updated the MaskFromFaceModel node.

Author: zhangp365

README.md

@@ -49,7 +49,9 @@ This node splits one mask into two masks of the same size according to the area
 This node is designed for growing masks quickly. When using the official or other mask growth nodes, the speed slows down significantly with large grow values, such as above 20. In contrast, this node maintains consistent speed regardless of the grow value.
 
 ## MaskFromFaceModel
-Generates a mask from the face model of the Reactor face swap node output. The mask covers the facial area below the eyes, excluding the forehead. If the forehead is crucial for your application, it's recommended to use a different mask or adjust the generated mask accordingly.
+Generates a mask from the face model of the Reactor face swap node. The mask covers the facial area below the eyes, excluding the forehead. Enabling add_bbox_upper_points provides a rough approximation but lacks precision. If the forehead is essential for your application, consider using a different mask or adjusting the generated mask as needed.
+
+<img src="assets/maskFromFacemodel.png" width="100%"/>
 
 ## MaskAutoSelector
 Check the three input masks. If any are available, return the first. If none are available, raise an exception.

assets/maskFromFacemodel.png

@@ -22,6 +22,7 @@
 from comfy_extras.nodes_upscale_model import ImageUpscaleWithModel
 from math import dist
 import folder_paths
+from .utils import tensor2np,np2tensor
 
 config_dir = os.path.join(folder_paths.base_path, "config")
 if not os.path.exists(config_dir):
@@ -532,22 +533,31 @@ class MaskFromFaceModel:
 
     @classmethod
     def INPUT_TYPES(self):
-
         return {
-            "required": {
-                "face_model": ("FACE_MODEL", ),
-                "size_as": ("IMAGE",),
+            "required": {                
+                "image": ("IMAGE",),
                 "max_face_number": ("INT", {"default": -1, "min": -1, "max": 99, "step": 1}),
+                "add_bbox_upper_points": ("BOOLEAN", {"default": False}),  # 新增参数
             },
             "optional": {
+                "faceanalysis": ("FACEANALYSIS", ),
+                "face_model": ("FACE_MODEL", ),
             }
         }
 
     RETURN_TYPES = ("MASK",)
     FUNCTION = 'mask_get'
     CATEGORY = 'utils/mask'
 
-    def mask_get(self, face_model, size_as, max_face_number):
+    def mask_get(self, image, max_face_number, add_bbox_upper_points, faceanalysis=None, face_model=None):
+        if faceanalysis is None and face_model is None:
+            raise Exception("both faceanalysis and face_model are none!")
+        
+        if face_model is None:
+            image_np = tensor2np(image)
+            image_np = image_np[0] if isinstance(image_np, list) else image_np
+            face_model = self.analyze_faces(faceanalysis, image_np)
+
         if not isinstance(face_model,list):
             face_models = [face_model]
         else:
@@ -556,11 +566,28 @@ def mask_get(self, face_model, size_as, max_face_number):
         if max_face_number !=-1 and len(face_model) > max_face_number:
             face_models = self.remove_unavaible_face_models(face_models=face_models,max_people_number=max_face_number)
 
-        h, w = size_as.shape[-3:-1]
+        h, w = image.shape[-3:-1]
 
         result = np.zeros((h, w), dtype=np.uint8)
         for face in face_models:
             points = face.landmark_2d_106.astype(np.int32)  # Convert landmarks to integer format
+            
+            if add_bbox_upper_points:
+                  # 获取bbox的坐标
+                x1, y1 = face.bbox[0:2]
+                x2, y2 = face.bbox[2:4]
+                
+                # 计算上边的1/4和3/4位置的点
+                width = x2 - x1
+                left_quarter_x = x1 + width // 4
+                right_quarter_x = x2 - width // 4
+                
+                # 创建两个新点
+                left_quarter_point = np.array([left_quarter_x, y1], dtype=np.int32)
+                right_quarter_point = np.array([right_quarter_x, y1], dtype=np.int32)
+                
+                # 将两个点添加到landmarks中
+                points = np.vstack((points, left_quarter_point, right_quarter_point))
 
             points = points.reshape((-1, 1, 2))  # Reshape for cv2.drawContours
 
@@ -603,7 +630,15 @@ def get_max_distance(self, keypoints):
 
         return max_distance
 
-
+    def analyze_faces(self, insightface, img_data: np.ndarray):
+        for size in [(size, size) for size in range(640, 320, -320)]:
+            insightface.det_model.input_size = size
+            face = insightface.get(img_data)
+            if face:                
+                if 640 not in size:
+                    print(f"\033[33mINFO: InsightFace detection resolution lowered to {size}.\033[0m")
+                break
+        return face 
 class MaskCoverFourCorners:
 
     @classmethod

py/nodes.py

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-utils-nodes"
 description = "Nodes:LoadImageWithSwitch, ImageBatchOneOrMore, ModifyTextGender, GenderControlOutput, ImageCompositeMaskedWithSwitch, ImageCompositeMaskedOneByOne, ColorCorrectOfUtils, SplitMask, MaskFastGrow, CheckpointLoaderSimpleWithSwitch, ImageResizeTo8x, MatchImageRatioToPreset, UpscaleImageWithModelIfNeed, MaskFromFaceModel, MaskCoverFourCorners, DetectorForNSFW, DeepfaceAnalyzeFaceAttributes etc."
-version = "1.1.8"
+version = "1.1.9"
 license = { file = "LICENSE" }
 dependencies = []