Update app.py

app.py

@@ -73,7 +73,7 @@ CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0")
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
-# Initialize the DiffusionPipeline (this was missing)
+# Initialize the DiffusionPipeline
 pipe = DiffusionPipeline.from_pretrained(
     "SG161222/RealVisXL_V3.0_Turbo",  # or any model of your choice
     torch_dtype=torch.float16,
@@ -81,11 +81,13 @@ pipe = DiffusionPipeline.from_pretrained(
     variant="fp16"
 ).to(device)
 
-# Convert mm to pixels for a specific DPI (300)
+# Convert mm to pixels for a specific DPI (300) and ensure divisible by 8
 def mm_to_pixels(mm, dpi=300):
-    return int((mm / 25.4) * dpi)
+    """Convert mm to pixels and make the dimensions divisible by 8."""
+    pixels = int((mm / 25.4) * dpi)
+    return pixels - (pixels % 8)  # Adjust to the nearest lower multiple of 8
 
-# Default sizes for 75mm and 35mm
+# Default sizes for 75mm and 35mm, rounded to nearest multiple of 8
 size_map = {
     "75mm": (mm_to_pixels(75), mm_to_pixels(75)),  # 75mm in pixels at 300dpi
     "35mm": (mm_to_pixels(35), mm_to_pixels(35)),  # 35mm in pixels at 300dpi