Create image_utils.py

inference/utils/image_utils.py

@@ -0,0 +1,16 @@
+from PIL import Image
+import numpy as np
+import torch
+
+def preprocess_controlnet_image(image: Image.Image, device, dtype=torch.float32):
+    image = image.resize((512, 512))
+    img_array = np.array(image).astype(np.float32) / 255.0
+
+    if img_array.ndim == 2:
+        img_array = img_array[None, None, :, :]
+    elif img_array.shape[2] == 3:
+        img_array = img_array.transpose(2, 0, 1)[None, :, :, :]
+    else:
+        raise ValueError("Unexpected image shape.")
+
+    return torch.tensor(img_array, device=device, dtype=dtype)