VersionUP

0.6.0 (Alpha/Beta passed)

.github/workflows/publish_action.yml

@@ -7,14 +7,18 @@ on:
     paths:
       - "pyproject.toml"
 
+permissions:
+  issues: write
+
 jobs:
   publish-node:
     name: Publish Custom Node to registry
     runs-on: ubuntu-latest
+    if: ${{ github.repository_owner == 'Gourieff' }}
     steps:
       - name: Check out code
         uses: actions/checkout@v4
       - name: Publish Custom Node
-        uses: Comfy-Org/publish-node-action@main
+        uses: Comfy-Org/publish-node-action@v1
         with:
-          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} ## Add your own personal access token to your Github secrets and reference it here.
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} ## Add your own personal access token to your Github secrets and reference it here.

README.md

@@ -2,7 +2,7 @@
 
   <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/ReActor_logo_NEW_EN.png?raw=true" alt="logo" width="180px"/>
 
-  ![Version](https://img.shields.io/badge/node_version-0.5.2-brightgreen?style=for-the-badge&labelColor=darkgreen)
+  ![Version](https://img.shields.io/badge/node_version-0.6.0-brightgreen?style=for-the-badge&labelColor=darkgreen)
 
   <!--<sup>
   <font color=brightred>
@@ -51,27 +51,33 @@
 
 ## What's new in the latest update
 
-### 0.5.2 <sub><sup>BETA1</sup></sub>
+### 0.6.0
+
+- New Node `ReActorSetWeight` - you can now set the strength of face swap for `source_image` or `face_model` from 0% to 100% (in 12.5% step)
+
+<center>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.6.0-whatsnew-01.jpg?raw=true" alt="0.6.0-whatsnew-01" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.6.0-whatsnew-02.jpg?raw=true" alt="0.6.0-whatsnew-02" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.6.0-alpha1-01.gif?raw=true" alt="0.6.0-whatsnew-03" width="540px"/>
+</center>
+
+<details>
+	<summary><a>Previous versions</a></summary>
+
+### 0.5.2
 
 - ReSwapper models support. Although Inswapper still has the best similarity, but ReSwapper is evolving - thanks @somanchiu https://github.com/somanchiu/ReSwapper for the ReSwapper models and the ReSwapper project! This is a good step for the Community in the Inswapper's alternative creation!
 
-<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-03.jpg?raw=true" alt="0.5.2-whatsnew-03" width="100%"/>
-<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-04.jpg?raw=true" alt="0.5.2-whatsnew-04" width="100%"/>
+<center>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-03.jpg?raw=true" alt="0.5.2-whatsnew-03" width="75%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-04.jpg?raw=true" alt="0.5.2-whatsnew-04" width="75%"/>
+</center>
 
 You can download ReSwapper models here:
 https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models
 Just put them into the "models/reswapper" directory.
 
-### 0.5.2 <sub><sup>ALPHA3</sup></sub>
-
 - NSFW-detector to not violate [GitHub rules](https://docs.github.com/en/site-policy/acceptable-use-policies/github-misinformation-and-disinformation#synthetic--manipulated-media-tools)
-
-### 0.5.2 <sub><sup>ALPHA2</sup></sub>
-
-- Minor fixes
-
-### 0.5.2 <sub><sup>ALPHA1</sup></sub>
-
 - New node "Unload ReActor Models" - is useful for complex WFs when you need to free some VRAM utilized by ReActor
 
 <img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-01.jpg?raw=true" alt="0.5.2-whatsnew-01" width="100%"/>
@@ -79,10 +85,12 @@ Just put them into the "models/reswapper" directory.
 - Support of ORT CoreML and ROCM EPs, just install onnxruntime version you need
 - Install script improvements to install latest versions of ORT-GPU
 
+<center>
 <img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-02.jpg?raw=true" alt="0.5.2-whatsnew-02" width="50%"/>
+</center>
+
+- Fixes and improvements
 
-<details>
-	<summary><a>Previous versions</a></summary>
 
 ### 0.5.1
 

README_RU.md

@@ -2,7 +2,7 @@
 
   <img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/ReActor_logo_NEW_RU.png?raw=true" alt="logo" width="180px"/>
 
-  ![Version](https://img.shields.io/badge/версия_нода-0.5.2-brightgreen?style=for-the-badge&labelColor=darkgreen)
+  ![Version](https://img.shields.io/badge/версия_нода-0.6.0-brightgreen?style=for-the-badge&labelColor=darkgreen)
   
   <!--<sup>
   <font color=brightred>
@@ -51,27 +51,33 @@
 
 ## Что нового в последнем обновлении
 
-### 0.5.2 <sub><sup>BETA1</sup></sub>
+### 0.6.0
+
+- Новый нод `ReActorSetWeight` - теперь можно установить силу замены лица для `source_image` или `face_model` от 0% до 100% (с шагом 12.5%)
+
+<center>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.6.0-whatsnew-01.jpg?raw=true" alt="0.6.0-whatsnew-01" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.6.0-whatsnew-02.jpg?raw=true" alt="0.6.0-whatsnew-02" width="100%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.6.0-alpha1-01.gif?raw=true" alt="0.6.0-whatsnew-03" width="540px"/>
+</center>
+
+<details>
+	<summary><a>Предыдущие версии</a></summary>
+
+### 0.5.2
 
 - Поддержка моделей ReSwapper. Несмотря на то, что Inswapper по-прежнему даёт лучшее сходство, но ReSwapper развивается - спасибо @somanchiu https://github.com/somanchiu/ReSwapper за эти модели и проект ReSwapper! Это хороший шаг для Сообщества в создании альтернативы Инсваппера!
 
-<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-03.jpg?raw=true" alt="0.5.2-whatsnew-03" width="100%"/>
-<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-04.jpg?raw=true" alt="0.5.2-whatsnew-04" width="100%"/>
+<center>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-03.jpg?raw=true" alt="0.5.2-whatsnew-03" width="75%"/>
+<img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-04.jpg?raw=true" alt="0.5.2-whatsnew-04" width="75%"/>
+</center>
 
 Скачать модели ReSwapper можно отсюда:
 https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models
 Сохраните их в директорию "models/reswapper".
 
-### 0.5.2 <sub><sup>ALPHA3</sup></sub>
-
 - NSFW-детектор, чтобы не нарушать [правила GitHub](https://docs.github.com/en/site-policy/acceptable-use-policies/github-misinformation-and-disinformation#synthetic--manipulated-media-tools)
-
-### 0.5.2 <sub><sup>ALPHA2</sup></sub>
-
-- Небольшие исправления
-
-### 0.5.2 <sub><sup>ALPHA1</sup></sub>
-
 - Новый нод "Unload ReActor Models" - полезен для сложных воркфлоу, когда вам нужно освободить ОЗУ, занятую РеАктором
 
 <img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-01.jpg?raw=true" alt="0.5.2-whatsnew-01" width="100%"/>
@@ -79,10 +85,11 @@ https://huggingface.co/datasets/Gourieff/ReActor/tree/main/models
 - Поддержка ORT CoreML and ROCM EPs, достаточно установить ту версию onnxruntime, которая соответствует вашему GPU
 - Некоторые улучшения скрипта установки для поддержки последней версии ORT-GPU
 
+<center>
 <img src="https://github.com/Gourieff/Assets/blob/main/comfyui-reactor-node/0.5.2-whatsnew-02.jpg?raw=true" alt="0.5.2-whatsnew-02" width="50%"/>
+</center>
 
-<details>
-	<summary><a>Предыдущие версии</a></summary>
+- Исправления и улучшения
 
 ### 0.5.1
 

nodes.py

@@ -72,19 +72,6 @@ if not os.path.exists(REACTOR_MODELS_PATH):
     if not os.path.exists(FACE_MODELS_PATH):
         os.makedirs(FACE_MODELS_PATH)
 
-if not os.path.exists(NSFWDET_MODEL_PATH):
-    os.makedirs(NSFWDET_MODEL_PATH)
-    nd_urls = [
-        "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/config.json",
-        "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/confusion_matrix.png",
-        "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/model.safetensors",
-        "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/preprocessor_config.json",
-    ]
-    for model_url in nd_urls:
-        model_name = os.path.basename(model_url)
-        model_path = os.path.join(NSFWDET_MODEL_PATH, model_name)
-        download(model_url, model_path, model_name)
-
 dir_facerestore_models = os.path.join(models_dir, "facerestore_models")
 os.makedirs(dir_facerestore_models, exist_ok=True)
 folder_paths.folder_names_and_paths["facerestore_models"] = ([dir_facerestore_models], folder_paths.supported_pt_extensions)
@@ -196,7 +183,7 @@ class reactor:
             global FACE_SIZE, FACE_HELPER
 
             self.face_helper = FACE_HELPER
-            
+
             faceSize = 512
             if "1024" in face_restore_model.lower():
                 faceSize = 1024
@@ -233,7 +220,7 @@ class reactor:
                 sd = comfy.utils.load_torch_file(model_path, safe_load=True)
                 facerestore_model = model_loading.load_state_dict(sd).eval()
                 facerestore_model.to(device)
-            
+
             if faceSize != FACE_SIZE or self.face_helper is None:
                 self.face_helper = FaceRestoreHelper(1, face_size=faceSize, crop_ratio=(1, 1), det_model=facedetection, save_ext='png', use_parse=True, device=device)
                 FACE_SIZE = faceSize
@@ -330,7 +317,7 @@ class reactor:
             result = restored_img_tensor
 
         return result
-    
+
     def execute(self, enabled, input_image, swap_model, detect_gender_source, detect_gender_input, source_faces_index, input_faces_index, console_log_level, face_restore_model,face_restore_visibility, codeformer_weight, facedetection, source_image=None, face_model=None, faces_order=None, face_boost=None):
 
         if face_boost is not None:
@@ -356,7 +343,7 @@ class reactor:
 
         if face_model == "none":
             face_model = None
-        
+
         script = FaceSwapScript()
         pil_images = batch_tensor_to_pil(input_image)
 
@@ -413,7 +400,7 @@ class reactor:
 
             if self.restore or not self.face_boost_enabled:
                 result = reactor.restore_face(self,result,face_restore_model,face_restore_visibility,codeformer_weight,facedetection)
-        
+
         else:
             image_black = Image.new("RGB", (512, 512))
             result = batched_pil_to_tensor([image_black])
@@ -428,7 +415,7 @@ class ReActorPlusOpt:
         return {
             "required": {
                 "enabled": ("BOOLEAN", {"default": True, "label_off": "OFF", "label_on": "ON"}),
-                "input_image": ("IMAGE",),               
+                "input_image": ("IMAGE",),
                 "swap_model": (list(model_names().keys()),),
                 "facedetection": (["retinaface_resnet50", "retinaface_mobile0.25", "YOLOv5l", "YOLOv5n"],),
                 "face_restore_model": (get_model_names(get_restorers),),
@@ -462,7 +449,7 @@ class ReActorPlusOpt:
         self.interpolation = "Bicubic"
         self.boost_model_visibility = 1
         self.boost_cf_weight = 0.5
-    
+
     def execute(self, enabled, input_image, swap_model, facedetection, face_restore_model, face_restore_visibility, codeformer_weight, source_image=None, face_model=None, options=None, face_boost=None):
 
         if options is not None:
@@ -472,13 +459,13 @@ class ReActorPlusOpt:
             self.detect_gender_source = options["detect_gender_source"]
             self.input_faces_index = options["input_faces_index"]
             self.source_faces_index = options["source_faces_index"]
-        
+
         if face_boost is not None:
             self.face_boost_enabled = face_boost["enabled"]
             self.restore = face_boost["restore_with_main_after"]
         else:
             self.face_boost_enabled = False
-        
+
         result = reactor.execute(
             self,enabled,input_image,swap_model,self.detect_gender_source,self.detect_gender_input,self.source_faces_index,self.input_faces_index,self.console_log_level,face_restore_model,face_restore_visibility,codeformer_weight,facedetection,source_image,face_model,self.faces_order, face_boost=face_boost
         )
@@ -494,7 +481,7 @@ class LoadFaceModel:
                 "face_model": (get_model_names(get_facemodels),),
             }
         }
-    
+
     RETURN_TYPES = ("FACE_MODEL",)
     FUNCTION = "load_model"
     CATEGORY = "🌌 ReActor"
@@ -510,10 +497,110 @@ class LoadFaceModel:
         return (out, )
 
 
+class ReActorWeight:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_image": ("IMAGE",),
+                "faceswap_weight": (["0%", "12.5%", "25%", "37.5%", "50%", "62.5%", "75%", "87.5%", "100%"], {"default": "50%"}),
+            },
+            "optional": {
+                "source_image": ("IMAGE",),
+                "face_model": ("FACE_MODEL",),
+            }
+        }
+    
+    RETURN_TYPES = ("IMAGE","FACE_MODEL")
+    RETURN_NAMES = ("INPUT_IMAGE","FACE_MODEL")
+    FUNCTION = "set_weight"
+
+    OUTPUT_NODE = True
+
+    CATEGORY = "🌌 ReActor"
+
+    def set_weight(self, input_image, faceswap_weight, face_model=None, source_image=None):
+
+        if input_image is None:
+            logger.error("Please provide `input_image`")
+            return (input_image,None)
+        
+        if source_image is None and face_model is None:
+            logger.error("Please provide `source_image` or `face_model`")
+            return (input_image,None)
+
+        weight = float(faceswap_weight.split("%")[0])
+
+        images = []
+        faces = [] if face_model is None else [face_model]
+        embeddings = [] if face_model is None else [face_model.embedding]
+
+        if weight == 0:
+            images = [input_image]
+            faces = []
+            embeddings = []
+        elif weight == 100:
+            if face_model is None:
+                images = [source_image]
+        else:
+            if weight > 50:
+                images = [input_image]
+                count = round(100/(100-weight))
+            else:
+                if face_model is None:
+                    images = [source_image]
+                count = round(100/(weight))
+            for i in range(count-1):
+                if weight > 50:
+                    if face_model is None:
+                        images.append(source_image)
+                    else:
+                        faces.append(face_model)
+                        embeddings.append(face_model.embedding)
+                else:
+                    images.append(input_image)
+        
+        images_list: List[Image.Image] = []
+
+        apply_patch(1)
+
+        if len(images) > 0:
+
+            for image in images:
+                img = tensor_to_pil(image)
+                images_list.append(img)
+
+            for image in images_list:
+                face = BuildFaceModel.build_face_model(self,image)
+                if isinstance(face, str):
+                    continue
+                faces.append(face)
+                embeddings.append(face.embedding)
+        
+        if len(faces) > 0:
+            blended_embedding = np.mean(embeddings, axis=0)
+            blended_face = Face(
+                bbox=faces[0].bbox,
+                kps=faces[0].kps,
+                det_score=faces[0].det_score,
+                landmark_3d_68=faces[0].landmark_3d_68,
+                pose=faces[0].pose,
+                landmark_2d_106=faces[0].landmark_2d_106,
+                embedding=blended_embedding,
+                gender=faces[0].gender,
+                age=faces[0].age
+            )
+            if blended_face is None:
+                no_face_msg = "Something went wrong, please try another set of images"
+                logger.error(no_face_msg)
+
+        return (input_image,blended_face)
+
+
 class BuildFaceModel:
     def __init__(self):
         self.output_dir = FACE_MODELS_PATH
-    
+
     @classmethod
     def INPUT_TYPES(s):
         return {
@@ -551,14 +638,14 @@ class BuildFaceModel:
             face_model = analyze_faces(image, det_size_half)
             if face_model is not None and len(face_model) > 0:
                 print("...........................................................", end=" ")
-        
+
         if face_model is not None and len(face_model) > 0:
             return face_model[0]
         else:
             no_face_msg = "No face found, please try another image"
             # logger.error(no_face_msg)
             return no_face_msg
-    
+
     def blend_faces(self, save_mode, send_only, face_model_name, compute_method, images=None, face_models=None):
         global BLENDED_FACE_MODEL
         blended_face: Face = BLENDED_FACE_MODEL
@@ -589,7 +676,7 @@ class BuildFaceModel:
                         print(f"{int(((i+1)/n)*100)}%")
                     faces.append(face)
                     embeddings.append(face.embedding)
-            
+
             elif face_models is not None:
 
                 n = len(face_models)
@@ -695,7 +782,7 @@ class RestoreFace:
     def INPUT_TYPES(s):
         return {
             "required": {
-                "image": ("IMAGE",),               
+                "image": ("IMAGE",),
                 "facedetection": (["retinaface_resnet50", "retinaface_mobile0.25", "YOLOv5l", "YOLOv5n"],),
                 "model": (get_model_names(get_restorers),),
                 "visibility": ("FLOAT", {"default": 1, "min": 0.0, "max": 1, "step": 0.05}),
@@ -734,7 +821,7 @@ class MaskHelper:
         # self.force_resize_width = 0
         # self.force_resize_height = 0
         # self.resize_behavior = "source_size"
-    
+
     @classmethod
     def INPUT_TYPES(s):
         bboxs = ["bbox/"+x for x in folder_paths.get_filename_list("ultralytics_bbox")]
@@ -764,7 +851,7 @@ class MaskHelper:
                 "mask_optional": ("MASK",),
             }
         }
-    
+
     RETURN_TYPES = ("IMAGE","MASK","IMAGE","IMAGE")
     RETURN_NAMES = ("IMAGE","MASK","MASK_PREVIEW","SWAPPED_FACE")
     FUNCTION = "execute"
@@ -792,7 +879,7 @@ class MaskHelper:
                 if len(self.labels) > 0:
                     segs, _ = masking_segs.filter(segs, self.labels)
             # segs, _ = masking_segs.filter(segs, "all")
-            
+
             sam_modelname = folder_paths.get_full_path("sams", sam_model_name)
 
             if 'vit_h' in sam_model_name:
@@ -813,12 +900,12 @@ class MaskHelper:
             sam.is_auto_mode = self.device_mode == "AUTO"
 
             combined_mask, _ = core.make_sam_mask_segmented(sam, segs, images, self.detection_hint, sam_dilation, sam_threshold, bbox_expansion, mask_hint_threshold, mask_hint_use_negative)
-        
+
         else:
             combined_mask = mask_optional
 
         # *** MASK TO IMAGE ***:
-        
+
         mask_image = combined_mask.reshape((-1, 1, combined_mask.shape[-2], combined_mask.shape[-1])).movedim(1, -1).expand(-1, -1, -1, 3)
 
         # *** MASK MORPH ***:
@@ -835,12 +922,12 @@ class MaskHelper:
         elif morphology_operation == "close":
             mask_image = self.dilate(mask_image, morphology_distance)
             mask_image = self.erode(mask_image, morphology_distance)
-        
+
         # *** MASK BLUR ***:
-        
+
         if len(mask_image.size()) == 3:
             mask_image = mask_image.unsqueeze(3)
-        
+
         mask_image = mask_image.permute(0, 3, 1, 2)
         kernel_size = blur_radius * 2 + 1
         sigma = sigma_factor * (0.6 * blur_radius - 0.3)
@@ -849,7 +936,7 @@ class MaskHelper:
             mask_image_final = mask_image_final[:, :, :, 0]
 
         # *** CUT BY MASK ***:
-        
+
         if len(swapped_image.shape) < 4:
             C = 1
         else:
@@ -906,7 +993,7 @@ class MaskHelper:
                 single = (swapped_image[i, ymin:ymax+1, xmin:xmax+1,:]).unsqueeze(0)
                 resized = torch.nn.functional.interpolate(single.permute(0, 3, 1, 2), size=(use_height, use_width), mode='bicubic').permute(0, 2, 3, 1)
                 cutted_image[i] = resized[0]
-        
+
         # Preserve our type unless we were previously RGB and added non-opaque alpha due to the mask size
         if C == 1:
             cutted_image = core.tensor2mask(cutted_image)
@@ -959,7 +1046,7 @@ class MaskHelper:
 
         result = image_base.detach().clone()
         face_segment = mask_image_final
-        
+
         for i in range(0, MB):
             if is_empty[i]:
                 continue
@@ -1038,7 +1125,7 @@ class MaskHelper:
                 face_segment[...,3] = mask[i]
 
                 result = rgba2rgb_tensor(result)
-        
+
         return (result,combined_mask,mask_image_final,face_segment,)
 
     def gaussian_blur(self, image, kernel_size, sigma):
@@ -1067,7 +1154,7 @@ class MaskHelper:
         output_tensor = output_reshaped.reshape(batch_size, num_channels, height, width)
 
         return output_tensor
-    
+
     def erode(self, image, distance):
         return 1. - self.dilate(1. - image, distance)
 
@@ -1084,7 +1171,7 @@ class ImageDublicator:
     def INPUT_TYPES(s):
         return {
             "required": {
-                "image": ("IMAGE",),               
+                "image": ("IMAGE",),
                 "count": ("INT", {"default": 1, "min": 0}),
             },
         }
@@ -1096,7 +1183,7 @@ class ImageDublicator:
     CATEGORY = "🌌 ReActor"
 
     def execute(self, image, count):
-        images = [image for i in range(count)]        
+        images = [image for i in range(count)]
         return (images,)
 
 
@@ -1114,7 +1201,7 @@ class ImageRGBA2RGB:
     CATEGORY = "🌌 ReActor"
 
     def execute(self, image):
-        out = rgba2rgb_tensor(image)       
+        out = rgba2rgb_tensor(image)
         return (out,)
 
 
@@ -1123,7 +1210,7 @@ class MakeFaceModelBatch:
     def INPUT_TYPES(s):
         return {
             "required": {
-                "face_model1": ("FACE_MODEL",), 
+                "face_model1": ("FACE_MODEL",),
             },
             "optional": {
                 "face_model2": ("FACE_MODEL",),
@@ -1217,7 +1304,7 @@ class ReActorFaceBoost:
             "restore_with_main_after": restore_with_main_after,
         }
         return (face_boost, )
-    
+
 class ReActorUnload:
     @classmethod
     def INPUT_TYPES(s):
@@ -1243,6 +1330,7 @@ NODE_CLASS_MAPPINGS = {
     "ReActorOptions": ReActorOptions,
     "ReActorFaceBoost": ReActorFaceBoost,
     "ReActorMaskHelper": MaskHelper,
+    "ReActorSetWeight": ReActorWeight,
     # --- Operations with Face Models ---
     "ReActorSaveFaceModel": SaveFaceModel,
     "ReActorLoadFaceModel": LoadFaceModel,
@@ -1262,6 +1350,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ReActorOptions": "ReActor 🌌 Options",
     "ReActorFaceBoost": "ReActor 🌌 Face Booster",
     "ReActorMaskHelper": "ReActor 🌌 Masking Helper",
+    "ReActorSetWeight": "ReActor 🌌 Set Face Swap Weight",
     # --- Operations with Face Models ---
     "ReActorSaveFaceModel": "Save Face Model 🌌 ReActor",
     "ReActorLoadFaceModel": "Load Face Model 🌌 ReActor",

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-reactor"
 description = "(SFW-Friendly) The Fast and Simple Face Swap Extension Node for ComfyUI, based on ReActor SD-WebUI Face Swap Extension"
-version = "0.5.2"
+version = "0.6.0"
 license = { file = "LICENSE" }
 dependencies = ["insightface==0.7.3", "onnx>=1.14.0", "opencv-python>=4.7.0.72", "numpy==1.26.3", "segment_anything", "albumentations>=1.4.16", "ultralytics"]
 

scripts/reactor_sfw.py

@@ -1,14 +1,30 @@
 from transformers import pipeline
 from PIL import Image
 import logging
+import os
+from reactor_utils import download
 from scripts.reactor_logger import logger
 
+def ensure_nsfw_model(nsfwdet_model_path):
+    """Download NSFW detection model if it doesn't exist"""
+    if not os.path.exists(nsfwdet_model_path):
+        os.makedirs(nsfwdet_model_path)
+        nd_urls = [
+            "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/config.json",
+            "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/model.safetensors",
+            "https://huggingface.co/AdamCodd/vit-base-nsfw-detector/resolve/main/preprocessor_config.json",
+        ]
+        for model_url in nd_urls:
+            model_name = os.path.basename(model_url)
+            model_path = os.path.join(nsfwdet_model_path, model_name)
+            download(model_url, model_path, model_name)
+
 SCORE = 0.96
 
 logging.getLogger("transformers").setLevel(logging.ERROR)
 
 def nsfw_image(img_path: str, model_path: str):
-
+    ensure_nsfw_model(model_path)
     with Image.open(img_path) as img:
         predict = pipeline("image-classification", model=model_path)
         result = predict(img)

scripts/reactor_version.py

@@ -1,5 +1,5 @@
 app_title = "ReActor Node for ComfyUI"
-version_flag = "v0.5.2"
+version_flag = "v0.6.0"
 
 COLORS = {
     "CYAN": "\033[0;36m",  # CYAN