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qwen inpaint : use input image size while still matching VAE packing requirements

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This commit is contained in:
Mohamed Oumoumad 2025-10-12 22:26:11 +02:00
parent 4f4f46dcbe
commit 69493cff50
1 changed files with 19 additions and 16 deletions
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35
comfy_extras/nodes_qwen.py
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@ -5,18 +5,6 @@ import torch
from typing_extensions import override from typing_extensions import override
from comfy_api.latest import ComfyExtension, io from comfy_api.latest import ComfyExtension, io
def calculate_dimensions(target_area: float, ratio: float) -> tuple[int, int]:
if ratio <= 0:
# fallback to square
width = height = math.sqrt(target_area)
else:
width = math.sqrt(target_area * ratio)
height = width / ratio
width = max(1, round(width / 32) * 32)
height = max(1, round(height / 32) * 32)
return int(width), int(height)
class TextEncodeQwenImageEdit(io.ComfyNode): class TextEncodeQwenImageEdit(io.ComfyNode):
@classmethod @classmethod
@ -89,14 +77,23 @@ class QwenImageInpaintConditioning(io.ComfyNode):
) )
@classmethod @classmethod
def execute(cls, positive, negative, vae, image, mask, use_noise_mask=True) -> io.NodeOutput: def execute(
cls,
positive,
negative,
vae,
image,
mask,
use_noise_mask=True,
) -> io.NodeOutput:
if image.ndim != 4: if image.ndim != 4:
raise ValueError("Expected image tensor with shape [B, H, W, C].") raise ValueError("Expected image tensor with shape [B, H, W, C].")
image = image[:, :, :, :3] image = image[:, :, :, :3]
batch, height, width, _ = image.shape batch, height, width, _ = image.shape
target_width, target_height = calculate_dimensions(1024 * 1024, width / height if height > 0 else 1.0) requested_width = float(width)
requested_height = float(height)
spacial_scale = vae.spacial_compression_encode() spacial_scale = vae.spacial_compression_encode()
if isinstance(spacial_scale, tuple): if isinstance(spacial_scale, tuple):
@ -104,8 +101,14 @@ class QwenImageInpaintConditioning(io.ComfyNode):
spacial_scale = int(spacial_scale) spacial_scale = int(spacial_scale)
align_multiple = max(1, spacial_scale * 2) align_multiple = max(1, spacial_scale * 2)
target_width = max(align_multiple, round(target_width / align_multiple) * align_multiple) target_width = max(
target_height = max(align_multiple, round(target_height / align_multiple) * align_multiple) align_multiple,
round(requested_width / align_multiple) * align_multiple,
)
target_height = max(
align_multiple,
round(requested_height / align_multiple) * align_multiple,
)
samples = image.movedim(-1, 1) samples = image.movedim(-1, 1)
resized = comfy.utils.common_upscale(samples, target_width, target_height, "area", "disabled") resized = comfy.utils.common_upscale(samples, target_width, target_height, "area", "disabled")