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 +1,100 @@
+import torch
+from PIL import Image
+from .imagefunc import log, pil2tensor, tensor2pil, image2mask, RGB2RGBA
+from .imagefunc import draw_rounded_rectangle, gaussian_blur, mask_area, max_inscribed_rect, min_bounding_rect
+
+
+class LS_RoundedRectangle:
+
+    def __init__(self):
+        self.NODE_NAME = 'RoundedRectangle'
+
+    @classmethod
+    def INPUT_TYPES(self):
+        detect_mode = ['mask_area', 'min_bounding_rect', 'max_inscribed_rect']
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "rounded_rect_radius": ("INT", {"default": 50, "min": 0, "max": 100, "step": 1}),
+                "anti_aliasing": ("INT", {"default": 2, "min": 0, "max": 16, "step": 1}),
+                "top": ("FLOAT", {"default": 8, "min": -100, "max": 100, "step": 0.1}),
+                "bottom": ("FLOAT", {"default": 8, "min": -100, "max": 100, "step": 0.1}),
+                "left": ("FLOAT", {"default": 8, "min": -100, "max": 100, "step": 0.1}),
+                "right": ("FLOAT", {"default": 8, "min": -100, "max": 100, "step": 0.1}),
+                "detect": (detect_mode,),
+                "obj_ext_top": ("FLOAT", {"default": 8, "min": -100, "max": 100, "step": 0.1}),
+                "obj_ext_bottom": ("FLOAT", {"default": 8, "min": -100, "max": 100, "step": 0.1}),
+                "obj_ext_left": ("FLOAT", {"default": 8, "min": -100, "max": 100, "step": 0.1}),
+                "obj_ext_right": ("FLOAT", {"default": 8, "min": -100, "max": 100, "step": 0.1}),
+            },
+            "optional": {
+                "object_mask": ("MASK",),
+                "crop_box": ("BOX",),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE", "MASK",)
+    RETURN_NAMES = ("image", "mask",)
+    FUNCTION = 'rounded_rectangle'
+    CATEGORY = '😺dzNodes/LayerUtility'
+
+    def rounded_rectangle(self, image, rounded_rect_radius, anti_aliasing, top, bottom, left, right,
+                          detect, obj_ext_top, obj_ext_bottom, obj_ext_left, obj_ext_right,
+                          object_mask=None, crop_box=None):
+        ret_images = []
+        ret_masks = []
+
+        for index, img in enumerate(image):
+            orig_image = tensor2pil(torch.unsqueeze(img, 0)).convert('RGB')
+            width, height = orig_image.size
+            black_image = Image.new('L', (width, height), color="black")
+
+            if crop_box is not None:
+                w = crop_box[2] - crop_box[0]
+                h = crop_box[3] - crop_box[1]
+                x1 = crop_box[0] - int(obj_ext_left * w * 0.01)
+                y1 = crop_box[1] - int(obj_ext_top * h * 0.01)
+                x2 = crop_box[2] + int(obj_ext_right * w * 0.01)
+                y2 = crop_box[3] + int(obj_ext_bottom * h * 0.01)
+                bbox = [(x1, y1, x2, y2)]
+            elif object_mask is not None:
+                if object_mask.dim() == 2: object_mask = torch.unsqueeze(object_mask, 0)
+                mask = object_mask[index] if index < len(object_mask) else object_mask[-1]
+                mask = tensor2pil(mask)
+                bluredmask = gaussian_blur(mask, 20).convert('L')
+                x = -10
+                y = -10
+                w = 4
+                h = 4
+                if detect == "min_bounding_rect":
+                    (x, y, w, h) = min_bounding_rect(bluredmask)
+                elif detect == "max_inscribed_rect":
+                    (x, y, w, h) = max_inscribed_rect(bluredmask)
+                else:
+                    (x, y, w, h) = mask_area(mask)
+
+                x1 = x - int(obj_ext_left * w * 0.01)
+                y1 = y - int(obj_ext_top * h * 0.01)
+                x2 = x + w + int(obj_ext_right * w * 0.01)
+                y2 = y + h + int(obj_ext_bottom * h * 0.01)
+                bbox = [(x1, y1, x2, y2)]
+            else:
+                bbox = [(int(left * width * 0.01),
+                         int(top * height * 0.01),
+                         width - int(right * width * 0.01),
+                         height - int(bottom * height * 0.01))
+                        ]
+            rect_mask = draw_rounded_rectangle(black_image, rounded_rect_radius, bbox, anti_aliasing, "white")
+            ret_image = RGB2RGBA(orig_image, rect_mask)
+            ret_images.append(pil2tensor(ret_image))
+            ret_masks.append(image2mask(rect_mask))
+
+        return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
+
+NODE_CLASS_MAPPINGS = {
+    "LayerUtility: RoundedRectangle": LS_RoundedRectangle
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LayerUtility: RoundedRectangle": "LayerUtility: RoundedRectangle"
+}