Nuked
86c8e00f8e
- Introduced Llava, moondream, joytag models - Introduced new cliptextencodeAdvanced - Added new output field to video node
109 lines
3.4 KiB
Python
109 lines
3.4 KiB
Python
import torch
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import math
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import numpy as np
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import os
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import random
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MAX_RESOLUTION = 4096
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class ImagePadForOutpaintAdvanced:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"image": ("IMAGE",),
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"left": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
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"top": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
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"right": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
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"bottom": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
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"feathering": ("INT", {"default": 40, "min": 0, "max": MAX_RESOLUTION, "step": 1}),
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"noise_type": ("INT", {"default": 1, "min": 1, "max": 3, "step": 1}),
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}
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}
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RETURN_TYPES = ("IMAGE", "MASK")
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FUNCTION = "expand_image"
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CATEGORY = "image"
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def expand_image(self, image, left, top, right, bottom, feathering,noise_type):
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d1, max_row, max_col, d4 = image.size()
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new_image = torch.zeros(
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(d1, max_row + top + bottom, max_col + left + right, d4),
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dtype=torch.float32,
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)
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new_image[:, top:top + max_row, left:left + max_col, :] = image
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mask = torch.ones(
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(max_row + top + bottom, max_col + left + right),
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dtype=torch.float32,
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)
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t = torch.zeros(
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(max_row, max_col),
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dtype=torch.float32
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)
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if feathering > 0 and feathering * 2 < max_row and feathering * 2 < max_col:
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padding_left = feathering
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padding_right = feathering
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padding_top = feathering
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padding_bottom = feathering
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grow = 0
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#max_row = vertical
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#max_col = horizontal
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for row in range(max_row):
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for col in range(max_col):
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#print(max_row) #768
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#print((max_row - padding + 5)) #743
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if col <= padding_left - grow:
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dt = 0
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elif col >= max_col - padding_right + grow:
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dt = 0
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elif row <= padding_top + grow:
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dt = 0
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elif row >= max_row - padding_bottom + grow:
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dt = 0
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else:
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dt = max_row
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grow += 1
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if grow > padding_left:
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grow=0
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db = max_row
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dl = max_col
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dr = max_col
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d = min(dt, db, dl, dr)
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if d >= feathering:
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continue
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v = (feathering - d) / feathering
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t[row, col] = v * v
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mask[top:top + max_row, left:left + max_col] = t
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return (new_image, mask)
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# A dictionary that contains all nodes you want to export with their names
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# NOTE: names should be globally unique
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NODE_CLASS_MAPPINGS = {
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"ImagePadForOutpaintAdvanced [n-suite]": ImagePadForOutpaintAdvanced
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ImagePadForOutpaintAdvanced [n-suite]": "Image Pad For Outpaint Advanced [🅝-🅢🅤🅘🅣🅔]"
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}
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