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from modules_forge.supported_preprocessor import PreprocessorClipVision, Preprocessor, PreprocessorParameter
from modules_forge.shared import add_supported_preprocessor
from modules_forge.utils import numpy_to_pytorch
from modules_forge.shared import add_supported_control_model
from modules_forge.supported_controlnet import ControlModelPatcher
from lib_ipadapter.IPAdapterPlus import IPAdapterApply, InsightFaceLoader
from pathlib import Path
opIPAdapterApply = IPAdapterApply().apply_ipadapter
opInsightFaceLoader = InsightFaceLoader().load_insight_face
class PreprocessorClipVisionForIPAdapter(PreprocessorClipVision):
def __init__(self, name, url, filename):
super().__init__(name, url, filename)
self.tags = ['IP-Adapter']
self.model_filename_filters = ['IP-Adapter', 'IP_Adapter']
self.sorting_priority = 20
def __call__(self, input_image, resolution, slider_1=None, slider_2=None, slider_3=None, **kwargs):
cond = dict(
clip_vision=self.load_clipvision(),
image=numpy_to_pytorch(input_image),
weight_type="original",
noise=0.0,
embeds=None,
unfold_batch=False,
)
return cond
class PreprocessorClipVisionWithInsightFaceForIPAdapter(PreprocessorClipVisionForIPAdapter):
def __init__(self, name, url, filename):
super().__init__(name, url, filename)
self.cached_insightface = None
def load_insightface(self):
if self.cached_insightface is None:
self.cached_insightface = opInsightFaceLoader()[0]
return self.cached_insightface
def __call__(self, input_image, resolution, slider_1=None, slider_2=None, slider_3=None, **kwargs):
cond = dict(
clip_vision=self.load_clipvision(),
insightface=self.load_insightface(),
image=numpy_to_pytorch(input_image),
weight_type="original",
noise=0.0,
embeds=None,
unfold_batch=False,
)
return cond
class PreprocessorInsightFaceForInstantID(Preprocessor):
def __init__(self, name):
super().__init__()
self.name = name
self.tags = ['Instant-ID']
self.model_filename_filters = ['Instant-ID', 'Instant_ID']
self.sorting_priority = 20
self.slider_resolution = PreprocessorParameter(visible=False)
self.corp_image_with_a1111_mask_when_in_img2img_inpaint_tab = False
self.show_control_mode = False
self.sorting_priority = 10
self.cached_insightface = None
def load_insightface(self):
if self.cached_insightface is None:
self.cached_insightface = opInsightFaceLoader(name='antelopev2')[0]
return self.cached_insightface
def __call__(self, input_image, resolution, slider_1=None, slider_2=None, slider_3=None, **kwargs):
cond = dict(
clip_vision=None,
insightface=self.load_insightface(),
image=numpy_to_pytorch(input_image),
weight_type="original",
noise=0.0,
embeds=None,
unfold_batch=False,
instant_id=True
)
return cond
add_supported_preprocessor(PreprocessorClipVisionForIPAdapter(
name='CLIP-ViT-H (IPAdapter)',
url='https://huggingface.co/h94/IP-Adapter/resolve/main/models/image_encoder/model.safetensors',
filename='CLIP-ViT-H-14.safetensors'
))
add_supported_preprocessor(PreprocessorClipVisionForIPAdapter(
name='CLIP-ViT-bigG (IPAdapter)',
url='https://huggingface.co/h94/IP-Adapter/resolve/main/sdxl_models/image_encoder/model.safetensors',
filename='CLIP-ViT-bigG.safetensors'
))
add_supported_preprocessor(PreprocessorClipVisionWithInsightFaceForIPAdapter(
name='InsightFace+CLIP-H (IPAdapter)',
url='https://huggingface.co/h94/IP-Adapter/resolve/main/models/image_encoder/model.safetensors',
filename='CLIP-ViT-H-14.safetensors'
))
add_supported_preprocessor(PreprocessorInsightFaceForInstantID(
name='InsightFace (InstantID)',
))
class IPAdapterPatcher(ControlModelPatcher):
@staticmethod
def try_build_from_state_dict(state_dict, ckpt_path):
model = state_dict
if ckpt_path.lower().endswith(".safetensors"):
st_model = {"image_proj": {}, "ip_adapter": {}}
for key in model.keys():
if key.startswith("image_proj."):
st_model["image_proj"][key.replace("image_proj.", "")] = model[key]
elif key.startswith("ip_adapter."):
st_model["ip_adapter"][key.replace("ip_adapter.", "")] = model[key]
model = st_model
if "ip_adapter" not in model.keys() or len(model["ip_adapter"]) == 0:
return None
o = IPAdapterPatcher(model)
model_filename = Path(ckpt_path).name.lower()
if 'v2' in model_filename:
o.faceid_v2 = True
o.weight_v2 = True
return o
def __init__(self, state_dict):
super().__init__()
self.ip_adapter = state_dict
self.faceid_v2 = False
self.weight_v2 = False
return
def process_before_every_sampling(self, process, cond, mask, *args, **kwargs):
unet = process.sd_model.forge_objects.unet
unet = opIPAdapterApply(
ipadapter=self.ip_adapter,
model=unet,
weight=self.strength,
start_at=self.start_percent,
end_at=self.end_percent,
faceid_v2=self.faceid_v2,
weight_v2=self.weight_v2,
attn_mask=mask.squeeze(1) if mask is not None else None,
**cond,
)[0]
process.sd_model.forge_objects.unet = unet
return
add_supported_control_model(IPAdapterPatcher)
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