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extensions_built_in/diffusion_models/omnigen2/src/utils/img_util.py

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+from typing import List
+
+from PIL import Image
+
+import torch
+from torchvision.transforms.functional import to_pil_image
+
+def resize_image(image, max_pixels, img_scale_num):
+    width, height = image.size
+    cur_pixels = height * width
+    ratio = (max_pixels / cur_pixels) ** 0.5
+    ratio = min(ratio, 1.0) # do not upscale input image
+
+    new_height, new_width = int(height * ratio) // img_scale_num * img_scale_num, int(width * ratio) // img_scale_num * img_scale_num
+
+    image = image.resize((new_width, new_height), resample=Image.BICUBIC)
+    return image
+
+def create_collage(images: List[torch.Tensor]) -> Image.Image:
+    """Create a horizontal collage from a list of images."""
+    max_height = max(img.shape[-2] for img in images)
+    total_width = sum(img.shape[-1] for img in images)
+    canvas = torch.zeros((3, max_height, total_width), device=images[0].device)
+    
+    current_x = 0
+    for img in images:
+        h, w = img.shape[-2:]
+        canvas[:, :h, current_x:current_x+w] = img * 0.5 + 0.5
+        current_x += w
+    
+    return to_pil_image(canvas)