num_images_per_prompt

app.py

@@ -12,8 +12,8 @@ from PIL import Image, ImageFilter, ImageOps
 DEVICE = "cuda"
 
 MAX_SEED = np.iinfo(np.int32).max
-# FIXED_DIMENSION = 900
-FIXED_DIMENSION = 512 + (512 // 2)
+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.
@@ -127,20 +127,18 @@ def infer(
         seed = secrets.randbelow(MAX_SEED)
 
     prompt = prompt + ".\n" + SYSTEM_PROMPT if prompt else SYSTEM_PROMPT
-    batch_size = 4
     results_images = pipe(
-        prompt=[prompt] * batch_size,
-        image=[image] * batch_size,
+        prompt=prompt,
+        image=image,
         mask_image=mask,
         height=FIXED_DIMENSION,
         width=FIXED_DIMENSION * 2,
-        guidance_scale=guidance_scale,
         num_inference_steps=num_inference_steps,
+        guidance_scale=guidance_scale,
+        num_images_per_prompt=4,
         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