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Allow padding in ImageStitch node to be white. (#8631)

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comfyanonymous 2025-06-21 21:19:41 -07:00 committed by GitHub
parent 1883e70b43
commit 78f79266a9
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1 changed files with 17 additions and 13 deletions
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comfy_extras/nodes_images.py
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@ -304,10 +304,23 @@ Optional spacing can be added between images.
image2.movedim(-1, 1), target_w, target_h, "lanczos", "disabled" image2.movedim(-1, 1), target_w, target_h, "lanczos", "disabled"
).movedim(1, -1) ).movedim(1, -1)
color_map = {
"white": 1.0,
"black": 0.0,
"red": (1.0, 0.0, 0.0),
"green": (0.0, 1.0, 0.0),
"blue": (0.0, 0.0, 1.0),
}
color_val = color_map[spacing_color]
# When not matching sizes, pad to align non-concat dimensions # When not matching sizes, pad to align non-concat dimensions
if not match_image_size: if not match_image_size:
h1, w1 = image1.shape[1:3] h1, w1 = image1.shape[1:3]
h2, w2 = image2.shape[1:3] h2, w2 = image2.shape[1:3]
pad_value = 0.0
if not isinstance(color_val, tuple):
pad_value = color_val
if direction in ["left", "right"]: if direction in ["left", "right"]:
# For horizontal concat, pad heights to match # For horizontal concat, pad heights to match
@ -316,11 +329,11 @@ Optional spacing can be added between images.
if h1 < target_h: if h1 < target_h:
pad_h = target_h - h1 pad_h = target_h - h1
pad_top, pad_bottom = pad_h // 2, pad_h - pad_h // 2 pad_top, pad_bottom = pad_h // 2, pad_h - pad_h // 2
image1 = torch.nn.functional.pad(image1, (0, 0, 0, 0, pad_top, pad_bottom), mode='constant', value=0.0) image1 = torch.nn.functional.pad(image1, (0, 0, 0, 0, pad_top, pad_bottom), mode='constant', value=pad_value)
if h2 < target_h: if h2 < target_h:
pad_h = target_h - h2 pad_h = target_h - h2
pad_top, pad_bottom = pad_h // 2, pad_h - pad_h // 2 pad_top, pad_bottom = pad_h // 2, pad_h - pad_h // 2
image2 = torch.nn.functional.pad(image2, (0, 0, 0, 0, pad_top, pad_bottom), mode='constant', value=0.0) image2 = torch.nn.functional.pad(image2, (0, 0, 0, 0, pad_top, pad_bottom), mode='constant', value=pad_value)
else: # up, down else: # up, down
# For vertical concat, pad widths to match # For vertical concat, pad widths to match
if w1 != w2: if w1 != w2:
@ -328,11 +341,11 @@ Optional spacing can be added between images.
if w1 < target_w: if w1 < target_w:
pad_w = target_w - w1 pad_w = target_w - w1
pad_left, pad_right = pad_w // 2, pad_w - pad_w // 2 pad_left, pad_right = pad_w // 2, pad_w - pad_w // 2
image1 = torch.nn.functional.pad(image1, (0, 0, pad_left, pad_right), mode='constant', value=0.0) image1 = torch.nn.functional.pad(image1, (0, 0, pad_left, pad_right), mode='constant', value=pad_value)
if w2 < target_w: if w2 < target_w:
pad_w = target_w - w2 pad_w = target_w - w2
pad_left, pad_right = pad_w // 2, pad_w - pad_w // 2 pad_left, pad_right = pad_w // 2, pad_w - pad_w // 2
image2 = torch.nn.functional.pad(image2, (0, 0, pad_left, pad_right), mode='constant', value=0.0) image2 = torch.nn.functional.pad(image2, (0, 0, pad_left, pad_right), mode='constant', value=pad_value)
# Ensure same number of channels # Ensure same number of channels
if image1.shape[-1] != image2.shape[-1]: if image1.shape[-1] != image2.shape[-1]:
@ -366,15 +379,6 @@ Optional spacing can be added between images.
if spacing_width > 0: if spacing_width > 0:
spacing_width = spacing_width + (spacing_width % 2) # Ensure even spacing_width = spacing_width + (spacing_width % 2) # Ensure even
color_map = {
"white": 1.0,
"black": 0.0,
"red": (1.0, 0.0, 0.0),
"green": (0.0, 1.0, 0.0),
"blue": (0.0, 0.0, 1.0),
}
color_val = color_map[spacing_color]
if direction in ["left", "right"]: if direction in ["left", "right"]:
spacing_shape = ( spacing_shape = (
image1.shape[0], image1.shape[0],