nodes/tritant-ComfyUI_Layers_Utility
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update ui

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tritant
2025-08-10 02:03:39 +02:00
committed by GitHub
parent 6efa47b48d
commit 901a0e457b
1 changed files with 63 additions and 29 deletions
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layer_system_final.py
+63 -29
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@@ -20,13 +20,9 @@ def start_preview_server():
def __init__(self, *args, **kwargs):
super().__init__(*args, directory=folder_paths.get_temp_directory(), **kwargs)
# --- AJOUT CRUCIAL ICI ---
# Cette méthode ajoute l'en-tête nécessaire pour autoriser le chargement des images
# par le script JavaScript du canvas.
def end_headers(self):
self.send_header('Access-Control-Allow-Origin', '*')
super().end_headers()
# --- FIN DE L'AJOUT ---
def do_GET(self):
if self.path == '/' or self.path.endswith('/'):
@@ -38,7 +34,6 @@ def start_preview_server():
return
address = ("127.0.0.1", PREVIEW_SERVER_PORT)
# Gestion de l'erreur "Address already in use"
socketserver.TCPServer.allow_reuse_address = True
httpd = socketserver.TCPServer(address, SecureHandler)
thread = threading.Thread(target=httpd.serve_forever)
@@ -49,7 +44,6 @@ def start_preview_server():
# --- FIN DE LA LOGIQUE DU SERVEUR D'APERÇU ---
# Le reste du fichier Python est inchangé
def prepare_layer(top_image, base_image, resize_mode, scale, offset_x, offset_y):
B, base_H, base_W, C = base_image.shape
top_C = top_image.shape[3] if top_image.dim() > 3 else 1
@@ -96,14 +90,21 @@ class LayerSystem:
@classmethod
def INPUT_TYPES(cls):
header_anchors = {}
for i in range(1, 11):
header_anchors[f"header_anchor_{i}"] = ("STRING", {"multiline": True, "default": ""})
optional_inputs = {
"_properties_json": ("STRING", {"multiline": True, "default": "{}"}),
"_preview_anchor": ("STRING", {"multiline": True, "default": "PREVIEW_ANCHOR"}),
}
optional_inputs.update(header_anchors)
return {
"required": {
"base_image": ("IMAGE",),
},
"optional": {
"_properties_json": ("STRING", {"multiline": True, "default": "{}"}),
"_preview_anchor": ("STRING", {"multiline": True, "default": "PREVIEW_ANCHOR"}),
}
"optional": optional_inputs
}
RETURN_TYPES = ("IMAGE",)
@@ -153,33 +154,56 @@ class LayerSystem:
sorted_layer_names = sorted(layers.keys())
for layer_name in sorted_layer_names:
layer_image = layers.get(layer_name)
if layer_image is None: continue
layer_image_full = layers.get(layer_name)
if layer_image_full is None: continue
layer_pil = self.tensor_to_pil(layer_image)
layer_pil = self.tensor_to_pil(layer_image_full)
layer_filename = f"layersys_{layer_name}.png"
layer_pil.save(os.path.join(temp_dir, layer_filename))
previews_data[layer_name] = f"http://127.0.0.1:{PREVIEW_SERVER_PORT}/{layer_filename}"
if layer_image.shape[-1] == 4:
layer_image = layer_image[..., :3]
mask_name = layer_name.replace("layer_", "mask_")
mask = masks.get(mask_name)
# MODIFIÉ : On gère la sauvegarde du masque correctement
if mask is not None:
# On s'assure que le masque est un tensor 4D (B, H, W, C)
mask_for_preview = mask
if mask_for_preview.dim() == 3:
mask_for_preview = mask_for_preview.unsqueeze(-1)
# On convertit le masque (1 canal) en image RGB (3 canaux) pour la sauvegarde
mask_for_preview_rgb = mask_for_preview.repeat(1, 1, 1, 3)
mask_pil = self.tensor_to_pil(mask_for_preview_rgb)
mask_filename = f"layersys_{mask_name}.png"
mask_pil.save(os.path.join(temp_dir, mask_filename))
previews_data[mask_name] = f"http://127.0.0.1:{PREVIEW_SERVER_PORT}/{mask_filename}"
layer_alpha = None
if layer_image_full.shape[-1] == 4:
layer_alpha = layer_image_full[..., 3:4]
layer_image = layer_image_full[..., :3]
else:
layer_image = layer_image_full
props = properties.get(layer_name, {})
if not props.get("enabled", True): continue
resize_mode = props.get("resize_mode", "fit")
scale = props.get("scale", 1.0)
offset_x = props.get("offset_x", 0)
offset_y = props.get("offset_y", 0)
prepared_layer = prepare_layer(layer_image, final_image, resize_mode, scale, offset_x, offset_y)
brightness = props.get("brightness", 0.0)
if brightness != 0.0:
prepared_layer = torch.clamp(prepared_layer + brightness, 0.0, 1.0)
if brightness != 0.0: prepared_layer = torch.clamp(prepared_layer + brightness, 0.0, 1.0)
contrast = props.get("contrast", 0.0)
if contrast != 0.0:
contrast_factor = 1.0 + contrast
prepared_layer = torch.clamp((prepared_layer - 0.5) * contrast_factor + 0.5, 0.0, 1.0)
color_r = props.get("color_r", 1.0)
color_g = props.get("color_g", 1.0)
color_b = props.get("color_b", 1.0)
color_r, color_g, color_b = props.get("color_r", 1.0), props.get("color_g", 1.0), props.get("color_b", 1.0)
if color_r != 1.0 or color_g != 1.0 or color_b != 1.0:
prepared_layer[..., 0] = torch.clamp(prepared_layer[..., 0] * color_r, 0.0, 1.0)
prepared_layer[..., 1] = torch.clamp(prepared_layer[..., 1] * color_g, 0.0, 1.0)
@@ -189,21 +213,31 @@ class LayerSystem:
grayscale = prepared_layer[..., 0] * 0.299 + prepared_layer[..., 1] * 0.587 + prepared_layer[..., 2] * 0.114
grayscale = grayscale.unsqueeze(-1)
prepared_layer = torch.clamp(grayscale * (1.0 - saturation) + prepared_layer * saturation, 0.0, 1.0)
mode = props.get("blend_mode", "normal")
mode = mode.replace('-', '_')
opacity = props.get("opacity", 1.0)
blended_image = self._blend(final_image, prepared_layer, mode)
composited_image = (1.0 - opacity) * final_image + opacity * blended_image
mask_name = layer_name.replace("layer_", "mask_")
mask = masks.get(mask_name)
final_mask = None
if mask is not None:
if mask.dim() == 3:
mask = mask.unsqueeze(-1)
prepared_mask = prepare_layer(mask, final_image, resize_mode, scale, offset_x, offset_y)
if mask.dim() == 3: mask = mask.unsqueeze(-1)
final_mask = prepare_layer(mask, final_image, resize_mode, scale, offset_x, offset_y)
if props.get("invert_mask", False):
prepared_mask = 1.0 - prepared_mask
final_image = final_image * (1.0 - prepared_mask) + composited_image * prepared_mask
final_mask = 1.0 - final_mask
elif layer_alpha is not None:
final_mask = prepare_layer(layer_alpha, final_image, resize_mode, scale, offset_x, offset_y)
if final_mask is not None:
final_mask_with_opacity = final_mask * opacity
final_image = final_image * (1.0 - final_mask_with_opacity) + blended_image * final_mask_with_opacity
else:
final_image = composited_image
if resize_mode != 'stretch':
mask_from_content = (prepared_layer.sum(dim=-1, keepdim=True) > 0.001).float()
mask_with_opacity = mask_from_content * opacity
final_image = final_image * (1.0 - mask_with_opacity) + blended_image * mask_with_opacity
else:
final_image = (1.0 - opacity) * final_image + blended_image * opacity
return {
"result": (final_image,),