nodes/lquesada-ComfyUI-Inpaint-CropAndStitch
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Re-add padding now that it works

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This commit is contained in:
Luis Quesada
2024-05-13 15:16:20 +02:00
parent 004ecd77dd
commit 317891d12b
1 changed files with 44 additions and 57 deletions
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inpaint_cropandstitch.py
+44 -57
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@@ -1,4 +1,5 @@
import comfy.utils
import math
import nodes
import numpy as np
import torch
@@ -29,7 +30,7 @@ class InpaintCrop:
"preferred_sizes": ("STRING", {"default": "1024"}),
"prefer_square_size": ("BOOLEAN", {"default": False}),
"internal_upscale_factor": ("FLOAT", {"default": 1.00, "min": 0.01, "max": 100.0, "step": 0.01}),
# "padding": ("INT", {"default": 32, "min": 0, "max": nodes.MAX_RESOLUTION, "step": 1}),
"padding": ("INT", {"default": 32, "min": 0, "max": nodes.MAX_RESOLUTION, "step": 1}),
},
"optional": {
"optional_context_mask": ("MASK",),
@@ -60,43 +61,34 @@ class InpaintCrop:
return new_min, new_max
def apply_padding(self, min_val, max_val, max_boundary, padding):
range_size = max_val - min_val + 1
if range_size % padding != 0:
increment = padding - (range_size % padding)
decrement = range_size % padding
# Calculate potential new max values for both expanding and contracting
expand_new_max_val = max_val + increment
contract_new_max_val = max_val - decrement
# Calculate the midpoint and the original range size
original_range_size = max_val - min_val + 1
midpoint = (min_val + max_val) // 2
# Choose to expand or contract based on boundary conditions
if expand_new_max_val < max_boundary and (min_val - (increment // 2) >= 0):
# Expand the range and adjust min and max equally
new_min_val = min_val - (increment // 2)
new_max_val = max_val + (increment // 2)
# If increment is odd, add the remaining to max_val
if increment % 2 != 0:
new_max_val += 1
else:
# Contract the range equally
new_min_val = min_val + (decrement // 2)
new_max_val = max_val - (decrement // 2)
# If decrement is odd, subtract the remaining from max_val
if decrement % 2 != 0:
new_max_val -= 1
# Ensure new_min_val and new_max_val are within bounds
if new_min_val < 0:
new_min_val = 0
if new_max_val >= max_boundary:
new_max_val = max_boundary - 1
return new_min_val, new_max_val
# Determine the smallest multiple of padding that is >= original_range_size
if original_range_size % padding == 0:
new_range_size = original_range_size
else:
return min_val, max_val
new_range_size = (original_range_size // padding + 1) * padding
# Calculate the new min and max values centered on the midpoint
new_min_val = max(midpoint - new_range_size // 2, 0)
new_max_val = new_min_val + new_range_size - 1
# Ensure the new max doesn't exceed the boundary
if new_max_val >= max_boundary:
new_max_val = max_boundary - 1
new_min_val = max(new_max_val - new_range_size + 1, 0)
# Ensure the range still ends on a multiple of padding
# Adjust if the calculated range isn't feasible within the given constraints
if (new_max_val - new_min_val + 1) != new_range_size:
new_min_val = max(new_max_val - new_range_size + 1, 0)
return new_min_val, new_max_val
# Parts of this function are from KJNodes: https://github.com/kijai/ComfyUI-KJNodes
def inpaint_crop(self, image, mask, context_expand_pixels, context_expand_factor, invert_mask, grow_mask_pixels, fill_holes, blur_radius_pixels, adjust_to_preferred_sizes, preferred_sizes, prefer_square_size, internal_upscale_factor, optional_context_mask = None): #TODO padding
def inpaint_crop(self, image, mask, context_expand_pixels, context_expand_factor, invert_mask, grow_mask_pixels, fill_holes, blur_radius_pixels, adjust_to_preferred_sizes, preferred_sizes, prefer_square_size, internal_upscale_factor, padding, optional_context_mask = None):
original_image = image
original_mask = mask
original_width = image.shape[2]
@@ -176,19 +168,6 @@ class InpaintCrop:
x_min = max(x_min - x_grow // 2, 0)
x_max = min(x_max + x_grow // 2, width - 1)
# TODO Pad area (if possible) to avoid the sampler returning smaller results
#if padding > 1:
# x_min, x_max = self.apply_padding(x_min, x_max, width, padding)
# y_min, y_max = self.apply_padding(y_min, y_max, height, padding)
# Limit to max image size
y_min = max(y_min, 0)
y_max = min(y_max, height - 1)
x_min = max(x_min, 0)
x_max = min(x_max, width - 1)
y_size = y_max - y_min + 1
x_size = x_max - x_min + 1
# Adjust to the smallest preferred size larger than the current size if possible
if adjust_to_preferred_sizes:
preferred_sizes_parsed = [int(size) for size in preferred_sizes.split(',')]
@@ -238,17 +217,25 @@ class InpaintCrop:
samples = samples.squeeze(1)
mask = samples
x_min = round(x_min * effective_upscale_factor_x)
x_max = round(x_max * effective_upscale_factor_x)
y_min = round(y_min * effective_upscale_factor_y)
y_max = round(y_max * effective_upscale_factor_y)
x_min = math.floor(x_min * effective_upscale_factor_x)
x_max = math.ceil(x_max * effective_upscale_factor_x)
y_min = math.floor(y_min * effective_upscale_factor_y)
y_max = math.ceil(y_max * effective_upscale_factor_y)
if optional_context_mask is not None:
samples = optional_context_mask
samples = samples.unsqueeze(1)
samples = comfy.utils.bislerp(samples, width, height)
samples = samples.squeeze(1)
optional_context_mask = samples
# Pad area (if possible) to avoid the sampler returning smaller results
width = image.shape[2]
height = image.shape[1]
if padding > 1:
x_min, x_max = self.apply_padding(x_min, x_max, width, padding)
y_min, y_max = self.apply_padding(y_min, y_max, height, padding)
# Ensure that they don't go outside of the image
x_min = max(x_min, 0)
x_max = min(x_max, width - 1)
y_min = max(y_min, 0)
y_max = min(y_max, height - 1)
x_size = x_max - x_min + 1
y_size = y_max - y_min + 1
# Crop the image and the mask, sized context area
cropped_image = image[:, y_min:y_max+1, x_min:x_max+1]