commit RGBValue and Seed node, image scale nodes increases width and height output

README.MD

@@ -70,6 +70,7 @@ When this error has occurred, please check the network environment.
 ## Update
 <font size="4">**If the dependency package error after updating, please reinstall the relevant dependency packages. </font><br />    
 
+* Add the [RGBValue](#RGBValue) node to output the color value as a single decimal value of R, G, and B. Add the [seed](#seed) node to output the seed value. The [ImageMaskScaleAs](#ImageMaskScaleAs), [ImageScaleBySspectRatio](#ImageScaleBySspectRatio), [ImageScaleBySspectRatioV2](#ImageScaleBySspectRatioV2), [ImageScaleRestore](#ImageScaleRestore), [ImageScaleRestoreV2](#ImageScaleRestoreV2) nodes increase ```width```, ```height``` output.
 * Commit [Levels](#Levels) node, it can achieve the same color levels adjustment function as Photoshop.[Sharp&Soft](#Sharp) add the "None" option.
 * Commit [BlendIfMask](#BlendIfMask) node, This node cooperates with ImgaeBlendV2 or ImageBlendAdvanceV2 to achieve the same Blend If function as Photoshop.
 * Commit [ColorTemperature](#ColorTemperature) and [ColorBalance](#ColorBalance) nodes, used to adjust the color temperature and color balance of the picture.
@@ -546,6 +547,8 @@ Outputs:
 * image: The scaled image.
 * mask: If have mask input, the scaled mask will be output.
 * original_size: The original size data of the image is used for subsequent node recovery.
+* width: The output image's width.
+* height: The output image's height.
 
 ### <a id="table1">ImageScaleRestoreV2</a>
 The V2 upgraded version of ImageScaleRestore.
@@ -577,6 +580,8 @@ Outputs:
 * image: If there is an image input, the scaled image will be output.
 * mask: If there is a mask input, the scaled mask will be output.
 * original_size: The original size data of the image is used for subsequent node recovery.
+* width: The output image's width.
+* height: The output image's height.
 
 ### <a id="table1">ImageScaleByAspectRatio</a>
 Scale the image or mask by aspect ratio. the scaled size can be rounded to a multiple of 8 or 16, and can be scaled to the long side size.
@@ -597,6 +602,13 @@ The _fill_ mode does not maintain frame ratio and fills the screen with width an
 * longest_side: When the scale_by_longest_side is set to True, this will be used this value to the long edge of the image. when the original_size have input, this setting will be ignored.
 
 
+Outputs:
+* image: If have image input, the scaled image will be output.
+* mask: If have mask input, the scaled mask will be output.
+* original_size: The original size data of the image is used for subsequent node recovery.
+* width: The output image's width.
+* height: The output image's height.
+
 ### <a id="table1">ImageScaleByAspectRatioV2</a>
 V2 Upgraded Version of ImageScaleByAspectRatio
 
@@ -697,6 +709,14 @@ Node options:
 Output type: 
 * value: String format.
 
+### <a id="table1">RGBValue</a>
+Output the color value as a single R, G, B three decimal values. Supports HEX and DEC formats for ColorPicker node output.
+
+![image](image/RGB_value_example.png)
+
+Node Options:
+* color_value: Supports hexadecimal (HEX) or decimal (DEC) color values and should be of string or tuple type. Forcing in other types will result in an error.
+
 ### <a id="table1">GetColorTone</a>
 Obtain the main color or average color from the image and output RGB values.
 ![image](image/get_color_tone_example.png)

README_CN.MD

@@ -70,6 +70,7 @@ git clone https://github.com/chflame163/ComfyUI_LayerStyle.git
 ## 更新说明
 <font size="4">**如果本插件更新后出现依赖包错误，请重新安装相关依赖包。
 
+  * 添加 [RGBValue](#RGBValue) 节点, 将色值输出为单独的R, G, B三个10进制数值。添加[seed](#seed) 节点，输出种子值。[ImageMaskScaleAs](#ImageMaskScaleAs), [ImageScaleBySspectRatio](#ImageScaleBySspectRatio), [ImageScaleBySspectRatioV2](#ImageScaleBySspectRatioV2), [ImageScaleRestore](#ImageScaleRestore), [ImageScaleRestoreV2](#ImageScaleRestoreV2) 节点增加```width```, ```height``` 输出。
 * 添加 [Levels](#Levels) 节点, 可以实现与Photoshop相同的色阶调整功能。[Sharp&Soft](#Sharp)增加"None"选项。
 * 添加 [BlendIfMask](#BlendIfMask) 节点，该节点与 ImgaeBlendV2 或者 ImageBlendAdvanceV2 配合，可以实现与Photoshop相同的混合颜色带功能。
 * 添加 [ColorTemperature](#ColorTemperature) 和 [ColorBalance](#ColorBalance) 节点，用于调整图片色温和色彩平衡。
@@ -541,6 +542,8 @@ CropByMask的V2升级版。支持crop_box输入，方便裁切相同尺寸的图
 * image: 缩放后的图像。
 * mask: 如果有mask输入，将输出缩放后的mask。
 * original_size: 图像的原始大小数据，用于后续节点进行恢复。
+* width: 输出图片的宽。
+* height: 输出图片的高。
 
 ### <a id="table1">ImageScaleRestoreV2</a>
 ImageScaleRestore的V2升级版。
@@ -570,6 +573,8 @@ ImageScaleRestore的V2升级版。
 * image: 如果有image输入，将输出缩放后的图像。
 * mask: 如果有mask输入，将输出缩放后的遮罩。
 * original_size: 图像的原始大小数据，用于后续节点进行恢复。
+* width: 输出图片的宽。
+* height: 输出图片的高。
 
 
 ### <a id="table1">ImageScaleByAspectRatio</a>
@@ -592,6 +597,8 @@ ImageScaleRestore的V2升级版。
 * image: 如果有image输入，将输出缩放后的图像。
 * mask: 如果有mask输入，将输出缩放后的遮罩。
 * original_size: 图像的原始大小数据，用于后续节点进行恢复。
+* width: 输出图片的宽。
+* height: 输出图片的高。
 
 ### <a id="table1">ImageScaleByAspectRatioV2</a>
 ImageScaleByAspectRatio的V2升级版
@@ -693,6 +700,15 @@ ImageScaleByAspectRatio的V2升级版
 输出:
 * value: 字符串格式。
 
+### <a id="table1">RGBValue</a>
+将色值输出为单独的R, G, B三个10进制数值。支持ColorPicker节点输出的HEX和DEC格式。
+
+![image](image/RGB_value_example.png)
+
+节点选项说明:
+* color_value： 支持十六进制(HEX)或十进制(DEC)色值，应是string或tuple类型，强行接入其他类型将导致错误。
+
+
 ### <a id="table1">GetColorTone</a>
 从图片中获取主颜色或平均色。
 ![image](image/get_color_tone_example.png)

py/color_to_RGBvalue.py

@@ -0,0 +1,45 @@
+from .imagefunc import *
+
+NODE_NAME = 'RGB Value'
+any = AnyType("*")
+
+class ColorValuetoRGBValue:
+
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(self):
+
+        return {
+            "required": {
+                "color_value": (any, {}),
+            },
+            "optional": {
+            }
+        }
+
+    RETURN_TYPES = ("INT", "INT", "INT")
+    RETURN_NAMES = ("R", "G", "B")
+    FUNCTION = 'color_value_to_rgb_value'
+    CATEGORY = '😺dzNodes/LayerUtility'
+
+    def color_value_to_rgb_value(self, color_value,):
+        R, G, B = 0, 0, 0
+        if isinstance(color_value, str):
+            color = Hex_to_RGB(color_value)
+            R, G, B = color[0], color[1], color[2]
+        elif isinstance(color_value, tuple):
+            R, G, B = color_value[0], color_value[1], color_value[2]
+        else:
+            log(f"{NODE_NAME}: color_value input type must be tuple or string.", message_type="error")
+
+        return (R, G, B,)
+
+NODE_CLASS_MAPPINGS = {
+    "LayerUtility: RGB Value": ColorValuetoRGBValue
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LayerUtility: RGB Value": "LayerUtility: RGB Value"
+}

py/data_nodes.py

@@ -2,6 +2,23 @@ from .imagefunc import AnyType
 
 any = AnyType("*")
 
+class SeedNode:
+    def __init__(self):
+        pass
+    @classmethod
+    def INPUT_TYPES(self):
+        return {"required": {
+                "seed":("INT", {"default": 0, "min": 0, "max": 99999999999999999999, "step": 1}),
+            },}
+
+    RETURN_TYPES = ("INT",)
+    RETURN_NAMES = ("seed",)
+    FUNCTION = 'seed_node'
+    CATEGORY = '😺dzNodes/LayerUtility'
+
+    def seed_node(self, seed):
+        return (seed,)
+
 
 class BooleanOperator:
     def __init__(self):
@@ -143,14 +160,14 @@ class BooleanNode:
 
 
 
-
 NODE_CLASS_MAPPINGS = {
     "LayerUtility: BooleanOperator": BooleanOperator,
     "LayerUtility: NumberCalculator": NumberCalculator,
     "LayerUtility: TextBox": TextBoxNode,
     "LayerUtility: Integer": IntegerNode,
     "LayerUtility: Float": FloatNode,
-    "LayerUtility: Boolean": BooleanNode
+    "LayerUtility: Boolean": BooleanNode,
+    "LayerUtility: Seed": SeedNode
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -159,5 +176,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "LayerUtility: TextBox": "LayerUtility: TextBox",
     "LayerUtility: Integer": "LayerUtility: Integer",
     "LayerUtility: Float": "LayerUtility: Float",
-    "LayerUtility: Boolean": "LayerUtility: Boolean"
+    "LayerUtility: Boolean": "LayerUtility: Boolean",
+    "LayerUtility: Seed": "LayerUtility: Seed"
 }

py/image_mask_scale_as.py

@@ -27,8 +27,8 @@ class ImageMaskScaleAs:
             }
         }
 
-    RETURN_TYPES = ("IMAGE", "MASK", "BOX",)
-    RETURN_NAMES = ("image", "mask", "original_size")
+    RETURN_TYPES = ("IMAGE", "MASK", "BOX", "INT", "INT")
+    RETURN_NAMES = ("image", "mask", "original_size", "widht", "height",)
     FUNCTION = 'image_mask_scale_as'
     CATEGORY = '😺dzNodes/LayerUtility'
 
@@ -77,16 +77,16 @@ class ImageMaskScaleAs:
                 ret_masks.append(image2mask(_mask))
         if len(ret_images) > 0 and len(ret_masks) >0:
             log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
-            return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
+            return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), [orig_width, orig_height],target_width, target_height,)
         elif len(ret_images) > 0 and len(ret_masks) == 0:
             log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
-            return (torch.cat(ret_images, dim=0), None, [orig_width, orig_height],)
+            return (torch.cat(ret_images, dim=0), None, [orig_width, orig_height],target_width, target_height,)
         elif len(ret_images) == 0 and len(ret_masks) > 0:
             log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).", message_type='finish')
-            return (None, torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
+            return (None, torch.cat(ret_masks, dim=0), [orig_width, orig_height], target_width, target_height,)
         else:
             log(f"Error: {NODE_NAME} skipped, because the available image or mask is not found.", message_type='error')
-            return (None, None, [orig_width, orig_height],)
+            return (None, None, [orig_width, orig_height], 0, 0,)
 
 NODE_CLASS_MAPPINGS = {
     "LayerUtility: ImageMaskScaleAs": ImageMaskScaleAs

py/image_scale_by_aspect_ratio.py

@@ -33,8 +33,8 @@ class ImageScaleByAspectRatio:
             }
         }
 
-    RETURN_TYPES = ("IMAGE", "MASK", "BOX",)
-    RETURN_NAMES = ("image", "mask", "original_size")
+    RETURN_TYPES = ("IMAGE", "MASK", "BOX", "INT", "INT",)
+    RETURN_NAMES = ("image", "mask", "original_size", "width", "height",)
     FUNCTION = 'image_scale_by_aspect_ratio'
     CATEGORY = '😺dzNodes/LayerUtility'
 
@@ -65,14 +65,14 @@ class ImageScaleByAspectRatio:
             _width, _height = tensor2pil(orig_masks[0]).size
             if (orig_width > 0 and orig_width != _width) or (orig_height > 0 and orig_height != _height):
                 log(f"Error: {NODE_NAME} skipped, because the mask is does'nt match image.", message_type='error')
-                return (None, None, None)
+                return (None, None, None, 0, 0,)
             elif orig_width + orig_height == 0:
                 orig_width = _width
                 orig_height = _height
 
         if orig_width + orig_height == 0:
             log(f"Error: {NODE_NAME} skipped, because the image or mask at least one must be input.", message_type='error')
-            return (None, None, None)
+            return (None, None, None, 0, 0,)
 
         if aspect_ratio == 'original':
             ratio = orig_width / orig_height
@@ -137,16 +137,16 @@ class ImageScaleByAspectRatio:
                 ret_masks.append(image2mask(_mask))
         if len(ret_images) > 0 and len(ret_masks) >0:
             log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
-            return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),[orig_width, orig_height],)
+            return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),[orig_width, orig_height], target_width, target_height,)
         elif len(ret_images) > 0 and len(ret_masks) == 0:
             log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
-            return (torch.cat(ret_images, dim=0), None,[orig_width, orig_height],)
+            return (torch.cat(ret_images, dim=0), None,[orig_width, orig_height], target_width, target_height,)
         elif len(ret_images) == 0 and len(ret_masks) > 0:
             log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).", message_type='finish')
-            return (None, torch.cat(ret_masks, dim=0),[orig_width, orig_height],)
+            return (None, torch.cat(ret_masks, dim=0),[orig_width, orig_height], target_width, target_height,)
         else:
             log(f"Error: {NODE_NAME} skipped, because the available image or mask is not found.", message_type='error')
-            return (None, None, None)
+            return (None, None, None, 0, 0,)
 
 NODE_CLASS_MAPPINGS = {
     "LayerUtility: ImageScaleByAspectRatio": ImageScaleByAspectRatio

py/image_scale_by_aspect_ratio_v2.py

@@ -33,8 +33,8 @@ class ImageScaleByAspectRatioV2:
             }
         }
 
-    RETURN_TYPES = ("IMAGE", "MASK", "BOX",)
-    RETURN_NAMES = ("image", "mask", "original_size")
+    RETURN_TYPES = ("IMAGE", "MASK", "BOX", "INT", "INT",)
+    RETURN_NAMES = ("image", "mask", "original_size", "width", "height",)
     FUNCTION = 'image_scale_by_aspect_ratio'
     CATEGORY = '😺dzNodes/LayerUtility'
 
@@ -65,14 +65,14 @@ class ImageScaleByAspectRatioV2:
             _width, _height = tensor2pil(orig_masks[0]).size
             if (orig_width > 0 and orig_width != _width) or (orig_height > 0 and orig_height != _height):
                 log(f"Error: {NODE_NAME} skipped, because the mask is does'nt match image.", message_type='error')
-                return (None, None, None)
+                return (None, None, None, 0, 0,)
             elif orig_width + orig_height == 0:
                 orig_width = _width
                 orig_height = _height
 
         if orig_width + orig_height == 0:
             log(f"Error: {NODE_NAME} skipped, because the image or mask at least one must be input.", message_type='error')
-            return (None, None, None)
+            return (None, None, None, 0, 0,)
 
         if aspect_ratio == 'original':
             ratio = orig_width / orig_height
@@ -136,16 +136,16 @@ class ImageScaleByAspectRatioV2:
                 ret_masks.append(image2mask(_mask))
         if len(ret_images) > 0 and len(ret_masks) >0:
             log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
-            return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),[orig_width, orig_height],)
+            return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),[orig_width, orig_height], target_width, target_height,)
         elif len(ret_images) > 0 and len(ret_masks) == 0:
             log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
-            return (torch.cat(ret_images, dim=0), None, [orig_width, orig_height],)
+            return (torch.cat(ret_images, dim=0), None, [orig_width, orig_height], target_width, target_height,)
         elif len(ret_images) == 0 and len(ret_masks) > 0:
             log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).", message_type='finish')
-            return (None, torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
+            return (None, torch.cat(ret_masks, dim=0), [orig_width, orig_height], target_width, target_height,)
         else:
             log(f"Error: {NODE_NAME} skipped, because the available image or mask is not found.", message_type='error')
-            return (None, None, None)
+            return (None, None, None, 0, 0,)
 
 NODE_CLASS_MAPPINGS = {
     "LayerUtility: ImageScaleByAspectRatio V2": ImageScaleByAspectRatioV2

py/image_scale_restore.py

@@ -24,8 +24,8 @@ class ImageScaleRestore:
             }
         }
 
-    RETURN_TYPES = ("IMAGE", "MASK", "BOX",)
-    RETURN_NAMES = ("image", "mask", "original_size")
+    RETURN_TYPES = ("IMAGE", "MASK", "BOX", "INT", "INT")
+    RETURN_NAMES = ("image", "mask", "original_size", "width", "height",)
     FUNCTION = 'image_scale_restore'
     CATEGORY = '😺dzNodes/LayerUtility'
 
@@ -98,7 +98,7 @@ class ImageScaleRestore:
             ret_masks.append(image2mask(ret_mask))
 
         log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
-        return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
+        return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), [orig_width, orig_height], target_width, target_height,)
 
 
 NODE_CLASS_MAPPINGS = {

py/image_scale_restore_v2.py

@@ -25,8 +25,8 @@ class ImageScaleRestoreV2:
             }
         }
 
-    RETURN_TYPES = ("IMAGE", "MASK", "BOX",)
-    RETURN_NAMES = ("image", "mask", "original_size")
+    RETURN_TYPES = ("IMAGE", "MASK", "BOX", "INT", "INT")
+    RETURN_NAMES = ("image", "mask", "original_size", "width", "height",)
     FUNCTION = 'image_scale_restore'
     CATEGORY = '😺dzNodes/LayerUtility'
 
@@ -106,7 +106,7 @@ class ImageScaleRestoreV2:
             ret_masks.append(image2mask(ret_mask))
 
         log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
-        return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
+        return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), [orig_width, orig_height], target_width, target_height,)
 
 
 NODE_CLASS_MAPPINGS = {

py/imagefunc.py

@@ -1,7 +1,6 @@
 """Image process functions for ComfyUI nodes
 by chflame https://github.com/chflame163
-"""
-"""
+
 @author: chflame
 @title: LayerStyle
 @nickname: LayerStyle