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Resize and pad image node. (#8636)

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comfyanonymous 2025-06-22 14:59:31 -07:00 committed by GitHub
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commit ae0e7c4dff
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comfy_extras/nodes_images.py
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@ -414,6 +414,62 @@ Optional spacing can be added between images.
concat_dim = 2 if direction in ["left", "right"] else 1
return (torch.cat(images, dim=concat_dim),)
class ResizeAndPadImage:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"image": ("IMAGE",),
"target_width": ("INT", {
"default": 512,
"min": 1,
"max": MAX_RESOLUTION,
"step": 1
}),
"target_height": ("INT", {
"default": 512,
"min": 1,
"max": MAX_RESOLUTION,
"step": 1
}),
"padding_color": (["white", "black"],),
"interpolation": (["area", "bicubic", "nearest-exact", "bilinear", "lanczos"],),
}
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "resize_and_pad"
CATEGORY = "image/transform"
def resize_and_pad(self, image, target_width, target_height, padding_color, interpolation):
batch_size, orig_height, orig_width, channels = image.shape
scale_w = target_width / orig_width
scale_h = target_height / orig_height
scale = min(scale_w, scale_h)
new_width = int(orig_width * scale)
new_height = int(orig_height * scale)
image_permuted = image.permute(0, 3, 1, 2)
resized = comfy.utils.common_upscale(image_permuted, new_width, new_height, interpolation, "disabled")
pad_value = 0.0 if padding_color == "black" else 1.0
padded = torch.full(
(batch_size, channels, target_height, target_width),
pad_value,
dtype=image.dtype,
device=image.device
)
y_offset = (target_height - new_height) // 2
x_offset = (target_width - new_width) // 2
padded[:, :, y_offset:y_offset + new_height, x_offset:x_offset + new_width] = resized
output = padded.permute(0, 2, 3, 1)
return (output,)
class SaveSVGNode:
"""
@ -536,5 +592,6 @@ NODE_CLASS_MAPPINGS = {
"SaveAnimatedPNG": SaveAnimatedPNG,
"SaveSVGNode": SaveSVGNode,
"ImageStitch": ImageStitch,
"ResizeAndPadImage": ResizeAndPadImage,
"GetImageSize": GetImageSize,
}