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Add a way to disable cropping in the CLIPVisionEncode node.
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@ -16,13 +16,18 @@ class Output:
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def __setitem__(self, key, item):
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setattr(self, key, item)
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def clip_preprocess(image, size=224, mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711]):
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def clip_preprocess(image, size=224, mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711], crop=True):
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mean = torch.tensor(mean, device=image.device, dtype=image.dtype)
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std = torch.tensor(std, device=image.device, dtype=image.dtype)
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image = image.movedim(-1, 1)
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if not (image.shape[2] == size and image.shape[3] == size):
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scale = (size / min(image.shape[2], image.shape[3]))
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image = torch.nn.functional.interpolate(image, size=(round(scale * image.shape[2]), round(scale * image.shape[3])), mode="bicubic", antialias=True)
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if crop:
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scale = (size / min(image.shape[2], image.shape[3]))
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scale_size = (round(scale * image.shape[2]), round(scale * image.shape[3]))
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else:
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scale_size = (size, size)
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image = torch.nn.functional.interpolate(image, size=scale_size, mode="bicubic", antialias=True)
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h = (image.shape[2] - size)//2
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w = (image.shape[3] - size)//2
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image = image[:,:,h:h+size,w:w+size]
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@ -51,9 +56,9 @@ class ClipVisionModel():
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def get_sd(self):
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return self.model.state_dict()
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def encode_image(self, image):
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def encode_image(self, image, crop=True):
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comfy.model_management.load_model_gpu(self.patcher)
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pixel_values = clip_preprocess(image.to(self.load_device), size=self.image_size, mean=self.image_mean, std=self.image_std).float()
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pixel_values = clip_preprocess(image.to(self.load_device), size=self.image_size, mean=self.image_mean, std=self.image_std, crop=crop).float()
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out = self.model(pixel_values=pixel_values, intermediate_output=-2)
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outputs = Output()
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10
nodes.py
10
nodes.py
@ -971,15 +971,19 @@ class CLIPVisionEncode:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "clip_vision": ("CLIP_VISION",),
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"image": ("IMAGE",)
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"image": ("IMAGE",),
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"crop": (["center", "none"],)
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}}
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RETURN_TYPES = ("CLIP_VISION_OUTPUT",)
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FUNCTION = "encode"
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CATEGORY = "conditioning"
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def encode(self, clip_vision, image):
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output = clip_vision.encode_image(image)
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def encode(self, clip_vision, image, crop):
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crop_image = True
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if crop != "center":
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crop_image = False
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output = clip_vision.encode_image(image, crop=crop_image)
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return (output,)
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class StyleModelLoader:
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