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rename node category

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This commit is contained in:
Tung Nguyen
2025-11-04 15:43:03 +07:00
parent f37981bffb
commit 1138a1f4d9
15 changed files with 105 additions and 102 deletions
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modules/inpaint/nodes.py
+7 -4
View File
@@ -27,7 +27,7 @@ class PrepareImageAndMaskForInpaint:
},
"optional": {
"controlnet_image": ("IMAGE",),
}
},
}
RETURN_TYPES = ("IMAGE", "MASK", "IMAGE", "CROP_REGION", "IMAGE")
@@ -89,7 +89,9 @@ class PrepareImageAndMaskForInpaint:
cropped_mask = pil_mask.crop(crop_region)
final_pil_img = resize_image(cropped_img, out_width, out_height, ResizeMode.RESIZE_TO_FIT)
final_pil_mask = resize_image(cropped_mask, out_width, out_height, ResizeMode.RESIZE_TO_FIT).convert("L")
final_pil_mask = resize_image(cropped_mask, out_width, out_height, ResizeMode.RESIZE_TO_FIT).convert(
"L"
)
if controlnet_image is not None:
pil_cimg = tensor2pil(controlnet_image[idx])
@@ -103,7 +105,9 @@ class PrepareImageAndMaskForInpaint:
x1, y1, x2, y2 = crop_region
cn_crop_region = (int(x1 * scale_x), int(y1 * scale_y), int(x2 * scale_x), int(y2 * scale_y))
cropped_cn_img = pil_cimg.crop(cn_crop_region)
final_cn_img = resize_image(cropped_cn_img, cn_target_width, cn_target_height, ResizeMode.RESIZE_TO_FIT)
final_cn_img = resize_image(
cropped_cn_img, cn_target_width, cn_target_height, ResizeMode.RESIZE_TO_FIT
)
processed_controlnet_images.append(pil2tensor(final_cn_img))
else:
@@ -129,7 +133,6 @@ class PrepareImageAndMaskForInpaint:
masks.append(pil2tensor(final_pil_mask))
crop_regions.append(torch.tensor(crop_region, dtype=torch.int64))
if processed_controlnet_images:
final_controlnet_tensor = torch.cat(processed_controlnet_images, dim=0)
else:
modules/postprocessing/color_blend.py
+3 -9
View File
@@ -41,13 +41,9 @@ class ColorBlend:
def color_blending_mode(self, bw_layer, color_layer):
if bw_layer.shape[0] < color_layer.shape[0]:
bw_layer = bw_layer.repeat(color_layer.shape[0], 1, 1, 1)[
: color_layer.shape[0]
]
bw_layer = bw_layer.repeat(color_layer.shape[0], 1, 1, 1)[: color_layer.shape[0]]
if bw_layer.shape[0] > color_layer.shape[0]:
color_layer = color_layer.repeat(bw_layer.shape[0], 1, 1, 1)[
: bw_layer.shape[0]
]
color_layer = color_layer.repeat(bw_layer.shape[0], 1, 1, 1)[: bw_layer.shape[0]]
batch_size, *_ = bw_layer.shape
tensor_output = torch.empty_like(bw_layer)
@@ -70,8 +66,6 @@ class ColorBlend:
for i in range(batch_size):
blend = color_blend(image1[i], image2[i])
blend = np.stack([blend])
tensor_output[i : i + 1] = (
torch.from_numpy(blend.transpose(0, 3, 1, 2)) / 255.0
).permute(0, 2, 3, 1)
tensor_output[i : i + 1] = (torch.from_numpy(blend.transpose(0, 3, 1, 2)) / 255.0).permute(0, 2, 3, 1)
return (tensor_output,)
modules/utility_nodes.py
+10 -4
View File
@@ -161,12 +161,15 @@ class UtilLoadImageFromUrl:
def INPUT_TYPES(cls):
return {
"required": {
"image": ("STRING", {
"image": (
"STRING",
{
"default": "",
"placeholder": "Input image paths or URLS one per line. Eg:\nhttps://example.com/image.png\nfile:///path/to/local/image.jpg\ndata:image/png;base64,...",
"multiline": True,
"dynamicPrompts": False,
}),
},
),
},
"optional": {
"keep_alpha_channel": (
@@ -243,12 +246,15 @@ class UtilLoadImageAsMaskFromUrl(UtilLoadImageFromUrl):
def INPUT_TYPES(cls):
return {
"required": {
"image": ("STRING", {
"image": (
"STRING",
{
"default": "",
"placeholder": "Input image paths or URLS one per line. Eg:\nhttps://example.com/image.png\nfile:///path/to/local/image.jpg\ndata:image/png;base64,...",
"multiline": True,
"dynamicPrompts": False,
}),
},
),
"channel": (["alpha", "red", "green", "blue"],),
},
"optional": {