Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

Added Mediapipe image processor for use as ControlNet preprocessor.

Browse Source 
Also hacked in ability to specify HF subfolder when loading ControlNet models from string.
This commit is contained in:
user1 2023-05-23 16:21:13 -07:00 committed by Kent Keirsey
parent be79d088c0
commit 8960ceb98b
2 changed files with 31 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
invokeai/app/invocations/controlnet_image_processors.py
View File

@ -84,9 +84,11 @@ CONTROLNET_DEFAULT_MODELS = [
##############################################
# ControlNetMediaPipeface, ControlNet v1.1
##############################################
"CrucibleAI/ControlNetMediaPipeFace",# SD 2.1?
# diffusion_sd15 needs to be passed to from_pretrained() as subfolder arg
# ["CrucibleAI/ControlNetMediaPipeFace", "diffusion_sd15"], # SD 1.5
# diffusion_sd15 needs to be passed to from_pretrained() as subfolder arg
# hacked t2l to split to model & subfolder if format is "model,subfolder"
"CrucibleAI/ControlNetMediaPipeFace,diffusion_sd15", # SD 1.5
"CrucibleAI/ControlNetMediaPipeFace", # SD 2.1?
]
CONTROLNET_NAME_VALUES = Literal[tuple(CONTROLNET_DEFAULT_MODELS)]
@ -403,3 +405,17 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation, PILInvoca
# processed_image = zoe_depth_processor(image)
# return processed_image
class MediapipeFaceProcessorInvocation(ImageProcessorInvocation, PILInvocationConfig):
"""Applies mediapipe face processing to image"""
# fmt: off
type: Literal["mediapipe_face_processor"] = "mediapipe_face_processor"
# Inputs
max_faces: int = Field(default=1, ge=1, description="maximum number of faces to detect")
min_confidence: float = Field(default=0.5, ge=0, le=1, description="minimum confidence for face detection")
# fmt: on
def run_processor(self, image):
mediapipe_face_processor = MediapipeFaceDetector()
processed_image = mediapipe_face_processor(image)
return processed_image

11
invokeai/app/invocations/latent.py
View File

@ -277,6 +277,17 @@ class TextToLatentsInvocation(BaseInvocation):
control_models = []
for control_info in control_list:
# handle control models
if ("," in control_info.control_model):
control_model_split = control_info.control_model.split(",")
control_name = control_model_split[0]
control_subfolder = control_model_split[1]
print("Using HF model subfolders")
print(" control_name: ", control_name)
print(" control_subfolder: ", control_subfolder)
control_model = ControlNetModel.from_pretrained(control_name,
subfolder=control_subfolder,
torch_dtype=model.unet.dtype).to(model.device)
else:
control_model = ControlNetModel.from_pretrained(control_info.control_model,
torch_dtype=model.unet.dtype).to(model.device)
control_models.append(control_model)