Commit WaterColor and SkinBeauty nodes

README.MD

@@ -13,6 +13,7 @@ Nodes are divided into four groups according to their functions: LayerStyle, Lay
 [中文说明点这里](./README_CN.MD)
 
 ## Update
+* Commit [WaterColor](#WaterColor) and [SkinBeauty](#SkinBeauty) nodes。These are image filters that generate watercolor and skin smoothness effects.
 * Commit [ImageShift](#ImageShift)  node to shift the image and output a displacement seam mask, making it convenient to create continuous textures.
 * Commit [ImageMaskScaleAs](#ImageMaskScaleAs) node to adjust the image or mask size based on the reference image.
 * Commit [ImageScaleRestore](#ImageScaleRestore) node to work with CropByMask for local upscale and repair works.
@@ -600,6 +601,28 @@ This node allows any type of input.
 ![image](image/layerfilter_nodes.png)
 
 
+
+### <a id="table1">SkinBeauty</a>
+Make the skin look smoother.
+![image](image/skin_beauty_example.png)
+
+Node options:
+![image](image/skin_beauty_node.png)
+* smooth: Skin smoothness.
+* threshold: Smooth range. the larger the range with the smaller value.
+* opacity: The opacity of the smoothness.
+
+
+### <a id="table1">WaterColor</a>
+Watercolor painting effect
+![image](image/water_color_example.png)
+
+Node option:
+![image](image/water_color_node.png)
+* line_density: The black line density.
+* opacity: The opacity of watercolor effects.
+
+
 ### <a id="table1">SoftLight</a>
 Soft light effect, the bright highlights on the screen appear blurry.
 ![image](image/soft_light_example.png)

README_CN.MD

@@ -10,6 +10,7 @@ ComfyUI
 * [LayerFilter](#LayerFilter)节点组提供图像效果滤镜。
 
 ## 更新说明
+* 添加[WaterColor](#WaterColor) 和 [SkinBeauty](#SkinBeauty) 节点。这是两个图像滤镜，生成水彩画和磨皮效果。
 * 添加[ImageShift](#ImageShift) 节点，使图片产生位移，可输出位移接缝遮罩，方便制作连续贴图。
 * 添加[ImageMaskScaleAs](#ImageMaskScaleAs) 节点，可根据参考图片调整图像或遮罩大小。
 * 添加[ImageScaleRestore](#ImageScaleRestore) 节点，用于配合CropByMask进行局部放大修复工作。
@@ -586,6 +587,26 @@ mask
 # <a id="table1">LayerFilter</a>
 ![image](image/layerfilter_nodes.png)
 
+### <a id="table1">SkinBeauty</a>
+磨皮效果。
+![image](image/skin_beauty_example.png)
+
+节点选项说明:
+![image](image/skin_beauty_node.png)
+* smooth: 皮肤平滑度。
+* threshold: 磨皮范围。数值越小范围越大。
+* opacity: 磨皮的不透明度。
+
+
+### <a id="table1">WaterColor</a>
+水彩画效果。
+![image](image/water_color_example.png)
+
+节点选项说明:
+![image](image/water_color_node.png)
+* line_density: 线条密度。
+* opacity: 水彩效果的不透明度。
+
 
 ### <a id="table1">SoftLight</a>
 柔光效果。
@@ -642,7 +663,6 @@ LayerFilter:
 * Emboss
 * Contour
 * Findedge
-* PhotoStyle
 * ColorMap
 
 

py/imagefunc.py

@@ -430,6 +430,28 @@ def calculate_mean_std(image:Image):
     std = np.hstack(np.around(std, decimals=2))
     return mean, std
 
+def image_watercolor(image:Image, level:int=50) -> Image:
+    img = pil2cv2(image)
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    factor = (level / 128.0) ** 2
+    sigmaS= int((image.width + image.height) / 5.0 * factor) + 1
+    sigmaR = sigmaS / 32.0 * factor + 0.002
+    img_color = cv2.stylization(img, sigma_s=sigmaS, sigma_r=sigmaR)
+    ret_image = cv2.cvtColor(img_color, cv2.COLOR_BGR2RGB)
+    return cv22pil(ret_image)
+
+
+def image_beauty(image:Image, level:int=50) -> Image:
+    img = pil2cv2(image)
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    factor = (level / 50.0)**2
+    d = int((image.width + image.height) / 256 * factor)
+    sigmaColor = int((image.width + image.height) / 256 * factor)
+    sigmaSpace = int((image.width + image.height) / 160 * factor)
+    img_bit = cv2.bilateralFilter(src=img, d=d, sigmaColor=sigmaColor, sigmaSpace=sigmaSpace)
+    ret_image = cv2.cvtColor(img_bit, cv2.COLOR_BGR2RGB)
+    return cv22pil(ret_image)
+
 '''Mask Functions'''
 
 def expand_mask(mask:torch.Tensor, grow:int, blur:int) -> torch.Tensor:
@@ -458,8 +480,7 @@ def expand_mask(mask:torch.Tensor, grow:int, blur:int) -> torch.Tensor:
     return ret_mask
 
 def mask_invert(mask:torch.Tensor) -> torch.Tensor:
-    _image = mask2image(mask)
-    return image2mask(ImageChops.invert(_image))
+    return 1 - mask
 
 def subtract_mask(masks_a:torch.Tensor, masks_b:torch.Tensor) -> torch.Tensor:
     return torch.clamp(masks_a - masks_b, 0, 255)

py/skin_beauty.py

@@ -0,0 +1,51 @@
+from .imagefunc import *
+
+class SkinBeauty:
+
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(self):
+
+        return {
+            "required": {
+                "image": ("IMAGE", ),
+                "smooth": ("INT", {"default": 20, "min": 1, "max": 64, "step": 1}),  # 磨皮程度
+                "threshold": ("INT", {"default": -10, "min": -255, "max": 255, "step": 1}),  # 高光阈值
+                "opacity": ("INT", {"default": 100, "min": 0, "max": 100, "step": 1}),  # 透明度
+            },
+            "optional": {
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE", "MASK")
+    RETURN_NAMES = ("image", "beauty_mask")
+    FUNCTION = 'skin_beauty'
+    CATEGORY = '😺dzNodes/LayerFilter'
+    OUTPUT_NODE = True
+
+    def skin_beauty(self, image, smooth, threshold, opacity
+                  ):
+
+        _canvas = tensor2pil(image).convert('RGB')
+        _R, _, _, _ = image_channel_split(_canvas, mode='RGB')
+        _otsumask = gray_threshold(_R, otsu=True)
+        _removebkgd = remove_background(_R, _otsumask, '#000000')
+        auto_threshold = get_image_bright_average(_removebkgd) - 16
+        light_mask = gray_threshold(_canvas, auto_threshold + threshold)
+        blur = int((_canvas.width + _canvas.height) / 2000 * smooth)
+        _image = image_beauty(_canvas, level=smooth)
+        _image = gaussian_blur(_image, blur)
+        _image = chop_image(_canvas, _image, 'normal', opacity)
+        _canvas.paste(_image, mask=gaussian_blur(light_mask, blur).convert('L'))
+
+        return (pil2tensor(_canvas), image2mask(light_mask),)
+
+NODE_CLASS_MAPPINGS = {
+    "LayerFilter: SkinBeauty": SkinBeauty
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LayerFilter: SkinBeauty": "LayerFilter: SkinBeauty"
+}

py/soft_light.py

@@ -11,7 +11,6 @@ class SoftLight:
         return {
             "required": {
                 "image": ("IMAGE", ),  #
-
                 "soft": ("FLOAT", {"default": 1, "min": 0.2, "max": 10, "step": 0.01}),  # 模糊
                 "threshold": ("INT", {"default": -10, "min": -255, "max": 255, "step": 1}),  # 高光阈值
                 "opacity": ("INT", {"default": 100, "min": 0, "max": 100, "step": 1}),  # 透明度

py/water_color.py

@@ -0,0 +1,42 @@
+from .imagefunc import *
+
+class WaterColor:
+
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(self):
+
+        return {
+            "required": {
+                "image": ("IMAGE", ),
+                "line_density": ("INT", {"default": 50, "min": 1, "max": 100, "step": 1}),  # 透明度
+                "opacity": ("INT", {"default": 100, "min": 0, "max": 100, "step": 1}),  # 透明度
+            },
+            "optional": {
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = 'water_color'
+    CATEGORY = '😺dzNodes/LayerFilter'
+    OUTPUT_NODE = True
+
+    def water_color(self, image, line_density, opacity
+                  ):
+
+        _canvas = tensor2pil(image).convert('RGB')
+        _image = image_watercolor(_canvas, level=101-line_density)
+        ret_image = chop_image(_canvas, _image, 'normal', opacity)
+
+        return (pil2tensor(ret_image),)
+
+NODE_CLASS_MAPPINGS = {
+    "LayerFilter: WaterColor": WaterColor
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LayerFilter: WaterColor": "LayerFilter: WaterColor"
+}