Image Size to Number¶
Documentation¶
- Class name:
Image Size to Number
- Category:
WAS Suite/Number/Operations
- Output node:
False
This node is designed to convert the dimensions of an image into numerical values, providing both integer and floating-point representations of the image's width and height.
Input types¶
Required¶
image
- The input image for which the width and height are to be determined and converted into numerical values.
- Comfy dtype:
IMAGE
- Python dtype:
torch.Tensor
Output types¶
width_num
- Comfy dtype:
NUMBER
- The width of the image as a numerical value.
- Python dtype:
int
- Comfy dtype:
height_num
- Comfy dtype:
NUMBER
- The height of the image as a numerical value.
- Python dtype:
int
- Comfy dtype:
width_float
- Comfy dtype:
FLOAT
- The width of the image represented as a floating-point number.
- Python dtype:
float
- Comfy dtype:
height_float
- Comfy dtype:
FLOAT
- The height of the image represented as a floating-point number.
- Python dtype:
float
- Comfy dtype:
width_int
- Comfy dtype:
INT
- The width of the image represented as an integer.
- Python dtype:
int
- Comfy dtype:
height_int
- Comfy dtype:
INT
- The height of the image represented as an integer.
- Python dtype:
int
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes:
Source code¶
class WAS_Image_Size_To_Number:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"image": ("IMAGE",),
}
}
RETURN_TYPES = ("NUMBER", "NUMBER", "FLOAT", "FLOAT", "INT", "INT")
RETURN_NAMES = ("width_num", "height_num", "width_float", "height_float", "width_int", "height_int")
FUNCTION = "image_width_height"
CATEGORY = "WAS Suite/Number/Operations"
def image_width_height(self, image):
image = tensor2pil(image)
if image.size:
return( image.size[0], image.size[1], float(image.size[0]), float(image.size[1]), image.size[0], image.size[1] )
return ( 0, 0, 0, 0, 0, 0)