Set batch size to 4

app.py

@@ -12,7 +12,8 @@ from PIL import Image, ImageFilter, ImageOps
 DEVICE = "cuda"
 
 MAX_SEED = np.iinfo(np.int32).max
-FIXED_DIMENSION = 900
+# FIXED_DIMENSION = 900
+FIXED_DIMENSION = 512 + (512 // 2)
 FIXED_DIMENSION = (FIXED_DIMENSION // 16) * 16
 
 SYSTEM_PROMPT = r"""This two-panel split-frame image showcases a furniture in as a product shot versus styled in a room.
@@ -119,14 +120,14 @@ def infer(
     mask = ImageOps.invert(mask)
     # Blur the mask
     mask = mask.filter(ImageFilter.GaussianBlur(radius=10))
-    # Convert to 1 channel
-    mask = mask.convert("L")
+    # Convert to 3 channel
+    mask = mask.convert("RGB")
 
     if randomize_seed:
         seed = secrets.randbelow(MAX_SEED)
 
     prompt = prompt + ".\n" + SYSTEM_PROMPT if prompt else SYSTEM_PROMPT
-    batch_size = 1
+    batch_size = 4
     results_images = pipe(
         prompt=[prompt] * batch_size,
         image=[image] * batch_size,
@@ -138,6 +139,8 @@ def infer(
         generator=torch.Generator("cpu").manual_seed(seed),
     )["images"]
 
+    print(len(results_images))
+
     cropped_images = [
         image.crop((FIXED_DIMENSION, 0, FIXED_DIMENSION * 2, FIXED_DIMENSION))
         for image in results_images
@@ -196,7 +199,6 @@ with gr.Blocks(css=css) as demo:
                 show_label=False,
                 columns=2,
                 height=600,
-                preview=True,
             )
 
         with gr.Accordion("Advanced Settings", open=False):