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Handle inpainting training for control_lora adapter

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This commit is contained in:
Jaret Burkett
2025-03-24 13:17:47 -06:00
parent f10937e6da
commit 45be82d5d6
9 changed files with 257 additions and 23 deletions
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12
toolkit/config_modules.py
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@@ -165,7 +165,13 @@ class AdapterConfig:
self.downscale_factor: int = kwargs.get('downscale_factor', 8)
self.adapter_type: str = kwargs.get('adapter_type', 'full_adapter')
self.image_dir: str = kwargs.get('image_dir', None)
self.test_img_path: str = kwargs.get('test_img_path', None)
self.test_img_path: List[str] = kwargs.get('test_img_path', None)
if self.test_img_path is not None:
if isinstance(self.test_img_path, str):
self.test_img_path = self.test_img_path.split(',')
self.test_img_path = [p.strip() for p in self.test_img_path]
self.test_img_path = [p for p in self.test_img_path if p != '']
self.train: str = kwargs.get('train', False)
self.image_encoder_path: str = kwargs.get('image_encoder_path', None)
self.name_or_path = kwargs.get('name_or_path', None)
@@ -244,6 +250,7 @@ class AdapterConfig:
self.num_control_images: int = kwargs.get('num_control_images', 1)
# decimal for how often the control is dropped out and replaced with noise 1.0 is 100%
self.control_image_dropout: float = kwargs.get('control_image_dropout', 0.0)
self.has_inpainting_input: bool = kwargs.get('has_inpainting_input', False)
class EmbeddingConfig:
@@ -714,6 +721,9 @@ class DatasetConfig:
self.flip_y: bool = kwargs.get('flip_y', False)
self.augments: List[str] = kwargs.get('augments', [])
self.control_path: Union[str,List[str]] = kwargs.get('control_path', None) # depth maps, etc
# inpaint images should be webp/png images with alpha channel. The alpha 0 (invisible) section will
# be the part conditioned to be inpainted. The alpha 1 (visible) section will be the part that is ignored
self.inpaint_path: Union[str,List[str]] = kwargs.get('inpaint_path', None)
# instead of cropping ot match image, it will serve the full size control image (clip images ie for ip adapters)
self.full_size_control_images: bool = kwargs.get('full_size_control_images', False)
self.alpha_mask: bool = kwargs.get('alpha_mask', False) # if true, will use alpha channel as mask