else:
hm_adapter = HMReferenceAdapter.from_pretrained(hm2_reference_dir)
hm_adapter = creat_model_from_cloud(HMReferenceAdapter, hm_reference_dir, modelscope=modelscope)
self.unet.insert_reference_adapter(hm_adapter)
self.unet.to(device='cpu', dtype=dtype).eval()
@@ -76,17 +69,17 @@ class HMImagePipeline(HMPipeline):
if hasattr(self, "mp_control"):
del self.mp_control
if version == 'v1':
self.mp_control = HMControlNet.from_pretrained(hm_control_dir)
self.mp_control = creat_model_from_cloud(HMControlNet, hm_control_dir, modelscope=modelscope)
else:
self.mp_control = HMV2ControlNet.from_pretrained(hm2_control_dir)
self.mp_control = creat_model_from_cloud(HMV2ControlNet, hm_control_dir, modelscope=modelscope)
self.mp_control.to(device='cpu', dtype=dtype).eval()
if hasattr(self, "mp_control2"):
del self.mp_control2
if version == 'v1':
self.mp_control2 = HMControlNet2.from_pretrained(hm_control2_dir)
self.mp_control2 = creat_model_from_cloud(HMControlNet2, hm_control2_dir, modelscope=modelscope)
else:
self.mp_control2 = HMV2ControlNet2.from_pretrained(hm2_control2_dir)
self.mp_control2 = creat_model_from_cloud(HMV2ControlNet2, hm_control2_dir, modelscope=modelscope)
self.mp_control2.to(device='cpu', dtype=dtype).eval()
self.vae.to(device='cpu', dtype=dtype).eval()
hellomeme/pipelines/pipline_hm_video.py
+17 -30
View File
@@ -25,6 +25,8 @@ from diffusers import MotionAdapter, EulerDiscreteScheduler
from ..models import (HMDenoising3D, HMDenoisingMotion, HMControlNet, HMControlNet2,
HMV2ControlNet, HMV2ControlNet2, HMPipeline)
from ..models import HMReferenceAdapter
from ..tools.utils import creat_model_from_cloud
class HMVideoPipeline(HMPipeline):
def caryomitosis(self, version, modelscope=False, **kwargs):
@@ -38,19 +40,13 @@ class HMVideoPipeline(HMPipeline):
self.unet_pre = HMDenoising3D.from_unet2d(self.unet)
self.unet_pre.cpu()
if modelscope:
from modelscope import snapshot_download
hm_animatediff_dir = snapshot_download('songkey/hm_animatediff_frame12')
hm2_animatediff_dir = snapshot_download('songkey/hm2_animatediff_frame12')
else:
if version == 'v1':
hm_animatediff_dir = 'songkey/hm_animatediff_frame12'
hm2_animatediff_dir = 'songkey/hm2_animatediff_frame12'
else:
hm_animatediff_dir = 'songkey/hm2_animatediff_frame12'
self.num_frames = 12
if version == 'v1':
adapter = MotionAdapter.from_pretrained(hm_animatediff_dir, torch_dtype=torch.float16)
else:
adapter = MotionAdapter.from_pretrained(hm2_animatediff_dir, torch_dtype=torch.float16)
adapter = creat_model_from_cloud(MotionAdapter, hm_animatediff_dir, modelscope=modelscope)
unet = HMDenoisingMotion.from_unet2d(unet=self.unet, motion_adapter=adapter, load_weights=True)
# todo: 不够优雅
del self.unet
@@ -63,26 +59,17 @@ class HMVideoPipeline(HMPipeline):
self.safety_checker.cpu()
def insert_hm_modules(self, version, dtype, modelscope=False):
if modelscope:
from modelscope import snapshot_download
hm_reference_dir = snapshot_download('songkey/hm_reference')
hm2_reference_dir = snapshot_download('songkey/hm2_reference')
hm_control_dir = snapshot_download('songkey/hm_control')
hm_control2_dir = snapshot_download('songkey/hm_control2')
hm2_control_dir = snapshot_download('songkey/hm2_control')
hm2_control2_dir = snapshot_download('songkey/hm2_control2')
else:
if version == 'v1':
hm_reference_dir = 'songkey/hm_reference'
hm2_reference_dir = 'songkey/hm2_reference'
hm_control_dir = 'songkey/hm_control'
hm_control2_dir = 'songkey/hm_control2'
hm2_control_dir = 'songkey/hm2_control'
hm2_control2_dir = 'songkey/hm2_control2'
if version == 'v1':
hm_adapter = HMReferenceAdapter.from_pretrained(hm_reference_dir)
else:
hm_adapter = HMReferenceAdapter.from_pretrained(hm2_reference_dir)
hm_reference_dir = 'songkey/hm2_reference'
hm_control_dir = 'songkey/hm2_control'
hm_control2_dir = 'songkey/hm2_control2'
hm_adapter = creat_model_from_cloud(HMReferenceAdapter, hm_reference_dir, modelscope=modelscope)
if isinstance(self.unet, HMDenoisingMotion):
self.unet.insert_reference_adapter(hm_adapter)
self.unet.to(device='cpu', dtype=dtype).eval()
@@ -97,18 +84,18 @@ class HMVideoPipeline(HMPipeline):
if hasattr(self, "mp_control"):
del self.mp_control
if version == 'v1':
self.mp_control = HMControlNet.from_pretrained(hm_control_dir)
self.mp_control = creat_model_from_cloud(HMControlNet, hm_control_dir, modelscope=modelscope)
else:
self.mp_control = HMV2ControlNet.from_pretrained(hm2_control_dir)
self.mp_control = creat_model_from_cloud(HMV2ControlNet, hm_control_dir, modelscope=modelscope)
self.mp_control.to(device='cpu', dtype=dtype).eval()
if hasattr(self, "mp_control2"):
del self.mp_control2
if version == 'v1':
self.mp_control2 = HMControlNet2.from_pretrained(hm_control2_dir)
self.mp_control2 = creat_model_from_cloud(HMControlNet2, hm_control2_dir, modelscope=modelscope)
else:
self.mp_control2 = HMV2ControlNet2.from_pretrained(hm2_control2_dir)
self.mp_control2 = creat_model_from_cloud(HMV2ControlNet2, hm2_control2_dir, modelscope=modelscope)
self.mp_control2.to(device='cpu', dtype=dtype).eval()
self.vae.to(device='cpu', dtype=dtype).eval()
hellomeme/tools/sr.py
+2 -7
View File
@@ -15,6 +15,7 @@ import cv2
import numpy as np
import math
import os.path as osp
from .utils import download_file_from_cloud
def pixel_unshuffle(x, scale):
""" Pixel unshuffle.
@@ -183,13 +184,7 @@ class RealESRGANer():
else:
self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') if device is None else device
if modelscope:
from modelscope import snapshot_download
model_path = osp.join(snapshot_download('songkey/ESRGAN'), 'RealESRGAN_x2plus.pth')
else:
from huggingface_hub import hf_hub_download
model_path = hf_hub_download('songkey/ESRGAN', filename='RealESRGAN_x2plus.pth')
model_path = download_file_from_cloud(model_id='songkey/ESRGAN', file_name='RealESRGAN_x2plus.pth', modelscope=modelscope)
loadnet = torch.load(model_path, map_location=torch.device('cpu'))
# prefer to use params_ema
hellomeme/tools/utils.py
+3 -2
View File
@@ -144,6 +144,7 @@ def creat_model_from_cloud(model_cls,
model_id,
modelscope=False,
cache_dir=None,
subfolder=None,
hf_token='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'):
if modelscope:
from modelscope import snapshot_download
@@ -153,10 +154,10 @@ def creat_model_from_cloud(model_cls,
print(e)
assert False, "@@ Failed to download model from modelscope"
model = model_cls.from_pretrained(model_path)
model = model_cls.from_pretrained(model_path, subfolder=subfolder)
else:
try:
model = model_cls.from_pretrained(model_id, cache_dir=cache_dir, token=hf_token)
model = model_cls.from_pretrained(model_id, subfolder=subfolder, cache_dir=cache_dir, token=hf_token)
except Exception as e:
print(e)
assert False, "@@ Failed to download model from huggingface hub"
hellomeme/utils.py
+2 -10
View File
@@ -41,16 +41,8 @@ def get_torch_device(gpu_id=-1):
return torch.device(f"cuda:{gpu_id}")
def load_face_toolkits(dtype=torch.float16, gpu_id=-1, modelscope=False):
if modelscope:
from modelscope import snapshot_download
pd_fpg_dir = snapshot_download('songkey/pd_fgc_motion')
clip_image_dir = snapshot_download('songkey/IP-Adapter')
else:
pd_fpg_dir = 'songkey/pd_fgc_motion'
clip_image_dir = 'songkey/IP-Adapter'
pd_fpg_motion = FanEncoder.from_pretrained(pd_fpg_dir)
image_encoder = CLIPVisionModelWithProjection.from_pretrained(clip_image_dir, subfolder='models/image_encoder')
pd_fpg_motion = creat_model_from_cloud(FanEncoder, 'songkey/pd_fgc_motion')
image_encoder = creat_model_from_cloud(CLIPVisionModelWithProjection, 'songkey/IP-Adapter', subfolder='models/image_encoder')
image_encoder.to(dtype=dtype).cpu()
pd_fpg_motion.to(dtype=dtype).cpu()
pyproject.toml
+1 -1
View File
@@ -1,7 +1,7 @@
[project]
name = "comfyui_hellomeme"
description = "This repository is the official implementation of the [a/HelloMeme](https://arxiv.org/pdf/2410.22901) ComfyUI interface"
version = "1.3.18"
version = "1.3.19"
license = {file = "LICENSE"}
[project.urls]