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update
Browse files- diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_canny.py +1 -1
- diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_depth.py +1 -2
- diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_hed.py +1 -1
- diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_mlsd.py +1 -1
- diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_pose.py +1 -1
- diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_scribble.py +1 -1
- diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_seg.py +1 -2
diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_canny.py
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@@ -42,7 +42,7 @@ class StableDiffusionControlNetInpaintCannyGenerator:
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(
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return image
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def controlnet_canny_inpaint(
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(image)
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return image
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def controlnet_canny_inpaint(
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diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_depth.py
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@@ -42,10 +42,9 @@ class StableDiffusionControlInpaintNetDepthGenerator:
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(
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return image
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-
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def controlnet_inpaint_depth(self, image_path: str):
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depth_estimator = pipeline("depth-estimation")
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image = image_path["image"].convert("RGB").resize((512, 512))
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(image)
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return image
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def controlnet_inpaint_depth(self, image_path: str):
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depth_estimator = pipeline("depth-estimation")
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image = image_path["image"].convert("RGB").resize((512, 512))
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diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_hed.py
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@@ -42,7 +42,7 @@ class StableDiffusionControlNetInpaintHedGenerator:
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(
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return image
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(image)
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return image
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diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_mlsd.py
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@@ -42,7 +42,7 @@ class StableDiffusionControlNetInpaintMlsdGenerator:
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(
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return image
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(image)
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return image
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diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_pose.py
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@@ -43,7 +43,7 @@ class StableDiffusionControlNetInpaintPoseGenerator:
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(
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return image
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def controlnet_pose_inpaint(self, image_path: str):
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(image)
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return image
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def controlnet_pose_inpaint(self, image_path: str):
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diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_scribble.py
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@@ -42,7 +42,7 @@ class StableDiffusionControlNetInpaintScribbleGenerator:
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(
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return image
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def controlnet_inpaint_scribble(self, image_path: str):
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(image)
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return image
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def controlnet_inpaint_scribble(self, image_path: str):
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diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_seg.py
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@@ -203,9 +203,8 @@ class StableDiffusionControlNetInpaintSegGenerator:
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(
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return image
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def controlnet_seg_inpaint(self, image_path: str):
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image_processor = AutoImageProcessor.from_pretrained(
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"openmmlab/upernet-convnext-small"
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def load_image(self, image_path):
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image = np.array(image_path)
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image = Image.fromarray(image)
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return image
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def controlnet_seg_inpaint(self, image_path: str):
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image_processor = AutoImageProcessor.from_pretrained(
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"openmmlab/upernet-convnext-small"
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