remove useless code

https://github.com/ltdrdata/ComfyUI-extension-tutorials/issues/28

README.md

@@ -7,6 +7,7 @@ This custom node helps to conveniently enhance images through Detector, Detailer
 
 
 ## NOTICE 
+* V7.6: Automatic installation is no longer supported. Please install using ComfyUI-Manager, or manually install requirements.txt and run install.py to complete the installation.
 * V7.0: Supports Switch based on Execution Model Inversion.
 * V6.0: Supports FLUX.1 model in Impact KSampler, Detailers, PreviewBridgeLatent
 * V5.0: It is no longer compatible with versions of ComfyUI before 2024.04.08. 
@@ -228,11 +229,14 @@ This custom node helps to conveniently enhance images through Detector, Detailer
   
 
 ### Batch/List Util
-  * `Image batch To Image List` - Convert Image batch to Image List
+  * `Image Batch to Image List` - Convert Image batch to Image List
     - You can use images generated in a multi batch to handle them
+  * `Image List to Image Batch` - Convert Image List to Image Batch 
   * `Make Image List` - Convert multiple images into a single image list
   * `Make Image Batch` - Convert multiple images into a single image batch
     - The input of images can be scaled up as needed
+  * `Masks to Mask List`, `Mask List to Masks`, `Make Mask List`, `Make Mask Batch` - It has the same functionality as the nodes above, but uses mask as input instead of image.
+  * `Flatten Mask Batch` - Flattens a Mask Batch into a single Mask. Normal operation is not guaranteed for non-binary masks. 
 
 
 ### Logics (experimental) 
@@ -306,7 +310,8 @@ This custom node helps to conveniently enhance images through Detector, Detailer
 
 
 ## Ultralytics models
-* huggingface.co/Bingsu/[adetailer](https://github.com/ultralytics/assets/releases/) - You can download face, people detection models, and clothing detection models.
+* When using ultralytics models, save them separately in `models/ultralytics/bbox` and `models/ultralytics/segm` depending on the type of model. Many models can be downloaded by searching for `ultralytics` in the Model Manager of ComfyUI-Manager.
+* huggingface.co/Bingsu/[adetailer](https://huggingface.co/Bingsu/adetailer/tree/main) - You can download face, people detection models, and clothing detection models.
 * ultralytics/[assets](https://github.com/ultralytics/assets/releases/) - You can download various types of detection models other than faces or people.
 * civitai/[adetailer](https://civitai.com/search/models?sortBy=models_v5&query=adetailer) - You can download various types detection models....Many models are associated with NSFW content.
 
@@ -328,6 +333,10 @@ mmdet_skip = False
 
 ## Installation
 
+### Install via ComfyUI-Manager (Recommended)
+* Search `ComfyUI Impact Pack` in ComfyUI-Manager and click `Install` button.
+
+### Manual Install (Not Recommended)
 1. `cd custom_nodes`
 2. `git clone https://github.com/ltdrdata/ComfyUI-Impact-Pack.git`
 3. `cd ComfyUI-Impact-Pack`
@@ -336,24 +345,29 @@ mmdet_skip = False
 5. (optional) `python install.py`
    * Impact Pack will automatically install its dependencies during its initial launch.
    * For the portable version, you should execute the command `..\..\..\python_embeded\python.exe install.py` to run the installation script.
-
-
 6. Restart ComfyUI
 
 * NOTE1: If an error occurs during the installation process, please refer to [Troubleshooting Page](troubleshooting/TROUBLESHOOTING.md) for assistance. 
 * NOTE2: You can use this colab notebook [colab notebook](https://colab.research.google.com/github/ltdrdata/ComfyUI-Impact-Pack/blob/Main/notebook/comfyui_colab_impact_pack.ipynb) to launch it. This notebook automatically downloads the impact pack to the custom_nodes directory, installs the tested dependencies, and runs it.
 * NOTE3: If you create an empty file named `skip_download_model` in the `ComfyUI/custom_nodes/` directory, it will skip the model download step during the installation of the impact pack.
 
+
 ## Package Dependencies (If you need to manual setup.)
 
 * pip install
-   * openmim
    * segment-anything
    * ultralytics
    * scikit-image
-   * piexif
-   * (optional) pycocotools
+   * piexif 
+   * opencv-python
+   * GitPython
+   * scipy
+   * numpy<2
+   * dill
+   * matplotlib
    * (optional) onnxruntime
+   * (deprecated) openmim      # for mim
+   * (deprecated) pycocotools  # for mim
    
 * mim install (deprecated)
    * mmcv==2.0.0, mmdet==3.0.0, mmengine==0.7.2

__init__.py

@@ -23,22 +23,6 @@ import impact.sample_error_enhancer
 print(f"### Loading: ComfyUI-Impact-Pack ({impact.config.version})")
 
 
-def do_install():
-    import importlib
-    spec = importlib.util.spec_from_file_location('impact_install', os.path.join(os.path.dirname(__file__), 'install.py'))
-    impact_install = importlib.util.module_from_spec(spec)
-    spec.loader.exec_module(impact_install)
-
-
-# ensure dependency
-if not os.path.exists(os.path.join(subpack_path, ".git")) and os.path.exists(subpack_path):
-    print(f"### CompfyUI-Impact-Pack: corrupted subpack detected.")
-    shutil.rmtree(subpack_path)
-
-if impact.config.get_config()['dependency_version'] < impact.config.dependency_version or not os.path.exists(subpack_path):
-    print(f"### ComfyUI-Impact-Pack: Updating dependencies [{impact.config.get_config()['dependency_version']} -> {impact.config.dependency_version}]")
-    do_install()
-
 sys.path.append(subpack_path)
 
 # Core
@@ -63,10 +47,10 @@ try:
         import mmcv
         from mmdet.apis import (inference_detector, init_detector)
         from mmdet.evaluation import get_classes
-except:
-    import importlib
-    print("### ComfyUI-Impact-Pack: Reinstall dependencies (several dependencies are missing.)")
-    do_install()
+except Exception as e:
+    import logging
+    logging.error("[Impact Pack] Failed to import due to several dependencies are missing!!!!")
+    raise e
 
 
 import impact.impact_server  # to load server api
@@ -161,6 +145,7 @@ NODE_CLASS_MAPPINGS = {
     "ImpactSegsAndMask": SegsBitwiseAndMask,
     "ImpactSegsAndMaskForEach": SegsBitwiseAndMaskForEach,
     "EmptySegs": EmptySEGS,
+    "ImpactFlattenMask": FlattenMask,
 
     "MediaPipeFaceMeshToSEGS": MediaPipeFaceMeshToSEGS,
     "MaskToSEGS": MaskToSEGS,
@@ -249,6 +234,8 @@ NODE_CLASS_MAPPINGS = {
     "ImpactImageBatchToImageList": ImageBatchToImageList,
     "ImpactMakeImageList": MakeImageList,
     "ImpactMakeImageBatch": MakeImageBatch,
+    "ImpactMakeMaskList": MakeMaskList,
+    "ImpactMakeMaskBatch": MakeMaskBatch,
 
     "RegionalSampler": RegionalSampler,
     "RegionalSamplerAdvanced": RegionalSamplerAdvanced,
@@ -332,6 +319,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "BitwiseAndMask": "Pixelwise(MASK & MASK)",
     "SubtractMask": "Pixelwise(MASK - MASK)",
     "AddMask": "Pixelwise(MASK + MASK)",
+    "ImpactFlattenMask": "Flatten Mask Batch",
     "DetailerForEach": "Detailer (SEGS)",
     "DetailerForEachPipe": "Detailer (SEGS/pipe)",
     "DetailerForEachDebug": "DetailerDebug (SEGS)",
@@ -400,12 +388,16 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ImpactInversedSwitch": "Inversed Switch (Any)",
     "ImpactExecutionOrderController": "Execution Order Controller",
 
-    "MasksToMaskList": "Masks to Mask List",
-    "MaskListToMaskBatch": "Mask List to Masks",
-    "ImpactImageBatchToImageList": "Image batch to Image List",
+    "MasksToMaskList": "Mask Batch to Mask List",
+    "MaskListToMaskBatch": "Mask List to Mask Batch",
+    "ImpactImageBatchToImageList": "Image Batch to Image List",
     "ImageListToImageBatch": "Image List to Image Batch",
+
     "ImpactMakeImageList": "Make Image List",
     "ImpactMakeImageBatch": "Make Image Batch",
+    "ImpactMakeMaskList": "Make Mask List",
+    "ImpactMakeMaskBatch": "Make Mask Batch",
+
     "ImpactStringSelector": "String Selector",
     "StringListToString": "String List to String",
     "WildcardPromptFromString": "Wildcard Prompt from String",

install.py

@@ -5,7 +5,6 @@ import subprocess
 import threading
 import locale
 import traceback
-import re
 
 
 if sys.argv[0] == 'install.py':
@@ -13,7 +12,6 @@ if sys.argv[0] == 'install.py':
 
 
 impact_path = os.path.join(os.path.dirname(__file__), "modules")
-old_subpack_path = os.path.join(os.path.dirname(__file__), "subpack")
 subpack_path = os.path.join(os.path.dirname(__file__), "impact_subpack")
 subpack_repo = "https://github.com/ltdrdata/ComfyUI-Impact-Subpack"
 
@@ -71,64 +69,13 @@ def process_wrap(cmd_str, cwd=None, handler=None, env=None):
 # ---
 
 
-pip_list = None
-
-
-def get_installed_packages():
-    global pip_list
-
-    if pip_list is None:
-        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()])
-        except subprocess.CalledProcessError as e:
-            print(f"[ComfyUI-Manager] Failed to retrieve the information of installed pip packages.")
-            return set()
-    
-    return pip_list
-    
-
-def is_installed(name):
-    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):
-    print(f"req_path: {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_installed(line):
-                    return False
-                    
-    return True
-
 try:
     import platform
+    import folder_paths
     from torchvision.datasets.utils import download_url
     import impact.config
 
-
     print("### ComfyUI-Impact-Pack: Check dependencies")
-
-    if "python_embeded" in sys.executable or "python_embedded" in sys.executable:
-        pip_install = [sys.executable, '-s', '-m', 'pip', 'install']
-        pip_upgrade = [sys.executable, '-s', '-m', 'pip', 'install', '-U']
-        mim_install = [sys.executable, '-s', '-m', 'mim', 'install']
-    else:
-        pip_install = [sys.executable, '-m', 'pip', 'install']
-        pip_upgrade = [sys.executable, '-m', 'pip', 'install', '-U']
-        mim_install = [sys.executable, '-m', 'mim', 'install']
-
-
     def ensure_subpack():
         import git
         if os.path.exists(subpack_path):
@@ -145,106 +92,11 @@ try:
         else:
             git.Repo.clone_from(subpack_repo, subpack_path)
 
-        if os.path.exists(old_subpack_path):
-            shutil.rmtree(old_subpack_path)
-
-
-    def ensure_pip_packages_first():
-        subpack_req = os.path.join(subpack_path, "requirements.txt")
-        if os.path.exists(subpack_req) and not is_requirements_installed(subpack_req):
-            process_wrap(pip_install + ['-r', 'requirements.txt'], cwd=subpack_path)
-
-        if not impact.config.get_config()['mmdet_skip']:
-            process_wrap(pip_install + ['openmim'])
-
-            try:
-                import pycocotools
-            except Exception:
-                if platform.system() not in ["Windows"] or platform.machine() not in ["AMD64", "x86_64"]:
-                    print(f"Your system is {platform.system()}; !! You need to install 'libpython3-dev' for this step. !!")
-
-                    process_wrap(pip_install + ['pycocotools'])
-                else:
-                    pycocotools = {
-                        (3, 8): "https://github.com/Bing-su/dddetailer/releases/download/pycocotools/pycocotools-2.0.6-cp38-cp38-win_amd64.whl",
-                        (3, 9): "https://github.com/Bing-su/dddetailer/releases/download/pycocotools/pycocotools-2.0.6-cp39-cp39-win_amd64.whl",
-                        (3, 10): "https://github.com/Bing-su/dddetailer/releases/download/pycocotools/pycocotools-2.0.6-cp310-cp310-win_amd64.whl",
-                        (3, 11): "https://github.com/Bing-su/dddetailer/releases/download/pycocotools/pycocotools-2.0.6-cp311-cp311-win_amd64.whl",
-                    }
-
-                    version = sys.version_info[:2]
-                    url = pycocotools[version]
-                    process_wrap(pip_install + [url])
-
-
-    def ensure_pip_packages_last():
-        my_path = os.path.dirname(__file__)
-        requirements_path = os.path.join(my_path, "requirements.txt")
-        
-        if not is_requirements_installed(requirements_path):
-            process_wrap(pip_install + ['-r', requirements_path])
-            
-        # fallback
-        try:
-            import segment_anything
-            from skimage.measure import label, regionprops
-            import piexif
-        except Exception:
-            process_wrap(pip_install + ['-r', requirements_path])
-
-        # !! cv2 importing test must be very last !!
-        try:
-            from cv2 import setNumThreads
-        except Exception:
-            try:
-                is_open_cv_installed = False
-
-                # upgrade if opencv is installed already
-                if is_installed('opencv-python'):
-                    process_wrap(pip_upgrade + ['opencv-python'])
-                    is_open_cv_installed = True
-
-                if is_installed('opencv-python-headless'):
-                    process_wrap(pip_upgrade + ['opencv-python-headless'])
-                    is_open_cv_installed = True
-
-                if is_installed('opencv-contrib-python'):
-                    process_wrap(pip_upgrade + ['opencv-contrib-python'])
-                    is_open_cv_installed = True
-
-                if is_installed('opencv-contrib-python-headless'):
-                    process_wrap(pip_upgrade + ['opencv-contrib-python-headless'])
-                    is_open_cv_installed = True
-
-                # if opencv is not installed install `opencv-python-headless`
-                if not is_open_cv_installed:
-                    process_wrap(pip_install + ['opencv-python-headless'])
-            except:
-                print(f"[ERROR] ComfyUI-Impact-Pack: failed to install 'opencv-python'. Please, install manually.")
-
-    def ensure_mmdet_package():
-        try:
-            import mmcv
-            import mmdet
-            from mmdet.evaluation import get_classes
-        except Exception:
-            process_wrap(pip_install + ['opendatalab==0.0.9'])
-            process_wrap(pip_install + ['-U', 'openmim'])
-            process_wrap(mim_install + ['mmcv>=2.0.0rc4, <2.1.0'])
-            process_wrap(mim_install + ['mmdet==3.0.0'])
-            process_wrap(mim_install + ['mmengine==0.7.4'])
-
 
     def install():
         subpack_install_script = os.path.join(subpack_path, "install.py")
 
         print(f"### ComfyUI-Impact-Pack: Updating subpack")
-        try:
-            import git
-        except Exception:
-            if not is_installed('GitPython'):
-                process_wrap(pip_install + ['GitPython'])
-
         ensure_subpack()  # The installation of the subpack must take place before ensure_pip. cv2 triggers a permission error.
 
         new_env = os.environ.copy()
@@ -253,29 +105,20 @@ try:
 
         if os.path.exists(subpack_install_script):
             process_wrap([sys.executable, 'install.py'], cwd=subpack_path, env=new_env)
-            if not is_requirements_installed(os.path.join(subpack_path, 'requirements.txt')):
-                process_wrap(pip_install + ['-r', 'requirements.txt'], cwd=subpack_path)
         else:
             print(f"### ComfyUI-Impact-Pack: (Install Failed) Subpack\nFile not found: `{subpack_install_script}`")
 
-        ensure_pip_packages_first()
-
-        if not impact.config.get_config()['mmdet_skip']:
-            ensure_mmdet_package()
-
-        ensure_pip_packages_last()
-
         # Download model
         print("### ComfyUI-Impact-Pack: Check basic models")
-        bbox_path = os.path.join(model_path, "mmdets", "bbox")
         sam_path = os.path.join(model_path, "sams")
         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 os.path.exists(bbox_path):
-                os.makedirs(bbox_path)
-
             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)
 
@@ -291,7 +134,6 @@ try:
 
         impact.config.write_config()
 
-
     install()
 
 except Exception as e:

js/impact-pack.js

@@ -237,7 +237,7 @@ app.registerExtension({
 		if(nodeData.name == "ImpactControlBridge") {
 			const onConnectionsChange = nodeType.prototype.onConnectionsChange;
 			nodeType.prototype.onConnectionsChange = function (type, index, connected, link_info) {
-				if(!link_info || this.inputs[0].type != '*')
+				if(index != 0 || !link_info || this.inputs[0].type != '*')
 					return;
 
 				// assign type
@@ -393,6 +393,7 @@ app.registerExtension({
 		}
 
 		if (nodeData.name === 'ImpactMakeImageList' || nodeData.name === 'ImpactMakeImageBatch' ||
+		    nodeData.name === 'ImpactMakeMaskList' || nodeData.name === 'ImpactMakeMaskBatch' ||
 			nodeData.name === 'CombineRegionalPrompts' ||
 			nodeData.name === 'ImpactCombineConditionings' || nodeData.name === 'ImpactConcatConditionings' ||
 			nodeData.name === 'ImpactSEGSConcat' ||
@@ -405,6 +406,11 @@ app.registerExtension({
 				input_name = "image";
 				break;
 
+			case 'ImpactMakeMaskList':
+			case 'ImpactMakeMaskBatch':
+				input_name = "mask";
+				break;
+
 			case 'ImpactSEGSConcat':
 				input_name = "segs";
 				break;

js/impact-wildcard.js

@@ -6,11 +6,15 @@ let refresh_btn2 = document.querySelector('button[title="Refresh widgets in node
 
 let orig = refresh_btn.onclick;
 
-refresh_btn.onclick = function() {
-	orig();
-	api.fetchApi('/impact/wildcards/refresh');
-};
+if(refresh_btn) {
+    refresh_btn.onclick = function() {
+        orig();
+        api.fetchApi('/impact/wildcards/refresh');
+    };
+}
 
-refresh_btn2.addEventListener('click', function() {
-	api.fetchApi('/impact/wildcards/refresh');
-});
+if(refresh_btn2) {
+    refresh_btn2?.addEventListener('click', function() {
+        api.fetchApi('/impact/wildcards/refresh');
+    });
+}

modules/impact/animatediff_nodes.py

@@ -5,6 +5,13 @@ from impact.core import SEG
 from impact.segs_nodes import SEGSPaste
 
 
+try:
+    from comfy_extras import nodes_differential_diffusion
+except Exception:
+    print(f"\n#############################################\n[Impact Pack] ComfyUI is an outdated version.\n#############################################\n")
+    raise Exception("[Impact Pack] ComfyUI is an outdated version.")
+
+
 class SEGSDetailerForAnimateDiff:
     @classmethod
     def INPUT_TYPES(cls):
@@ -53,6 +60,9 @@ class SEGSDetailerForAnimateDiff:
         new_segs = []
         cnet_image_list = []
 
+        if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
+            model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
+
         for seg in segs[1]:
             cropped_image_frames = None
 

modules/impact/bridge_nodes.py

@@ -19,6 +19,9 @@ class PreviewBridge:
                     "images": ("IMAGE",),
                     "image": ("STRING", {"default": ""}),
                     },
+                "optional": {
+                    "block": ("BOOLEAN", {"default": False, "label_on": "if_empty_mask", "label_off": "never", "tooltip": "is_empty_mask: If the mask is empty, the execution is stopped.\nnever: The execution is never stopped."})
+                    },
                 "hidden": {"unique_id": "UNIQUE_ID", "extra_pnginfo": "EXTRA_PNGINFO"},
                 }
 
@@ -30,6 +33,8 @@ class PreviewBridge:
 
     CATEGORY = "ImpactPack/Util"
 
+    DESCRIPTION = "This is a feature that allows you to edit and send a Mask over a image.\nIf the block is set to 'is_empty_mask', the execution is stopped when the mask is empty."
+
     def __init__(self):
         super().__init__()
         self.output_dir = folder_paths.get_temp_directory()
@@ -70,7 +75,7 @@ class PreviewBridge:
 
         return image, mask.unsqueeze(0), ui_item
 
-    def doit(self, images, image, unique_id, prompt=None, extra_pnginfo=None):
+    def doit(self, images, image, unique_id, block=False, prompt=None, extra_pnginfo=None):
         need_refresh = False
 
         if unique_id not in core.preview_bridge_cache:
@@ -96,9 +101,20 @@ class PreviewBridge:
 
             image = image2
 
+        is_empty_mask = torch.all(mask == 0)
+
+        if block and is_empty_mask and core.is_execution_model_version_supported:
+            from comfy_execution.graph import ExecutionBlocker
+            result = ExecutionBlocker(None), ExecutionBlocker(None)
+        elif block and is_empty_mask:
+            print(f"[Impact Pack] PreviewBridge: ComfyUI is outdated - blocking feature is disabled.")
+            result = pixels, mask
+        else:
+            result = pixels, mask
+
         return {
             "ui": {"images": image},
-            "result": (pixels, mask, ),
+            "result": result,
         }
 
 
@@ -179,7 +195,8 @@ class PreviewBridgeLatent:
                                         "TAEF1", "TAESDXL", "TAESD15", "TAESD3"],),
                     },
                 "optional": {
-                    "vae_opt": ("VAE", )
+                    "vae_opt": ("VAE", ),
+                    "block": ("BOOLEAN", {"default": False, "label_on": "if_empty_mask", "label_off": "never", "tooltip": "is_empty_mask: If the mask is empty, the execution is stopped.\nnever: The execution is never stopped. Instead, it returns a white mask."})
                 },
                 "hidden": {"unique_id": "UNIQUE_ID", "prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
                 }
@@ -192,6 +209,8 @@ class PreviewBridgeLatent:
 
     CATEGORY = "ImpactPack/Util"
 
+    DESCRIPTION = "This is a feature that allows you to edit and send a Mask over a latent image.\nIf the block is set to 'is_empty_mask', the execution is stopped when the mask is empty."
+
     def __init__(self):
         super().__init__()
         self.output_dir = folder_paths.get_temp_directory()
@@ -233,7 +252,7 @@ class PreviewBridgeLatent:
 
         return image, mask, ui_item
 
-    def doit(self, latent, image, preview_method, vae_opt=None, unique_id=None, prompt=None, extra_pnginfo=None):
+    def doit(self, latent, image, preview_method, vae_opt=None, block=False, unique_id=None, prompt=None, extra_pnginfo=None):
         latent_channels = latent['samples'].shape[1]
         preview_method_channels = 16 if 'SD3' in preview_method or 'SC-Prior' in preview_method or 'FLUX.1' in preview_method or 'TAEF1' == preview_method else 4
 
@@ -262,10 +281,14 @@ class PreviewBridgeLatent:
                     del res_latent['noise_mask']
                 else:
                     res_latent = latent
+
+                is_empty_mask = True
             else:
                 res_latent = latent.copy()
                 res_latent['noise_mask'] = mask
 
+                is_empty_mask = torch.all(mask == 1)
+
             res_image = [path_item]
         else:
             decoded_image = decode_latent(latent, preview_method, vae_opt)
@@ -287,11 +310,15 @@ class PreviewBridgeLatent:
                                 'subfolder': 'PreviewBridge',
                                 'type': 'temp',
                             }]
+
+                is_empty_mask = torch.all(mask == 1)
             else:
                 mask = torch.ones(latent['samples'].shape[2:], dtype=torch.float32, device="cpu").unsqueeze(0)
                 res = nodes.PreviewImage().save_images(decoded_image, filename_prefix="PreviewBridge/PBL-", prompt=prompt, extra_pnginfo=extra_pnginfo)
                 res_image = res['ui']['images']
 
+                is_empty_mask = True
+
             path = os.path.join(folder_paths.get_temp_directory(), 'PreviewBridge', res_image[0]['filename'])
             core.set_previewbridge_image(unique_id, path, res_image[0])
             core.preview_bridge_image_id_map[image] = (path, res_image[0])
@@ -300,7 +327,16 @@ class PreviewBridgeLatent:
 
             res_latent = latent
 
+        if block and is_empty_mask and core.is_execution_model_version_supported:
+            from comfy_execution.graph import ExecutionBlocker
+            result = ExecutionBlocker(None), ExecutionBlocker(None)
+        elif block and is_empty_mask:
+            print(f"[Impact Pack] PreviewBridgeLatent: ComfyUI is outdated - blocking feature is disabled.")
+            result = res_latent, mask
+        else:
+            result = res_latent, mask
+
         return {
             "ui": {"images": res_image},
-            "result": (res_latent, mask, ),
+            "result": result,
         }

modules/impact/config.py

@@ -1,7 +1,7 @@
 import configparser
 import os
 
-version_code = [7, 3]
+version_code = [7, 6, 2]
 version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
 
 dependency_version = 22

modules/impact/core.py

@@ -237,7 +237,7 @@ def enhance_detail(image, model, clip, vae, guide_size, guide_size_for_bbox, max
         noise_mask = utils.tensor_gaussian_blur_mask(noise_mask, noise_mask_feather)
         noise_mask = noise_mask.squeeze(3)
 
-        if noise_mask_feather > 0:
+        if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
             model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
 
     if wildcard_opt is not None and wildcard_opt != "":
@@ -383,7 +383,7 @@ def enhance_detail_for_animatediff(image_frames, model, clip, vae, guide_size, g
         noise_mask = utils.tensor_gaussian_blur_mask(noise_mask, noise_mask_feather)
         noise_mask = noise_mask.squeeze(3)
 
-    if noise_mask_feather > 0:
+    if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
         model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
 
     if wildcard_opt is not None and wildcard_opt != "":
@@ -1680,6 +1680,9 @@ class PixelKSampleUpscaler:
                 self.hook.pre_ksample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative,
                                       upscaled_latent, denoise)
 
+        if 'noise_mask' in samples:
+            upscaled_latent['noise_mask'] = samples['noise_mask']
+
         refined_latent = self.sample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise, upscaled_images)
         return refined_latent
 
@@ -1709,6 +1712,9 @@ class PixelKSampleUpscaler:
                 self.hook.pre_ksample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative,
                                       upscaled_latent, denoise)
 
+        if 'noise_mask' in samples:
+            upscaled_latent['noise_mask'] = samples['noise_mask']
+
         refined_latent = self.sample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise, upscaled_images)
         return refined_latent
 

modules/impact/hook_nodes.py

@@ -78,6 +78,8 @@ class PreviewDetailerHookProvider:
 
     CATEGORY = "ImpactPack/Util"
 
+    NOT_IDEMPOTENT = True
+
     def doit(self, quality, unique_id):
         hook = hooks.PreviewDetailerHook(unique_id, quality)
-        return (hook, hook)
+        return hook, hook

modules/impact/impact_pack.py

@@ -29,6 +29,14 @@ import impact.wildcards as wildcards
 from . import hooks
 from . import utils
 
+
+try:
+    from comfy_extras import nodes_differential_diffusion
+except Exception:
+    print(f"\n#############################################\n[Impact Pack] ComfyUI is an outdated version.\n#############################################\n")
+    raise Exception("[Impact Pack] ComfyUI is an outdated version.")
+
+
 warnings.filterwarnings('ignore', category=UserWarning, message='TypedStorage is deprecated')
 
 model_path = folder_paths.models_dir
@@ -62,10 +70,10 @@ class CLIPSegDetectorProvider:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": {
-                        "text": ("STRING", {"multiline": False}),
-                        "blur": ("FLOAT", {"min": 0, "max": 15, "step": 0.1, "default": 7}),
-                        "threshold": ("FLOAT", {"min": 0, "max": 1, "step": 0.05, "default": 0.4}),
-                        "dilation_factor": ("INT", {"min": 0, "max": 10, "step": 1, "default": 4}),
+                        "text": ("STRING", {"multiline": False, "tooltip": "Enter the targets to be detected, separated by commas"}),
+                        "blur": ("FLOAT", {"min": 0, "max": 15, "step": 0.1, "default": 7, "tooltip": "Blurs the detected mask"}),
+                        "threshold": ("FLOAT", {"min": 0, "max": 1, "step": 0.05, "default": 0.4, "tooltip": "Detects only areas that are certain above the threshold."}),
+                        "dilation_factor": ("INT", {"min": 0, "max": 10, "step": 1, "default": 4, "tooltip": "Dilates the detected mask."}),
                     }
                 }
 
@@ -74,6 +82,8 @@ class CLIPSegDetectorProvider:
 
     CATEGORY = "ImpactPack/Util"
 
+    DESCRIPTION = "Provides a detection function using CLIPSeg, which generates masks based on text prompts.\nTo use this node, the CLIPSeg custom node must be installed."
+
     def doit(self, text, blur, threshold, dilation_factor):
         if "CLIPSeg" in nodes.NODE_CLASS_MAPPINGS:
             return (core.BBoxDetectorBasedOnCLIPSeg(text, blur, threshold, dilation_factor), )
@@ -87,8 +97,10 @@ class SAMLoader:
         models = [x for x in folder_paths.get_filename_list("sams") if 'hq' not in x]
         return {
             "required": {
-                "model_name": (models + ['ESAM'], ),
-                "device_mode": (["AUTO", "Prefer GPU", "CPU"],),
+                "model_name": (models + ['ESAM'], {"tooltip": "The detection accuracy varies depending on the SAM model. ESAM can only be used if ComfyUI-YoloWorld-EfficientSAM is installed."}),
+                "device_mode": (["AUTO", "Prefer GPU", "CPU"], {"tooltip": "AUTO: Only applicable when a GPU is available. It temporarily loads the SAM_MODEL into VRAM only when the detection function is used.\n"
+                                                                           "Prefer GPU: Tries to keep the SAM_MODEL on the GPU whenever possible. This can be used when there is sufficient VRAM available.\n"
+                                                                           "CPU: Always loads only on the CPU."}),
             }
         }
 
@@ -97,6 +109,8 @@ class SAMLoader:
 
     CATEGORY = "ImpactPack"
 
+    DESCRIPTION = "Load the SAM (Segment Anything) model. This can be used in places that utilize SAM detection functionality, such as SAMDetector or SimpleDetector.\nThe SAM detection functionality in Impact Pack must use the SAM_MODEL loaded through this node."
+
     def load_model(self, model_name, device_mode="auto"):
         if model_name == 'ESAM':
             if 'ESAM_ModelLoader_Zho' not in nodes.NODE_CLASS_MAPPINGS:
@@ -251,6 +265,9 @@ class DetailerForEach:
         else:
             ordered_segs = segs[1]
 
+        if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
+            model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
+
         for i, seg in enumerate(ordered_segs):
             cropped_image = crop_ndarray4(image.cpu().numpy(), seg.crop_region)  # Never use seg.cropped_image to handle overlapping area
             cropped_image = to_tensor(cropped_image)
@@ -302,6 +319,7 @@ class DetailerForEach:
             if wildcard_item and wildcard_item.strip() == '[STOP]':
                 break
 
+            orig_cropped_image = cropped_image.clone()
             enhanced_image, cnet_pils = core.enhance_detail(cropped_image, model, clip, vae, guide_size, guide_size_for_bbox, max_size,
                                                             seg.bbox, seg_seed, steps, cfg, sampler_name, scheduler,
                                                             cropped_positive, cropped_negative, denoise, cropped_mask, force_inpaint,
@@ -321,7 +339,7 @@ class DetailerForEach:
                 # use image paste
                 image = image.cpu()
                 enhanced_image = enhanced_image.cpu()
-                tensor_paste(image, enhanced_image, (seg.crop_region[0], seg.crop_region[1]), mask)
+                tensor_paste(image, enhanced_image, (seg.crop_region[0], seg.crop_region[1]), mask)  # this code affecting to `cropped_image`.
                 enhanced_list.append(enhanced_image)
 
                 if detailer_hook is not None:
@@ -339,7 +357,7 @@ class DetailerForEach:
             else:
                 new_seg_image = None
 
-            cropped_list.append(cropped_image)
+            cropped_list.append(orig_cropped_image) # NOTE: Don't use `cropped_image`
 
             new_seg = SEG(new_seg_image, seg.cropped_mask, seg.confidence, seg.crop_region, seg.bbox, seg.label, seg.control_net_wrapper)
             new_segs.append(new_seg)
@@ -1232,6 +1250,7 @@ class IterativeLatentUpscale:
             upscale_factor_unit = max(0, (upscale_factor - 1.0) / steps)
 
         current_latent = samples
+        noise_mask = current_latent.get('noise_mask')
         scale = 1
 
         for i in range(steps-1):
@@ -1246,6 +1265,8 @@ class IterativeLatentUpscale:
             print(f"IterativeLatentUpscale[{i+1}/{steps}]: {new_w:.1f}x{new_h:.1f} (scale:{scale:.2f}) ")
             step_info = i, steps
             current_latent = upscaler.upscale_shape(step_info, current_latent, new_w, new_h, temp_prefix)
+            if noise_mask is not None:
+                current_latent['noise_mask'] = noise_mask
 
         if scale < upscale_factor:
             new_w = w*upscale_factor
@@ -1257,7 +1278,7 @@ class IterativeLatentUpscale:
 
         core.update_node_status(unique_id, "", None)
 
-        return (current_latent, upscaler.vae)
+        return current_latent, upscaler.vae
 
 
 class IterativeImageUpscale:
@@ -1640,6 +1661,8 @@ class BitwiseAndMaskForEach:
 
     CATEGORY = "ImpactPack/Operation"
 
+    DESCRIPTION = "Retains only the overlapping areas between the masks included in base_segs and the mask regions of mask_segs. SEGS with no overlapping mask areas are filtered out."
+
     def doit(self, base_segs, mask_segs):
         mask = core.segs_to_combined_mask(mask_segs)
         mask = make_3d_mask(mask)
@@ -1661,6 +1684,8 @@ class SubtractMaskForEach:
 
     CATEGORY = "ImpactPack/Operation"
 
+    DESCRIPTION = "Removes only the overlapping areas between the masks included in base_segs and the mask regions of mask_segs. SEGS with no overlapping mask areas are filtered out."
+
     def doit(self, base_segs, mask_segs):
         mask = core.segs_to_combined_mask(mask_segs)
         mask = make_3d_mask(mask)
@@ -1686,6 +1711,25 @@ class ToBinaryMask:
         return (mask,)
 
 
+class FlattenMask:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                        "masks": ("MASK",),
+                    }
+                }
+
+    RETURN_TYPES = ("MASK",)
+    FUNCTION = "doit"
+
+    CATEGORY = "ImpactPack/Operation"
+
+    def doit(self, masks):
+        masks = utils.make_3d_mask(masks)
+        masks = utils.flatten_mask(masks)
+        return (masks,)
+
+
 class BitwiseAndMask:
     @classmethod
     def INPUT_TYPES(s):

modules/impact/impact_server.py

@@ -24,37 +24,6 @@ import random
 from server import PromptServer
 
 
-@PromptServer.instance.routes.post("/upload/temp")
-async def upload_image(request):
-    upload_dir = folder_paths.get_temp_directory()
-
-    if not os.path.exists(upload_dir):
-        os.makedirs(upload_dir)
-    
-    post = await request.post()
-    image = post.get("image")
-
-    if image and image.file:
-        filename = image.filename
-        if not filename:
-            return web.Response(status=400)
-
-        split = os.path.splitext(filename)
-        i = 1
-        while os.path.exists(os.path.join(upload_dir, filename)):
-            filename = f"{split[0]} ({i}){split[1]}"
-            i += 1
-
-        filepath = os.path.join(upload_dir, filename)
-
-        with open(filepath, "wb") as f:
-            f.write(image.file.read())
-        
-        return web.json_response({"name": filename})
-    else:
-        return web.Response(status=400)
-
-
 sam_predictor = None
 default_sam_model_name = os.path.join(impact_pack.model_path, "sams", "sam_vit_b_01ec64.pth")
 

modules/impact/logics.py

@@ -9,7 +9,6 @@ import impact.core as core
 import re
 import nodes
 import traceback
-from comfy_execution.graph import ExecutionBlocker
 
 class ImpactCompare:
     @classmethod
@@ -674,6 +673,11 @@ class ImpactControlBridge:
     def doit(self, value, mode, behavior="Stop", unique_id=None, prompt=None, extra_pnginfo=None):
         global error_skip_flag
 
+        if core.is_execution_model_version_supported:
+            from comfy_execution.graph import ExecutionBlocker
+        else:
+            print("[Impact Pack] ImpactControlBridge: ComfyUI is outdated. The 'Stop' behavior cannot function properly.")
+
         if behavior == "Stop":
             if mode:
                 return (value, )

modules/impact/segs_nodes.py

@@ -14,6 +14,13 @@ from comfy.cli_args import args
 import math
 
 
+try:
+    from comfy_extras import nodes_differential_diffusion
+except Exception:
+    print(f"\n#############################################\n[Impact Pack] ComfyUI is an outdated version.\n#############################################\n")
+    raise Exception("[Impact Pack] ComfyUI is an outdated version.")
+
+
 class SEGSDetailer:
     @classmethod
     def INPUT_TYPES(s):
@@ -69,6 +76,9 @@ class SEGSDetailer:
         new_segs = []
         cnet_pil_list = []
 
+        if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
+            model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
+
         for i in range(batch_size):
             seed += 1
             for seg in segs[1]:
@@ -1403,8 +1413,6 @@ class SEGSPicker:
 
     RETURN_TYPES = ("SEGS", )
 
-    OUTPUT_NODE = True
-
     FUNCTION = "doit"
 
     CATEGORY = "ImpactPack/Util"

modules/impact/segs_upscaler.py

@@ -98,7 +98,7 @@ def img2img_segs(image, model, clip, vae, seed, steps, cfg, sampler_name, schedu
         noise_mask = tensor_gaussian_blur_mask(noise_mask, noise_mask_feather)
         noise_mask = noise_mask.squeeze(3)
 
-        if noise_mask_feather > 0:
+        if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
             model = nodes_differential_diffusion.DifferentialDiffusion().apply(model)[0]
 
     if control_net_wrapper is not None:

modules/impact/util_nodes.py

@@ -1,6 +1,5 @@
 from impact.utils import any_typ, ByPassTypeTuple, make_3d_mask
 import comfy_extras.nodes_mask
-from comfy_execution.graph import ExecutionBlocker
 from nodes import MAX_RESOLUTION
 import torch
 import comfy
@@ -166,6 +165,8 @@ class GeneralInversedSwitch:
     def doit(self, select, prompt, unique_id, input, **kwargs):
         if core.is_execution_model_version_supported:
             from comfy_execution.graph import ExecutionBlocker
+        else:
+            print("[Impact Pack] InversedSwitch: ComfyUI is outdated. The 'select_on_execution' mode cannot function properly.")
 
         res = []
 
@@ -391,6 +392,26 @@ class ImageBatchToImageList:
         return (images, )
 
 
+class MakeMaskList:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {"mask1": ("MASK",), }}
+
+    RETURN_TYPES = ("MASK",)
+    OUTPUT_IS_LIST = (True,)
+    FUNCTION = "doit"
+
+    CATEGORY = "ImpactPack/Util"
+
+    def doit(self, **kwargs):
+        masks = []
+
+        for k, v in kwargs.items():
+            masks.append(v)
+
+        return (masks, )
+
+
 class MakeImageList:
     @classmethod
     def INPUT_TYPES(s):
@@ -436,6 +457,31 @@ class MakeImageBatch:
             return (image1,)
 
 
+class MakeMaskBatch:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {"mask1": ("MASK",), }}
+
+    RETURN_TYPES = ("MASK",)
+    FUNCTION = "doit"
+
+    CATEGORY = "ImpactPack/Util"
+
+    def doit(self, **kwargs):
+        mask1 = kwargs['mask1']
+        del kwargs['mask1']
+        masks = [utils.make_3d_mask(value) for value in kwargs.values()]
+
+        if len(masks) == 0:
+            return (mask1,)
+        else:
+            for mask2 in masks:
+                if mask1.shape[1:] != mask2.shape[1:]:
+                    mask2 = comfy.utils.common_upscale(mask2.movedim(-1, 1), mask1.shape[2], mask1.shape[1], "lanczos", "center").movedim(1, -1)
+                mask1 = torch.cat((mask1, mask2), dim=0)
+            return (mask1,)
+
+
 class ReencodeLatent:
     @classmethod
     def INPUT_TYPES(s):

modules/impact/utils.py

@@ -5,8 +5,7 @@ import numpy as np
 import folder_paths
 import nodes
 from . import config
-from PIL import Image, ImageFilter
-from scipy.ndimage import zoom
+from PIL import Image
 import comfy
 
 
@@ -579,6 +578,14 @@ def apply_mask_alpha_to_pil(decoded_pil, mask):
     return decoded_rgba
 
 
+def flatten_mask(all_masks):
+    merged_mask = (all_masks[0] * 255).to(torch.uint8)
+    for mask in all_masks[1:]:
+        merged_mask |= (mask * 255).to(torch.uint8)
+
+    return merged_mask
+
+
 def try_install_custom_node(custom_node_url, msg):
     try:
         import cm_global

modules/impact/wildcards.py

@@ -12,7 +12,7 @@ from impact import config
 
 wildcards_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", "wildcards"))
 
-RE_WildCardQuantifier = re.compile(r"(?P<quantifier>\d+)#__(?P<keyword>[\w.\-+/*\\]+)__", re.IGNORECASE)
+RE_WildCardQuantifier = re.compile(r"(?P<quantifier>\d+)#__(?P<keyword>[\w.\-+/*\\]+?)__", re.IGNORECASE)
 wildcard_lock = threading.Lock()
 wildcard_dict = {}
 
@@ -121,7 +121,7 @@ def process(text, seed=None):
             select_sep = ' '
             range_pattern = r'(\d+)(-(\d+))?'
             range_pattern2 = r'-(\d+)'
-            wildcard_pattern = r"__([\w.\-+/*\\]+)__"
+            wildcard_pattern = r"__([\w.\-+/*\\]+?)__"
 
             if len(multi_select_pattern) > 1:
                 r = re.match(range_pattern, options[0])
@@ -200,7 +200,7 @@ def process(text, seed=None):
         return replaced_string, replacements_found
 
     def replace_wildcard(string):
-        pattern = r"__([\w.\-+/*\\]+)__"
+        pattern = r"__([\w.\-+/*\\]+?)__"
         matches = re.findall(pattern, string)
 
         replacements_found = False

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 = "7.3"
+version = "7.6.2"
 license = { file = "LICENSE.txt" }
 dependencies = ["segment-anything", "scikit-image", "piexif", "transformers", "opencv-python-headless", "GitPython", "scipy>=1.11.4"]
 

requirements.txt

@@ -6,3 +6,5 @@ opencv-python-headless
 GitPython
 scipy>=1.11.4
 numpy<2
+dill
+matplotlib