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Browse files- src/backend/annotators/canny_control.py +15 -0
- src/backend/annotators/control_interface.py +12 -0
- src/backend/annotators/depth_control.py +15 -0
- src/backend/annotators/image_control_factory.py +31 -0
- src/backend/annotators/lineart_control.py +11 -0
- src/backend/annotators/mlsd_control.py +10 -0
- src/backend/annotators/normal_control.py +10 -0
- src/backend/annotators/pose_control.py +10 -0
- src/backend/annotators/shuffle_control.py +10 -0
- src/backend/annotators/softedge_control.py +10 -0
src/backend/annotators/canny_control.py
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import numpy as np
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from backend.annotators.control_interface import ControlInterface
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from cv2 import Canny
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from PIL import Image
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class CannyControl(ControlInterface):
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def get_control_image(self, image: Image) -> Image:
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low_threshold = 100
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high_threshold = 200
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image = np.array(image)
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image = Canny(image, low_threshold, high_threshold)
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image = image[:, :, None]
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image = np.concatenate([image, image, image], axis=2)
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return Image.fromarray(image)
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src/backend/annotators/control_interface.py
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from abc import ABC, abstractmethod
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from PIL import Image
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class ControlInterface(ABC):
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@abstractmethod
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def get_control_image(
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self,
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image: Image,
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) -> Image:
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pass
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src/backend/annotators/depth_control.py
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import numpy as np
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from backend.annotators.control_interface import ControlInterface
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from PIL import Image
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from transformers import pipeline
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class DepthControl(ControlInterface):
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def get_control_image(self, image: Image) -> Image:
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depth_estimator = pipeline("depth-estimation")
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image = depth_estimator(image)["depth"]
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image = np.array(image)
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image = image[:, :, None]
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image = np.concatenate([image, image, image], axis=2)
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image = Image.fromarray(image)
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return image
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src/backend/annotators/image_control_factory.py
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from backend.annotators.canny_control import CannyControl
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from backend.annotators.depth_control import DepthControl
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from backend.annotators.lineart_control import LineArtControl
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from backend.annotators.mlsd_control import MlsdControl
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from backend.annotators.normal_control import NormalControl
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from backend.annotators.pose_control import PoseControl
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from backend.annotators.shuffle_control import ShuffleControl
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from backend.annotators.softedge_control import SoftEdgeControl
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class ImageControlFactory:
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def create_control(self, controlnet_type: str):
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if controlnet_type == "Canny":
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return CannyControl()
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elif controlnet_type == "Pose":
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return PoseControl()
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elif controlnet_type == "MLSD":
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return MlsdControl()
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elif controlnet_type == "Depth":
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return DepthControl()
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elif controlnet_type == "LineArt":
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return LineArtControl()
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elif controlnet_type == "Shuffle":
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return ShuffleControl()
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elif controlnet_type == "NormalBAE":
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return NormalControl()
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elif controlnet_type == "SoftEdge":
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return SoftEdgeControl()
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else:
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print("Error: Control type not implemented!")
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raise Exception("Error: Control type not implemented!")
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src/backend/annotators/lineart_control.py
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import numpy as np
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from backend.annotators.control_interface import ControlInterface
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from controlnet_aux import LineartDetector
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from PIL import Image
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class LineArtControl(ControlInterface):
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def get_control_image(self, image: Image) -> Image:
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processor = LineartDetector.from_pretrained("lllyasviel/Annotators")
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control_image = processor(image)
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return control_image
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src/backend/annotators/mlsd_control.py
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from backend.annotators.control_interface import ControlInterface
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from controlnet_aux import MLSDdetector
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from PIL import Image
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class MlsdControl(ControlInterface):
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def get_control_image(self, image: Image) -> Image:
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mlsd = MLSDdetector.from_pretrained("lllyasviel/ControlNet")
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image = mlsd(image)
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return image
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src/backend/annotators/normal_control.py
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from backend.annotators.control_interface import ControlInterface
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from controlnet_aux import NormalBaeDetector
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from PIL import Image
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class NormalControl(ControlInterface):
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def get_control_image(self, image: Image) -> Image:
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processor = NormalBaeDetector.from_pretrained("lllyasviel/Annotators")
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control_image = processor(image)
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return control_image
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src/backend/annotators/pose_control.py
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from backend.annotators.control_interface import ControlInterface
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from controlnet_aux import OpenposeDetector
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from PIL import Image
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class PoseControl(ControlInterface):
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def get_control_image(self, image: Image) -> Image:
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openpose = OpenposeDetector.from_pretrained("lllyasviel/ControlNet")
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image = openpose(image)
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return image
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src/backend/annotators/shuffle_control.py
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from backend.annotators.control_interface import ControlInterface
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from controlnet_aux import ContentShuffleDetector
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from PIL import Image
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class ShuffleControl(ControlInterface):
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def get_control_image(self, image: Image) -> Image:
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shuffle_processor = ContentShuffleDetector()
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image = shuffle_processor(image)
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return image
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src/backend/annotators/softedge_control.py
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from backend.annotators.control_interface import ControlInterface
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from controlnet_aux import PidiNetDetector
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from PIL import Image
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class SoftEdgeControl(ControlInterface):
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def get_control_image(self, image: Image) -> Image:
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processor = PidiNetDetector.from_pretrained("lllyasviel/Annotators")
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control_image = processor(image)
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return control_image
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