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[pull] master from comfyanonymous:master #134

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Merged
pull merged 1 commit into from
Jun 22, 2025
Merged

[pull] master from comfyanonymous:master #134

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30 changes: 17 additions & 13 deletions comfy_extras/nodes_images.py
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Original file line number Diff line number Diff line change
Expand Up @@ -304,10 +304,23 @@ def stitch(
image2.movedim(-1, 1), target_w, target_h, "lanczos", "disabled"
).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
if not match_image_size:
h1, w1 = image1.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"]:
# For horizontal concat, pad heights to match
Expand All @@ -316,23 +329,23 @@ def stitch(
if h1 < target_h:
pad_h = target_h - h1
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:
pad_h = target_h - h2
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
# For vertical concat, pad widths to match
if w1 != w2:
target_w = max(w1, w2)
if w1 < target_w:
pad_w = target_w - w1
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:
pad_w = target_w - w2
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
if image1.shape[-1] != image2.shape[-1]:
Expand Down Expand Up @@ -366,15 +379,6 @@ def stitch(
if spacing_width > 0:
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"]:
spacing_shape = (
image1.shape[0],
Expand Down
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