app.py

app.py

@@ -6,7 +6,9 @@ from PIL import Image
 import os
 import time
 
-from utils.utils import load_cn_model, load_cn_config, load_tagger_model, load_lora_model, resize_image_aspect_ratio, base_generation
+from utils.dl_utils import load_cn_model, load_cn_config, load_tagger_model, load_lora_model
+from utils.image_utils import resize_image_aspect_ratio, base_generation
+
 from utils.prompt_utils import execute_prompt, remove_color, remove_duplicates
 from utils.tagger import modelLoad, analysis
 

utils/image_utils.py

@@ -0,0 +1,45 @@
+import os
+
+import requests
+from tqdm import tqdm
+import shutil
+
+from PIL import Image, ImageOps
+import numpy as np
+import cv2
+
+def resize_image_aspect_ratio(image):
+    # 元の画像サイズを取得
+    original_width, original_height = image.size
+
+    # アスペクト比を計算
+    aspect_ratio = original_width / original_height
+
+    # 標準のアスペクト比サイズを定義
+    sizes = {
+        1: (1024, 1024),  # 正方形
+        4/3: (1152, 896),  # 横長画像
+        3/2: (1216, 832),
+        16/9: (1344, 768),
+        21/9: (1568, 672),
+        3/1: (1728, 576),
+        1/4: (512, 2048),  # 縦長画像
+        1/3: (576, 1728),
+        9/16: (768, 1344),
+        2/3: (832, 1216),
+        3/4: (896, 1152)
+    }
+
+    # 最も近いアスペクト比を見つける
+    closest_aspect_ratio = min(sizes.keys(), key=lambda x: abs(x - aspect_ratio))
+    target_width, target_height = sizes[closest_aspect_ratio]
+
+    # リサイズ処理
+    resized_image = image.resize((target_width, target_height), Image.LANCZOS)
+
+    return resized_image
+
+
+def base_generation(size, color):
+    canvas = Image.new("RGBA", size, color) 
+    return canvas