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 +1,88 @@
+import torch
+from PIL import Image
+from .imagefunc import log, tensor2pil, pil2tensor, image2mask, draw_border, gaussian_blur, shift_image
+
+
+class ImageShift:
+
+    def __init__(self):
+        self.NODE_NAME = 'ImageShift'
+
+    @classmethod
+    def INPUT_TYPES(self):
+
+        return {
+            "required": {
+                "image": ("IMAGE", ),  #
+                "shift_x": ("INT", {"default": 256, "min": -9999, "max": 9999, "step": 1}),
+                "shift_y": ("INT", {"default": 256, "min": -9999, "max": 9999, "step": 1}),
+                "cyclic": ("BOOLEAN", {"default": True}),  # 是否循环重复
+                "background_color": ("STRING", {"default": "#000000"}),
+                "border_mask_width": ("INT", {"default": 20, "min": 0, "max": 999, "step": 1}),
+                "border_mask_blur": ("INT", {"default": 12, "min": 0, "max": 999, "step": 1}),
+            },
+            "optional": {
+                "mask": ("MASK",),  #
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE", "MASK", "MASK",)
+    RETURN_NAMES = ("image", "mask", "border_mask")
+    FUNCTION = 'image_shift'
+    CATEGORY = '😺dzNodes/LayerUtility'
+
+    def image_shift(self, image, shift_x, shift_y,
+                    cyclic, background_color,
+                    border_mask_width, border_mask_blur,
+                    mask=None
+                    ):
+
+        ret_images = []
+        ret_masks = []
+        ret_border_masks = []
+
+        l_images = []
+        l_masks = []
+
+
+        for l in image:
+            l_images.append(torch.unsqueeze(l, 0))
+            m = tensor2pil(l)
+            if m.mode == 'RGBA':
+                l_masks.append(m.split()[-1])
+            else:
+                l_masks.append(Image.new('L', size=m.size, color='white'))
+        if mask is not None:
+            if mask.dim() == 2:
+                mask = torch.unsqueeze(mask, 0)
+            l_masks = []
+            for m in mask:
+                l_masks.append(tensor2pil(torch.unsqueeze(m, 0)).convert('L'))
+
+        shift_x, shift_y = -shift_x, -shift_y
+        for i in range(len(l_images)):
+            _image = l_images[i]
+            _canvas = tensor2pil(_image).convert('RGB')
+            _mask = l_masks[i] if len(l_masks) < i else l_masks[-1]
+            _border =  Image.new('L', size=_canvas.size, color='black')
+            _border = draw_border(_border, border_width=border_mask_width, color='#FFFFFF')
+            _border = _border.resize(_canvas.size)
+            _canvas = shift_image(_canvas, shift_x, shift_y, background_color=background_color, cyclic=cyclic)
+            _mask = shift_image(_mask, shift_x, shift_y, background_color='#000000', cyclic=cyclic)
+            _border = shift_image(_border, shift_x, shift_y, background_color='#000000', cyclic=cyclic)
+            _border = gaussian_blur(_border, border_mask_blur)
+
+            ret_images.append(pil2tensor(_canvas))
+            ret_masks.append(image2mask(_mask))
+            ret_border_masks.append(image2mask(_border))
+
+        log(f"{self.NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
+        return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), torch.cat(ret_border_masks, dim=0),)
+
+NODE_CLASS_MAPPINGS = {
+    "LayerUtility: ImageShift": ImageShift
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LayerUtility: ImageShift": "LayerUtility: ImageShift"
+}