FIXED: wildcard, lora selector bug

from https://github.com/ltdrdata/ComfyUI-Impact-Pack/pull/838/files)

FIXED: SAM Detector
https://github.com/ltdrdata/ComfyUI-Impact-Pack/issues/836

README.md

@@ -286,6 +286,7 @@ This custom node helps to conveniently enhance images through Detector, Detailer
   * `Negative Cond Placeholder` - Models like FLUX.1 do not use Negative Conditioning. This is a placeholder node for them. You can use FLUX.1 by replacing the Negative Conditioning used in Impact KSampler, KSampler (Inspire), and Detailer with this node.
   * `Execution Order Controller` - A helper node that can forcibly control the execution order of nodes.
     * Connect the output of the node that should be executed first to the signal, and make the input of the node that should be executed later pass through this node.
+  * `List Bridge` - When passing the list output through this node, it collects and organizes the data before forwarding it, which ensures that the previous stage's sub-workflow has been completed.
 
 
 ## MMDet nodes (DEPRECATED) - Don't use these nodes

__init__.py

@@ -273,6 +273,7 @@ NODE_CLASS_MAPPINGS = {
     "StringListToString": StringListToString,
     "WildcardPromptFromString": WildcardPromptFromString,
     "ImpactExecutionOrderController": ImpactExecutionOrderController,
+    "ImpactListBridge": ImpactListBridge,
 
     "RemoveNoiseMask": RemoveNoiseMask,
 
@@ -393,6 +394,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ImpactSwitch": "Switch (Any)",
     "ImpactInversedSwitch": "Inversed Switch (Any)",
     "ImpactExecutionOrderController": "Execution Order Controller",
+    "ImpactListBridge": "List Bridge",
 
     "MasksToMaskList": "Mask Batch to Mask List",
     "MaskListToMaskBatch": "Mask List to Mask Batch",

install-manual.py

@@ -1,10 +1,13 @@
+import functools
 import os
+import re
 import shutil
 import sys
 import subprocess
 import threading
 import locale
 import traceback
+from typing import Set
 
 
 if sys.argv[0] == 'install.py':
@@ -66,6 +69,42 @@ def process_wrap(cmd_str, cwd=None, handler=None, env=None):
     stderr_thread.join()
 
     return process.wait()
+
+
+@functools.cache
+def get_installed_packages() -> Set[str]:
+    try:
+        result = subprocess.check_output([sys.executable, '-m', 'pip', 'list'], universal_newlines=True)
+        pip_list = set([line.split()[0].lower() for line in result.split('\n') if line.strip()])
+        return pip_list
+    except subprocess.CalledProcessError as e:
+        raise Exception(f"[ComfyUI-Impact-Pack] Failed to retrieve the information of installed pip packages.")
+
+
+def is_package_installed(name: str) -> bool:
+    name = name.strip()
+    pattern = r'([^<>!=]+)([<>!=]=?)'
+    match = re.search(pattern, name)
+    
+    if match:
+        name = match.group(1)
+        
+    result = name.lower() in get_installed_packages()
+    return result
+
+
+def is_requirements_installed(file_path: str) -> bool:
+    print(f"Requirements file: {file_path}")
+    if os.path.exists(file_path):
+        with open(file_path, "r") as file:
+            lines = file.readlines()
+
+        for line in lines:
+            if not is_package_installed(line):
+                return False
+
+pip_install = [sys.executable, "-m", "pip", "install", "-U"]
+
 # ---
 
 

install.py

@@ -114,19 +114,22 @@ try:
         onnx_path = os.path.join(model_path, "onnx")
 
         if not os.path.exists(os.path.join(os.path.dirname(__file__), '..', 'skip_download_model')):
-            if not impact.config.get_config()['mmdet_skip']:
-                bbox_path = os.path.join(model_path, "mmdets", "bbox")
-                if not os.path.exists(bbox_path):
-                    os.makedirs(bbox_path)
+            try:
+                if not impact.config.get_config()['mmdet_skip']:
+                    bbox_path = os.path.join(model_path, "mmdets", "bbox")
+                    if not os.path.exists(bbox_path):
+                        os.makedirs(bbox_path)
 
-                if not os.path.exists(os.path.join(bbox_path, "mmdet_anime-face_yolov3.pth")):
-                    download_url("https://huggingface.co/dustysys/ddetailer/resolve/main/mmdet/bbox/mmdet_anime-face_yolov3.pth", bbox_path)
+                    if not os.path.exists(os.path.join(bbox_path, "mmdet_anime-face_yolov3.pth")):
+                        download_url("https://huggingface.co/dustysys/ddetailer/resolve/main/mmdet/bbox/mmdet_anime-face_yolov3.pth", bbox_path)
 
-                if not os.path.exists(os.path.join(bbox_path, "mmdet_anime-face_yolov3.py")):
-                    download_url("https://raw.githubusercontent.com/Bing-su/dddetailer/master/config/mmdet_anime-face_yolov3.py", bbox_path)
+                    if not os.path.exists(os.path.join(bbox_path, "mmdet_anime-face_yolov3.py")):
+                        download_url("https://raw.githubusercontent.com/Bing-su/dddetailer/master/config/mmdet_anime-face_yolov3.py", bbox_path)
 
-            if not os.path.exists(os.path.join(sam_path, "sam_vit_b_01ec64.pth")):
-                download_url("https://dl.fbaipublicfiles.com/segment_anything/sam_vit_b_01ec64.pth", sam_path)
+                if not os.path.exists(os.path.join(sam_path, "sam_vit_b_01ec64.pth")):
+                    download_url("https://dl.fbaipublicfiles.com/segment_anything/sam_vit_b_01ec64.pth", sam_path)
+            except:
+                print(f"[Impact Pack] Failed to auto-download model files. Please download them manually.")
 
         if not os.path.exists(onnx_path):
             print(f"### ComfyUI-Impact-Pack: onnx model directory created ({onnx_path})")

js/impact-pack.js

@@ -353,7 +353,7 @@ app.registerExtension({
 						}
 
 						this.outputs[0].type = origin_type;
-						this.outputs[0].name = origin_type;
+						this.outputs[0].name = 'output1';
 					}
 
 					return;
@@ -483,8 +483,12 @@ app.registerExtension({
 
 					if(this.inputs[0].type == '*'){
 						const node = app.graph.getNodeById(link_info.origin_id);
-						let origin_type = node.outputs[link_info.origin_slot].type;
-
+						let origin_type = node.outputs[link_info.origin_slot]?.type;
+						if(link_info.target_slot == 0 && this.inputs.length > 1) {
+								origin_type = this.inputs[1].type;
+								node.connect(link_info.origin_slot, node.id, 'input1');
+						}
+						
 						if(origin_type == '*') {
 							this.disconnectInput(link_info.target_slot);
 							return;
@@ -583,17 +587,17 @@ app.registerExtension({
 		}
 
 		if(node.comfyClass == "ImpactSEGSLabelFilter" || node.comfyClass == "SEGSLabelFilterDetailerHookProvider") {
+			node.widgets[0].callback = (value, canvas, node, pos, e) => {
+				if(node.widgets[1].value.trim() != "" && !node.widgets[1].value.trim().endsWith(","))
+					node.widgets[1].value += ", "
+
+				node.widgets[1].value += value;
+				if(node.widgets_values)
+					node.widgets_values[1] = node.widgets[1].value;
+			}
+
 			Object.defineProperty(node.widgets[0], "value", {
 				set: (value) => {
-						const stackTrace = new Error().stack;
-						if(stackTrace.includes('inner_value_change')) {
-							if(node.widgets[1].value.trim() != "" && !node.widgets[1].value.trim().endsWith(","))
-								node.widgets[1].value += ", "
-
-							node.widgets[1].value += value;
-							node.widgets_values[1] = node.widgets[1].value;
-						}
-
 						node._value = value;
 					},
 				get: () => {
@@ -663,18 +667,18 @@ app.registerExtension({
 					break;
 			}
 
+            node.widgets[combo_id+1].callback = (value, canvas, node, pos, e) => {
+                    if(node.widgets[tbox_id].value != '')
+                        node.widgets[tbox_id].value += ', '
+
+                    node.widgets[tbox_id].value += node._wildcard_value;
+            }
+
 			Object.defineProperty(node.widgets[combo_id+1], "value", {
 				set: (value) => {
-						const stackTrace = new Error().stack;
-						if(stackTrace.includes('inner_value_change')) {
-							if(value != "Select the Wildcard to add to the text") {
-								if(node.widgets[tbox_id].value != '')
-									node.widgets[tbox_id].value += ', '
-
-								node.widgets[tbox_id].value += value;
-							}
-						}
-					},
+                    if (value !== "Select the Wildcard to add to the text")
+                        node._wildcard_value = value;
+                },
 				get: () => { return "Select the Wildcard to add to the text"; }
 			});
 
@@ -686,24 +690,22 @@ app.registerExtension({
 			});
 
 			if(has_lora) {
+				node.widgets[combo_id].callback = (value, canvas, node, pos, e) => {
+					let lora_name = node._value;
+					if(lora_name.endsWith('.safetensors')) {
+						lora_name = lora_name.slice(0, -12);
+					}
+
+					node.widgets[tbox_id].value += `<lora:${lora_name}>`;
+					if(node.widgets_values) {
+						node.widgets_values[tbox_id] = node.widgets[tbox_id].value;
+					}
+				}
+
 				Object.defineProperty(node.widgets[combo_id], "value", {
 					set: (value) => {
-							const stackTrace = new Error().stack;
-							if(stackTrace.includes('inner_value_change')) {
-								if(value != "Select the LoRA to add to the text") {
-									let lora_name = value;
-									if (lora_name.endsWith('.safetensors')) {
-										lora_name = lora_name.slice(0, -12);
-									}
-
-									node.widgets[tbox_id].value += `<lora:${lora_name}>`;
-									if(node.widgets_values) {
-										node.widgets_values[tbox_id] = node.widgets[tbox_id].value;
-									}
-								}
-							}
-
-							node._value = value;
+							if (value !== "Select the LoRA to add to the text")
+								node._value = value;
 						},
 
 					get: () => { return "Select the LoRA to add to the text"; }

js/impact-sam-editor.js

@@ -353,13 +353,16 @@ class ImpactSamEditorDialog extends ComfyDialog {
 			imgCtx.drawImage(orig_image, 0, 0, drawWidth, drawHeight);
 
 			// update mask
+			let w = (drawWidth * imgCanvas.clientWidth/imgCanvas.width) + "px";
+			let h = (drawHeight * imgCanvas.clientHeight/imgCanvas.height) + "px";
+
 			pointsCanvas.width = drawWidth;
 			pointsCanvas.height = drawHeight;
 			pointsCanvas.style.top = imgCanvas.offsetTop + "px";
 			pointsCanvas.style.left = imgCanvas.offsetLeft + "px";
 
-			maskCanvas.width = drawWidth;
-			maskCanvas.height = drawHeight;
+			maskCanvas.style.width = w;
+			maskCanvas.style.height = h;
 			maskCanvas.style.top = imgCanvas.offsetTop + "px";
 			maskCanvas.style.left = imgCanvas.offsetLeft + "px";
 

modules/impact/config.py

@@ -1,10 +1,10 @@
 import configparser
 import os
 
-version_code = [7, 10, 1]
+version_code = [7, 13]
 version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
 
-dependency_version = 23
+dependency_version = 24
 
 my_path = os.path.dirname(__file__)
 old_config_path = os.path.join(my_path, "impact-pack.ini")

modules/impact/core.py

@@ -11,6 +11,7 @@ from impact.utils import *
 from collections import namedtuple
 import numpy as np
 from skimage.measure import label
+from PIL import ImageOps
 
 import nodes
 import comfy_extras.nodes_upscale_model as model_upscale
@@ -47,7 +48,7 @@ preview_bridge_last_mask_cache = {}
 
 current_prompt = None
 
-SCHEDULERS = comfy.samplers.KSampler.SCHEDULERS + ['AYS SDXL', 'AYS SD1', 'AYS SVD', 'GITS[coeff=1.2]']
+SCHEDULERS = comfy.samplers.KSampler.SCHEDULERS + ['AYS SDXL', 'AYS SD1', 'AYS SVD', 'GITS[coeff=1.2]', 'LTXV[default]']
 
 
 def is_execution_model_version_supported():
@@ -69,6 +70,13 @@ def set_previewbridge_image(node_id, file, item):
     pb_id = f"${node_id}-{pb_id_cnt}"
     preview_bridge_image_id_map[pb_id] = (file, item)
     preview_bridge_image_name_map[node_id, file] = (pb_id, item)
+    if os.path.isfile(file):
+        i = Image.open(file)
+        i = ImageOps.exif_transpose(i)
+        if 'A' in i.getbands():
+            mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
+            mask = 1. - torch.from_numpy(mask)
+            preview_bridge_last_mask_cache[node_id] = mask.unsqueeze(0)
     pb_id_cnt += 1
 
     return pb_id
@@ -319,7 +327,12 @@ def enhance_detail(image, model, clip, vae, guide_size, guide_size_for_bbox, max
 
     # prepare mask
     if noise_mask is not None and inpaint_model:
-        positive, negative, latent_image = nodes.InpaintModelConditioning().encode(positive, negative, upscaled_image, vae, noise_mask)
+        imc_encode = nodes.InpaintModelConditioning().encode
+        if 'noise_mask' in inspect.signature(imc_encode).parameters:
+            positive, negative, latent_image = imc_encode(positive, negative, upscaled_image, vae, mask=noise_mask, noise_mask=True)
+        else:
+            print(f"[Impact Pack] ComfyUI is an outdated version.")
+            positive, negative, latent_image = imc_encode(positive, negative, upscaled_image, vae, noise_mask)
     else:
         latent_image = to_latent_image(upscaled_image, vae)
         if noise_mask is not None:
@@ -1354,9 +1367,14 @@ def segs_to_masklist(segs):
     return masks
 
 
-def vae_decode(vae, samples, use_tile, hook, tile_size=512):
+def vae_decode(vae, samples, use_tile, hook, tile_size=512, overlap=64):
     if use_tile:
-        pixels = nodes.VAEDecodeTiled().decode(vae, samples, tile_size)[0]
+        decoder = nodes.VAEDecodeTiled()
+        if 'overlap' in inspect.signature(decoder.decode).parameters:
+            pixels = decoder.decode(vae, samples, tile_size, overlap=overlap)[0]
+        else:
+            print(f"[Impact Pack] Your ComfyUI is outdated.")
+            pixels = decoder.decode(vae, samples, tile_size)[0]
     else:
         pixels = nodes.VAEDecode().decode(vae, samples)[0]
 
@@ -1378,12 +1396,12 @@ def vae_encode(vae, pixels, use_tile, hook, tile_size=512):
     return samples
 
 
-def latent_upscale_on_pixel_space_shape(samples, scale_method, w, h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
-    return latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_tile, tile_size, save_temp_prefix, hook)[0]
+def latent_upscale_on_pixel_space_shape(samples, scale_method, w, h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
+    return latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_tile, tile_size, save_temp_prefix, hook, overlap=overlap)[0]
 
 
-def latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
-    pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size)
+def latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
+    pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size, overlap=overlap)
 
     if save_temp_prefix is not None:
         nodes.PreviewImage().save_images(pixels, filename_prefix=save_temp_prefix)
@@ -1397,12 +1415,12 @@ def latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_t
     return (vae_encode(vae, pixels, use_tile, hook, tile_size=tile_size), old_pixels)
 
 
-def latent_upscale_on_pixel_space(samples, scale_method, scale_factor, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
-    return latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use_tile, tile_size, save_temp_prefix, hook)[0]
+def latent_upscale_on_pixel_space(samples, scale_method, scale_factor, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
+    return latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use_tile, tile_size, save_temp_prefix, hook, overlap=overlap)[0]
 
 
-def latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
-    pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size)
+def latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
+    pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size, overlap=overlap)
 
     if save_temp_prefix is not None:
         nodes.PreviewImage().save_images(pixels, filename_prefix=save_temp_prefix)
@@ -1418,12 +1436,12 @@ def latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use
     return (vae_encode(vae, pixels, use_tile, hook, tile_size=tile_size), old_pixels)
 
 
-def latent_upscale_on_pixel_space_with_model_shape(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
-    return latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile, tile_size, save_temp_prefix, hook)[0]
+def latent_upscale_on_pixel_space_with_model_shape(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
+    return latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile, tile_size, save_temp_prefix, hook, overlap=overlap)[0]
 
 
-def latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
-    pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size)
+def latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
+    pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size, overlap=overlap)
 
     if save_temp_prefix is not None:
         nodes.PreviewImage().save_images(pixels, filename_prefix=save_temp_prefix)
@@ -1450,12 +1468,12 @@ def latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upsca
 
 
 def latent_upscale_on_pixel_space_with_model(samples, scale_method, upscale_model, scale_factor, vae, use_tile=False,
-                                             tile_size=512, save_temp_prefix=None, hook=None):
-    return latent_upscale_on_pixel_space_with_model2(samples, scale_method, upscale_model, scale_factor, vae, use_tile, tile_size, save_temp_prefix, hook)[0]
+                                             tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
+    return latent_upscale_on_pixel_space_with_model2(samples, scale_method, upscale_model, scale_factor, vae, use_tile, tile_size, save_temp_prefix, hook, overlap=overlap)[0]
 
 def latent_upscale_on_pixel_space_with_model2(samples, scale_method, upscale_model, scale_factor, vae, use_tile=False,
-                                              tile_size=512, save_temp_prefix=None, hook=None):
-    pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size)
+                                              tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
+    pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size, overlap=overlap)
 
     if save_temp_prefix is not None:
         nodes.PreviewImage().save_images(pixels, filename_prefix=save_temp_prefix)

modules/impact/impact_pack.py

@@ -2150,16 +2150,19 @@ class ImpactWildcardProcessor:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": {
-                        "wildcard_text": ("STRING", {"multiline": True, "dynamicPrompts": False}),
-                        "populated_text": ("STRING", {"multiline": True, "dynamicPrompts": False}),
-                        "mode": ("BOOLEAN", {"default": True, "label_on": "Populate", "label_off": "Fixed"}),
-                        "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
+                        "wildcard_text": ("STRING", {"multiline": True, "dynamicPrompts": False, "tooltip": "Enter a prompt using wildcard syntax."}),
+                        "populated_text": ("STRING", {"multiline": True, "dynamicPrompts": False, "tooltip": "The actual value passed during the execution of 'ImpactWildcardProcessor' is what is shown here. The behavior varies slightly depending on the mode. Wildcard syntax can also be used in 'populated_text'."}),
+                        "mode": ("BOOLEAN", {"default": True, "label_on": "Populate", "label_off": "Fixed", "tooltip": "Populate: Before running the workflow, it overwrites the existing value of 'populated_text' with the prompt processed from 'wildcard_text'. In this mode, 'populated_text' cannot be edited.\nFixed: Ignores wildcard_text and keeps 'populated_text' as is. You can edit 'populated_text' in this mode."}),
+                        "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "tooltip": "Determines the random seed to be used for wildcard processing."}),
                         "Select to add Wildcard": (["Select the Wildcard to add to the text"],),
                     },
                 }
 
     CATEGORY = "ImpactPack/Prompt"
 
+    DESCRIPTION = ("The 'ImpactWildcardProcessor' processes text prompts written in wildcard syntax and outputs the processed text prompt.\n\n"
+                   "TIP: Before the workflow is executed, the processing result of 'wildcard_text' is displayed in 'populated_text', and the populated text is saved along with the workflow. If you want to use a seed converted as input, write the prompt directly in 'populated_text' instead of 'wildcard_text', and set the mode to 'Fixed'.")
+
     RETURN_TYPES = ("STRING", )
     FUNCTION = "doit"
 
@@ -2178,17 +2181,22 @@ class ImpactWildcardEncode:
         return {"required": {
                         "model": ("MODEL",),
                         "clip": ("CLIP",),
-                        "wildcard_text": ("STRING", {"multiline": True, "dynamicPrompts": False}),
-                        "populated_text": ("STRING", {"multiline": True, "dynamicPrompts": False}),
-                        "mode": ("BOOLEAN", {"default": True, "label_on": "Populate", "label_off": "Fixed"}),
+                        "wildcard_text": ("STRING", {"multiline": True, "dynamicPrompts": False, "tooltip": "Enter a prompt using wildcard syntax."}),
+                        "populated_text": ("STRING", {"multiline": True, "dynamicPrompts": False, "tooltip": "The actual value passed during the execution of 'ImpactWildcardEncode' is what is shown here. The behavior varies slightly depending on the mode. Wildcard syntax can also be used in 'populated_text'."}),
+                        "mode": ("BOOLEAN", {"default": True, "label_on": "Populate", "label_off": "Fixed", "tooltip": "Populate: Before running the workflow, it overwrites the existing value of 'populated_text' with the prompt processed from 'wildcard_text'. In this mode, 'populated_text' cannot be edited.\n"
+                                                                                                                       "Fixed: Ignores wildcard_text and keeps 'populated_text' as is. You can edit 'populated_text' in this mode."}),
                         "Select to add LoRA": (["Select the LoRA to add to the text"] + folder_paths.get_filename_list("loras"), ),
                         "Select to add Wildcard": (["Select the Wildcard to add to the text"], ),
-                        "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
+                        "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "tooltip": "Determines the random seed to be used for wildcard processing."}),
                     },
                 }
 
     CATEGORY = "ImpactPack/Prompt"
 
+    DESCRIPTION = ("The 'ImpactWildcardEncode' node processes text prompts written in wildcard syntax and outputs them as conditioning. It also supports LoRA syntax, with the applied LoRA reflected in the model's output.\n\n"
+                   "TIP1: Before the workflow is executed, the processing result of 'wildcard_text' is displayed in 'populated_text', and the populated text is saved along with the workflow. If you want to use a seed converted as input, write the prompt directly in 'populated_text' instead of 'wildcard_text', and set the mode to 'Fixed'.\n"
+                   "TIP2: If the 'Inspire Pack' is installed, LBW(LoRA Block Weight) syntax can also be applied.")
+
     RETURN_TYPES = ("MODEL", "CLIP", "CONDITIONING", "STRING")
     RETURN_NAMES = ("model", "clip", "conditioning", "populated_text")
     FUNCTION = "doit"
@@ -2213,7 +2221,7 @@ class ImpactSchedulerAdapter:
     def INPUT_TYPES(s):
         return {"required": {
             "scheduler": (comfy.samplers.KSampler.SCHEDULERS, {"defaultInput": True, }),
-            "extra_scheduler": (['None', 'AYS SDXL', 'AYS SD1', 'AYS SVD', 'GITS[coeff=1.2]'],),
+            "extra_scheduler": (['None', 'AYS SDXL', 'AYS SD1', 'AYS SVD', 'GITS[coeff=1.2]', 'LTXV[default]'],),
         }}
 
     CATEGORY = "ImpactPack/Util"

modules/impact/impact_sampling.py

@@ -27,6 +27,8 @@ def calculate_sigmas(model, sampler, scheduler, steps):
         sigmas = nodes.NODE_CLASS_MAPPINGS['AlignYourStepsScheduler']().get_sigmas(scheduler[4:], steps, denoise=1.0)[0]
     elif scheduler.startswith('GITS[coeff='):
         sigmas = nodes.NODE_CLASS_MAPPINGS['GITSScheduler']().get_sigmas(float(scheduler[11:-1]), steps, denoise=1.0)[0]
+    elif scheduler == 'LTXV[default]':
+        sigmas = nodes.NODE_CLASS_MAPPINGS['LTXVScheduler']().get_sigmas(20, 2.05, 0.95, True, 0.1)[0]
     else:
         sigmas = samplers.calculate_sigmas(model.get_model_object("model_sampling"), scheduler, steps)
 

modules/impact/logics.py

@@ -766,6 +766,29 @@ class ImpactExecutionOrderController:
         return signal, value
 
 
+class ImpactListBridge:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {"required": {
+                    "list_input": (any_typ,),
+                    }}
+
+    FUNCTION = "doit"
+
+    DESCRIPTION = "When passing the list output through this node, it collects and organizes the data before forwarding it, which ensures that the previous stage's sub-workflow has been completed."
+
+    CATEGORY = "ImpactPack/Util"
+    RETURN_TYPES = (any_typ, )
+    RETURN_NAMES = ("list_output", )
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True, )
+
+    @staticmethod
+    def doit(list_input):
+        return (list_input,)
+
+
 original_handle_execution = execution.PromptExecutor.handle_execution_error
 
 

modules/impact/segs_nodes.py

@@ -896,7 +896,7 @@ class From_SEG_ELT_bbox:
     CATEGORY = "ImpactPack/Util"
 
     def doit(self, bbox):
-        return bbox
+        return [int(c) for c in bbox]
 
 
 class From_SEG_ELT_crop_region:
@@ -1101,10 +1101,10 @@ class SEG_ELT_BBOX_ScaleBy:
         x1, y1, x2, y2 = x1-cx1, y1-cy1, x2-cx1, y2-cy1
         h, w = mask.shape
 
-        x1 = min(w-1, max(0, x1))
-        x2 = min(w-1, max(0, x2))
-        y1 = min(h-1, max(0, y1))
-        y2 = min(h-1, max(0, y2))
+        x1 = int(min(w-1, max(0, x1)))
+        x2 = int(min(w-1, max(0, x2)))
+        y1 = int(min(h-1, max(0, y1)))
+        y2 = int(min(h-1, max(0, y2)))
 
         mask_cropped = mask.copy()
         mask_cropped[:, :x1] = 0  # zero fill left side

modules/impact/segs_upscaler.py

@@ -106,7 +106,12 @@ def img2img_segs(image, model, clip, vae, seed, steps, cfg, sampler_name, schedu
 
     # prepare mask
     if noise_mask is not None and inpaint_model:
-        positive, negative, latent_image = nodes.InpaintModelConditioning().encode(positive, negative, image, vae, noise_mask)
+        imc_encode = nodes.InpaintModelConditioning().encode
+        if 'noise_mask' in inspect.signature(imc_encode).parameters:
+            positive, negative, latent_image = imc_encode(positive, negative, image, vae, mask=noise_mask, noise_mask=True)
+        else:
+            print(f"[Impact Pack] ComfyUI is an outdated version.")
+            positive, negative, latent_image = imc_encode(positive, negative, image, vae, noise_mask)
     else:
         latent_image = to_latent_image(image, vae)
         if noise_mask is not None:

modules/impact/util_nodes.py

@@ -17,9 +17,16 @@ class GeneralSwitch:
         dyn_inputs = {"input1": (any_typ, {"lazy": True, "tooltip": "Any input. When connected, one more input slot is added."}), }
         if core.is_execution_model_version_supported():
             stack = inspect.stack()
-            if stack[2].function == 'get_input_info' and stack[3].function == 'add_node':
-                for x in range(2, 200):
-                    dyn_inputs[f"input{x}"] = (any_typ, {"lazy": True})
+            if stack[2].function == 'get_input_info':
+                # bypass validation
+                class AllContainer:
+                    def __contains__(self, item):
+                        return True
+
+                    def __getitem__(self, key):
+                        return any_typ, {"lazy": True}
+
+                dyn_inputs = AllContainer()
 
         inputs = {"required": {
                     "select": ("INT", {"default": 1, "min": 1, "max": 999999, "step": 1, "tooltip": "The input number you want to output among the inputs"}),
@@ -366,7 +373,7 @@ class ImageListToImageBatch:
 
     def doit(self, images):
         if len(images) <= 1:
-            return (images,)
+            return (images[0],)
         else:
             image1 = images[0]
             for image2 in images[1:]:
@@ -494,7 +501,7 @@ class MakeMaskBatch:
     def doit(self, **kwargs):
         mask1 = kwargs['mask1']
         del kwargs['mask1']
-        masks = [utils.make_3d_mask(value) for value in kwargs.values()]
+        masks = [make_3d_mask(value) for value in kwargs.values()]
 
         if len(masks) == 0:
             return (mask1,)

modules/impact/wildcards.py

@@ -58,11 +58,11 @@ def read_wildcard_dict(wildcard_path):
                 try:
                     with open(file_path, 'r', encoding="ISO-8859-1") as f:
                         lines = f.read().splitlines()
-                        wildcard_dict[key] = lines
+                        wildcard_dict[key] = [x for x in lines if not x.strip().startswith('#')]
                 except yaml.reader.ReaderError:
                     with open(file_path, 'r', encoding="UTF-8", errors="ignore") as f:
                         lines = f.read().splitlines()
-                        wildcard_dict[key] = lines
+                        wildcard_dict[key] = [x for x in lines if not x.strip().startswith('#')]
             elif file.endswith('.yaml'):
                 file_path = os.path.join(root, file)
 
@@ -150,7 +150,7 @@ def process(text, seed=None):
                         matches = re.findall(wildcard_pattern, multi_select_pattern[1])
                         if len(options) == 1 and matches:
                             # count$$<single wildcard>
-                            options = local_wildcard_dict.get(matches[0])
+                            options = get_wildcard_options(multi_select_pattern[1])
                         else:
                             # count$$opt1|opt2|...
                             options[0] = multi_select_pattern[1]
@@ -199,6 +199,34 @@ def process(text, seed=None):
 
         return replaced_string, replacements_found
 
+    def get_wildcard_options(string):
+        pattern = r"__([\w.\-+/*\\]+?)__"
+        matches = re.findall(pattern, string)
+
+        options = []
+
+        for match in matches:
+            keyword = match.lower()
+            keyword = wildcard_normalize(keyword)
+            if keyword in local_wildcard_dict:
+                options.extend(local_wildcard_dict[keyword])
+            elif '*' in keyword:
+                subpattern = keyword.replace('*', '.*').replace('+', '\\+')
+                total_patterns = []
+                found = False
+                for k, v in local_wildcard_dict.items():
+                    if re.match(subpattern, k) is not None or re.match(subpattern, k+'/') is not None:
+                        total_patterns += v
+                        found = True
+
+                if found:
+                    options.extend(total_patterns)
+            elif '/' not in keyword:
+                string_fallback = string.replace(f"__{match}__", f"__*/{match}__", 1)
+                options.extend(get_wildcard_options(string_fallback))
+
+        return options
+
     def replace_wildcard(string):
         pattern = r"__([\w.\-+/*\\]+?)__"
         matches = re.findall(pattern, string)
@@ -259,7 +287,7 @@ def process(text, seed=None):
 
 
 def is_numeric_string(input_str):
-    return re.match(r'^-?\d+(\.\d+)?$', input_str) is not None
+    return re.match(r'^-?(\d*\.?\d+|\d+\.?\d*)$', input_str) is not None
 
 
 def safe_float(x):

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-impact-pack"
 description = "This extension offers various detector nodes and detailer nodes that allow you to configure a workflow that automatically enhances facial details. And provide iterative upscaler."
-version = "7.10.1"
+version = "7.13"
 license = { file = "LICENSE.txt" }
 dependencies = ["segment-anything", "scikit-image", "piexif", "transformers", "opencv-python-headless", "GitPython", "scipy>=1.11.4"]