add reference code

2025-06-23 20:42:49 +08:00
parent 1c44578d9a
commit ca2c13e0ef
131 changed files with 18966 additions and 0 deletions
@@ -0,0 +1,71 @@
+import torch
+from .imagefunc import log, AnyType, gradient, pil2tensor, tensor2pil, load_custom_size
+
+
+
+
+any = AnyType("*")
+
+
+class GradientImageV2:
+
+    def __init__(self):
+        self.NODE_NAME = 'GradientImage V2'
+
+    @classmethod
+    def INPUT_TYPES(self):
+        size_list = ['custom']
+        size_list.extend(load_custom_size())
+        return {
+            "required": {
+                "size": (size_list,),
+                "custom_width": ("INT", {"default": 512, "min": 4, "max": 99999, "step": 1}),
+                "custom_height": ("INT", {"default": 512, "min": 4, "max": 99999, "step": 1}),
+                "angle": ("INT", {"default": 0, "min": -360, "max": 360, "step": 1}),
+                "start_color": ("STRING", {"default": "#FFFFFF"},),
+                "end_color": ("STRING", {"default": "#000000"},),
+            },
+            "optional": {
+                "size_as": (any, {}),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE", )
+    RETURN_NAMES = ("image", )
+    FUNCTION = 'gradient_image_v2'
+    CATEGORY = '😺dzNodes/LayerUtility'
+
+    def gradient_image_v2(self, size, custom_width, custom_height, angle, start_color, end_color, size_as=None):
+
+        if size_as is not None:
+            if size_as.shape[0] > 0:
+                _asimage = tensor2pil(size_as[0])
+            else:
+                _asimage = tensor2pil(size_as)
+            width, height = _asimage.size
+        else:
+            if size == 'custom':
+                width = custom_width
+                height = custom_height
+            else:
+                try:
+                    _s = size.split('x')
+                    width = int(_s[0].strip())
+                    height = int(_s[1].strip())
+                except Exception as e:
+                    log(f'Warning: {self.NODE_NAME} invalid size, check "custom_size.ini"', message_type='warning')
+                    width = custom_width
+                    height = custom_height
+
+
+        ret_image = gradient(start_color, end_color, width, height, angle)
+
+        return (pil2tensor(ret_image), )
+
+NODE_CLASS_MAPPINGS = {
+    "LayerUtility: GradientImage V2": GradientImageV2
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LayerUtility: GradientImage V2": "LayerUtility: GradientImage V2"
+}