init🤩

__init__.py

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+from .scene_generator import SceneGenerator
+
+NODE_CLASS_MAPPINGS = {
+    "Scene Generator": SceneGenerator
+}

requirements.txt

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+Pillow==9.0.1
+requests==2.28.1
+numpy==1.23.1
+torch==1.13.1

scene_generator.py

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+import base64
+import json
+import requests
+from io import BytesIO
+from PIL import Image, ImageOps, ImageChops
+import numpy as np
+import torch
+
+class SceneGenerator:
+    @staticmethod
+    def INPUT_TYPES():
+        return {
+            "required": {
+                "json_img": ("STRING", {"multiline": True}),
+            }
+        }
+
+    RETURN_TYPES = ("STRING", "STRING")
+    FUNCTION = "process"
+
+    def __init__(self):
+        pass
+
+    def process(self, json_img):
+        try:
+            if not json_img:
+                raise ValueError("JSON input must not be empty")
+
+            # Parse the JSON string
+            try:
+                json_data = json.loads(json_img)
+            except json.JSONDecodeError as e:
+                raise ValueError(f"Invalid JSON format: {str(e)}")
+
+            if "json_img" not in json_data:
+                raise ValueError("Invalid JSON input: missing 'json_img' key")
+
+            def sort_key(item):
+                return item['config'].get('z', float('-inf'))
+
+            data = json_data["json_img"]["json"]
+            original_width = json_data["json_img"]["stage"]["width"]
+            original_height = json_data["json_img"]["stage"]["height"]
+            scale_factor = 1
+
+            main_image = Image.new('RGBA', (original_width, original_height), (255, 255, 255, 255))
+            product_image = Image.new('RGBA', (original_width, original_height), (255, 255, 255, 255))
+
+            sorted_data = sorted(data, key=sort_key)
+
+            for item in sorted_data:
+                config = item['config']
+
+                if config["width"] == 0 or config["height"] == 0 or config["scale"]["x"] == 0 or config["scale"]["y"] == 0:
+                    continue
+
+                # Ölçeklendirme
+                config["x"] *= scale_factor
+                config["y"] *= scale_factor
+                config["width"] *= scale_factor
+                config["height"] *= scale_factor
+
+                # Image yükleme
+                response = requests.get(config["src"])
+                image = Image.open(BytesIO(response.content))
+                image = self.apply_flip(image, config["flip"])
+
+                if image.mode != 'RGBA':
+                    image = image.convert('RGBA')
+
+                # Ayarlama ve döndürme
+                new_width = int(image.width * config["scale"]["x"])
+                new_height = int(image.height * config["scale"]["y"])
+                image_resized = image.resize((new_width, new_height), Image.LANCZOS)
+                center_x, center_y = new_width / 2, new_height / 2
+                image_rotated = image_resized.rotate(-config["rotation"], center=(center_x, center_y), expand=True)
+
+                # Döndürme sonrası yeni konum hesaplamaları
+                rotated_width, rotated_height = image_rotated.size
+                rotated_center_x, rotated_center_y = rotated_width / 2, rotated_height / 2
+                new_x = config["x"] + center_x - rotated_center_x
+                new_y = config["y"] + center_y - rotated_center_y
+
+                # Koordinatları merkezleme
+                paste_x = int(config["x"])
+                paste_y = int(config["y"])
+
+                # Product image üzerine prop'ları yapıştırma ve gerektiğinde kesme
+                if config["p_type"] == 'product':
+                    product_image.paste(image_rotated, (int(new_x), int(new_y)), image_rotated)
+                    main_image.paste(image_rotated, (int(new_x), int(new_y)), image_rotated)
+                else:
+                    main_image.paste(image_rotated, (int(new_x), int(new_y)), image_rotated)
+
+            # Convert images to base64
+            product_image_base64 = self.image_to_base64(product_image)
+            main_image_base64 = self.image_to_base64(main_image)
+
+            return (product_image_base64, main_image_base64)
+
+        except Exception as e:
+            raise ValueError(f"An error occurred: {str(e)}")
+
+    def apply_flip(self, image, flip):
+        flip_x, flip_y = json.loads(flip)
+        if flip_x == -1:
+            image = ImageOps.mirror(image)
+        if flip_y == -1:
+            image = ImageOps.flip(image)
+        return image
+
+    def crop_overlapping_area(self, product_image, prop_image, prop_x, prop_y):
+        product_box = (prop_x, prop_y, prop_x + prop_image.width, prop_y + prop_image.height)
+        region = product_image.crop(product_box)
+        cropped_region = ImageChops.subtract(region, prop_image)
+        product_image.paste(cropped_region, product_box)
+
+    def image_to_base64(self, image):
+        buffered = BytesIO()
+        image.save(buffered, format="PNG")
+        img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
+        return img_str