NearestSDXLResolution¶
Documentation¶
- Class name:
CM_NearestSDXLResolution
- Category:
math/graphics
- Output node:
False
This node is designed to find the nearest supported SDXL resolution to the input image's resolution. It calculates the aspect ratio of the input image and compares it with a list of supported SDXL resolutions to select the closest match, ensuring optimal resizing without significant distortion.
Input types¶
Required¶
image
- The input image for which the nearest SDXL resolution is to be found. The image's aspect ratio is used to determine the closest supported resolution.
- Comfy dtype:
IMAGE
- Python dtype:
torch.Tensor
Output types¶
width
- Comfy dtype:
INT
- The width component of the nearest SDXL resolution.
- Python dtype:
int
- Comfy dtype:
height
- Comfy dtype:
INT
- The height component of the nearest SDXL resolution.
- Python dtype:
int
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes:
- ConstrainImage|pysssss
- Reroute
- ImageScale
Source code¶
class NearestSDXLResolution:
@classmethod
def INPUT_TYPES(cls) -> Mapping[str, Any]:
return {"required": {"image": ("IMAGE",)}}
RETURN_TYPES = ("INT", "INT")
RETURN_NAMES = ("width", "height")
FUNCTION = "op"
CATEGORY = "math/graphics"
def op(self, image) -> tuple[int, int]:
image_width = image.size()[2]
image_height = image.size()[1]
print(f"Input image resolution: {image_width}x{image_height}")
image_ratio = image_width / image_height
differences = [
(abs(image_ratio - resolution[2]), resolution)
for resolution in SDXL_SUPPORTED_RESOLUTIONS
]
smallest = None
for difference in differences:
if smallest is None:
smallest = difference
else:
if difference[0] < smallest[0]:
smallest = difference
if smallest is not None:
width = smallest[1][0]
height = smallest[1][1]
else:
width = 1024
height = 1024
print(f"Selected SDXL resolution: {width}x{height}")
return (width, height)