Image Analyze

Documentation

• Class name: Image Analyze
• Category: WAS Suite/Image/Analyze
• Output node: False

This node is designed to analyze images by applying specific filters based on the selected mode, such as 'Black White Levels' or 'RGB Levels'. It converts images into a format suitable for analysis, applies the chosen filter, and returns the analyzed image.

Input types

Required

• image
  • The image to be analyzed. It is the primary input for the analysis process.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• mode
  • Determines the type of analysis to be performed on the image, with options including 'Black White Levels' and 'RGB Levels'.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str

Output types

• image
  • Comfy dtype: IMAGE
  • The analyzed image after applying the selected filter.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class WAS_Image_Analyze:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "image": ("IMAGE",),
                "mode": (["Black White Levels", "RGB Levels"],),
            },
        }

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "image_analyze"

    CATEGORY = "WAS Suite/Image/Analyze"

    def image_analyze(self, image, mode='Black White Levels'):

        # Convert images to PIL
        image = tensor2pil(image)

        # WAS Filters
        WTools = WAS_Tools_Class()

        # Analye Image
        if mode:
            if mode == 'Black White Levels':
                image = WTools.black_white_levels(image)
            elif mode == 'RGB Levels':
                image = WTools.channel_frequency(image)
            else:
                image = image

        return (pil2tensor(image), )