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feat(mm): probe for main model default settings

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Currently, this is just the width and height, derived from the model base.
This commit is contained in:
psychedelicious 2024-03-13 09:49:12 +11:00
parent 2584a950aa
commit 3fd824306c
1 changed files with 45 additions and 37 deletions
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82
invokeai/backend/model_manager/probe.py
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@ -17,6 +17,7 @@ from .config import (
BaseModelType,
ControlAdapterDefaultSettings,
InvalidModelConfigException,
MainModelDefaultSettings,
ModelConfigFactory,
ModelFormat,
ModelRepoVariant,
@ -160,11 +161,13 @@ class ModelProbe(object):
fields["format"] = fields.get("format") or probe.get_format()
fields["hash"] = fields.get("hash") or ModelHash(algorithm=hash_algo).hash(model_path)
fields["default_settings"] = (
fields.get("default_settings") or probe.get_default_settings(fields["name"])
if isinstance(probe, ControlAdapterProbe)
else None
)
fields["default_settings"] = fields.get("default_settings")
if not fields["default_settings"]:
if fields["type"] in {ModelType.ControlNet, ModelType.T2IAdapter}:
fields["default_settings"] = get_default_settings_controlnet_t2i_adapter(fields["name"])
elif fields["type"] is ModelType.Main:
fields["default_settings"] = get_default_settings_main(fields["base"])
if format_type == ModelFormat.Diffusers and isinstance(probe, FolderProbeBase):
fields["repo_variant"] = fields.get("repo_variant") or probe.get_repo_variant()
@ -336,36 +339,41 @@ class ModelProbe(object):
raise Exception("The model {model_name} is potentially infected by malware. Aborting import.")
class ControlAdapterProbe(ProbeBase):
"""Adds `get_default_settings` for ControlNet and T2IAdapter probes"""
# Probing utilities
MODEL_NAME_TO_PREPROCESSOR = {
"canny": "canny_image_processor",
"mlsd": "mlsd_image_processor",
"depth": "depth_anything_image_processor",
"bae": "normalbae_image_processor",
"normal": "normalbae_image_processor",
"sketch": "pidi_image_processor",
"scribble": "lineart_image_processor",
"lineart": "lineart_image_processor",
"lineart_anime": "lineart_anime_image_processor",
"softedge": "hed_image_processor",
"shuffle": "content_shuffle_image_processor",
"pose": "dw_openpose_image_processor",
"mediapipe": "mediapipe_face_processor",
"pidi": "pidi_image_processor",
"zoe": "zoe_depth_image_processor",
"color": "color_map_image_processor",
}
# TODO(psyche): It would be nice to get these from the invocations, but that creates circular dependencies.
# "canny": CannyImageProcessorInvocation.get_type()
MODEL_NAME_TO_PREPROCESSOR = {
"canny": "canny_image_processor",
"mlsd": "mlsd_image_processor",
"depth": "depth_anything_image_processor",
"bae": "normalbae_image_processor",
"normal": "normalbae_image_processor",
"sketch": "pidi_image_processor",
"scribble": "lineart_image_processor",
"lineart": "lineart_image_processor",
"lineart_anime": "lineart_anime_image_processor",
"softedge": "hed_image_processor",
"shuffle": "content_shuffle_image_processor",
"pose": "dw_openpose_image_processor",
"mediapipe": "mediapipe_face_processor",
"pidi": "pidi_image_processor",
"zoe": "zoe_depth_image_processor",
"color": "color_map_image_processor",
}
@classmethod
def get_default_settings(cls, model_name: str) -> Optional[ControlAdapterDefaultSettings]:
for k, v in cls.MODEL_NAME_TO_PREPROCESSOR.items():
if k in model_name:
return ControlAdapterDefaultSettings(preprocessor=v)
return None
def get_default_settings_controlnet_t2i_adapter(model_name: str) -> Optional[ControlAdapterDefaultSettings]:
for k, v in MODEL_NAME_TO_PREPROCESSOR.items():
if k in model_name:
return ControlAdapterDefaultSettings(preprocessor=v)
return None
def get_default_settings_main(model_base: BaseModelType) -> Optional[MainModelDefaultSettings]:
if model_base is BaseModelType.StableDiffusion1 or model_base is BaseModelType.StableDiffusion2:
return MainModelDefaultSettings(width=512, height=512)
elif model_base is BaseModelType.StableDiffusionXL:
return MainModelDefaultSettings(width=1024, height=1024)
# We don't provide defaults for BaseModelType.StableDiffusionXLRefiner, as they are not standalone models.
return None
# ##################################################3
@ -491,7 +499,7 @@ class TextualInversionCheckpointProbe(CheckpointProbeBase):
raise InvalidModelConfigException(f"{self.model_path}: Could not determine base type")
class ControlNetCheckpointProbe(CheckpointProbeBase, ControlAdapterProbe):
class ControlNetCheckpointProbe(CheckpointProbeBase):
"""Class for probing controlnets."""
def get_base_type(self) -> BaseModelType:
@ -519,7 +527,7 @@ class CLIPVisionCheckpointProbe(CheckpointProbeBase):
raise NotImplementedError()
class T2IAdapterCheckpointProbe(CheckpointProbeBase, ControlAdapterProbe):
class T2IAdapterCheckpointProbe(CheckpointProbeBase):
def get_base_type(self) -> BaseModelType:
raise NotImplementedError()
@ -657,7 +665,7 @@ class ONNXFolderProbe(PipelineFolderProbe):
return ModelVariantType.Normal
class ControlNetFolderProbe(FolderProbeBase, ControlAdapterProbe):
class ControlNetFolderProbe(FolderProbeBase):
def get_base_type(self) -> BaseModelType:
config_file = self.model_path / "config.json"
if not config_file.exists():
@ -731,7 +739,7 @@ class CLIPVisionFolderProbe(FolderProbeBase):
return BaseModelType.Any
class T2IAdapterFolderProbe(FolderProbeBase, ControlAdapterProbe):
class T2IAdapterFolderProbe(FolderProbeBase):
def get_base_type(self) -> BaseModelType:
config_file = self.model_path / "config.json"
if not config_file.exists():