Image Monitor Effects Filter

Documentation

• Class name: Image Monitor Effects Filter
• Category: WAS Suite/Image/Filter
• Output node: False

This node applies various monitor effect filters to an image, simulating digital, signal, and TV distortions. It allows for customization of the distortion intensity and offset, providing a versatile tool for creating visually unique images.

Input types

Required

• image
  • The input image to which the monitor effect filters will be applied. It serves as the base for the distortion effects.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor
• mode
  • Specifies the type of distortion effect to apply: Digital Distortion, Signal Distortion, or TV Distortion. This choice determines the visual style of the output image.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• amplitude
  • Controls the intensity of the distortion effect. A higher value results in more pronounced distortions.
  • Comfy dtype: INT
  • Python dtype: int
• offset
  • Adjusts the offset of the distortion effect, allowing for further customization of the visual outcome.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • The output image after applying the selected monitor effect filter. It showcases the visual distortions as specified by the input parameters.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class WAS_Image_Monitor_Distortion_Filter:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "image": ("IMAGE",),
                "mode": (["Digital Distortion", "Signal Distortion", "TV Distortion"],),
                "amplitude": ("INT", {"default": 5, "min": 1, "max": 255, "step": 1}),
                "offset": ("INT", {"default": 10, "min": 1, "max": 255, "step": 1}),
            },
        }

    RETURN_TYPES = ("IMAGE",)
    RETURN_NAMES = ("image",)
    FUNCTION = "image_monitor_filters"

    CATEGORY = "WAS Suite/Image/Filter"

    def image_monitor_filters(self, image, mode="Digital Distortion", amplitude=5, offset=5):

        # Convert images to PIL
        image = tensor2pil(image)

        # WAS Filters
        WTools = WAS_Tools_Class()

        # Apply image effect
        if mode:
            if mode == 'Digital Distortion':
                image = WTools.digital_distortion(image, amplitude, offset)
            elif mode == 'Signal Distortion':
                image = WTools.signal_distortion(image, amplitude)
            elif mode == 'TV Distortion':
                image = WTools.tv_vhs_distortion(image, amplitude)
            else:
                image = image

        return (pil2tensor(image), )