EqualizeHistogram

Documentation

• Class name: EqualizeHistogram
• Category: Bmad/CV/Thresholding
• Output node: False

The EqualizeHistogram node is designed to enhance the contrast of an image by equalizing its histogram. This process redistributes the intensity levels of the image, potentially improving its visual perception.

Input types

Required

• src
  • The source image to be processed for histogram equalization. This input is crucial as it directly influences the enhancement of the image's contrast.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor

Output types

• image
  • Comfy dtype: IMAGE
  • The output is an enhanced image with equalized histogram, aimed at improving the contrast and visual quality.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class EqualizeHistogram:
    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "src": ("IMAGE",),
            },
        }

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "eq"
    CATEGORY = f"{cv_category_path}/Thresholding"

    def eq(self, src):
        src = tensor2opencv(src, 1)
        eq = cv.equalizeHist(src)
        eq = cv.cvtColor(eq, cv.COLOR_GRAY2RGB)
        eq = opencv2tensor(eq)
        return (eq,)