Update app.py

app.py

@@ -4,6 +4,7 @@ import huggingface_hub
 import requests
 from PIL import Image
 from io import BytesIO
+import numpy as np
 import gradio as gr
 
 multi_view_diffusion_pipeline = DiffusionPipeline.from_pretrained(
@@ -13,6 +14,29 @@ multi_view_diffusion_pipeline = DiffusionPipeline.from_pretrained(
     trust_remote_code=True,
 ).to("cuda")
 
+image_url = "https://huggingface.co/datasets/dylanebert/3d-arena/resolve/main/inputs/images/a_cat_statue.jpg"
+response = requests.get(image_url)
+image = Image.open(BytesIO(response.content))
+image
+
+def create_image_grid(images):
+    images = [Image.fromarray((img * 255).astype("uint8")) for img in images]
+
+    width, height = images[0].size
+    grid_img = Image.new("RGB", (2 * width, 2 * height))
+
+    grid_img.paste(images[0], (0, 0))
+    grid_img.paste(images[1], (width, 0))
+    grid_img.paste(images[2], (0, height))
+    grid_img.paste(images[3], (width, height))
+
+    return grid_img
+
+image = np.array(image, dtype=np.float32) / 255.0
+images = multi_view_diffusion_pipeline("", image, guidance_scale=5, num_inference_steps=30, elevation=0)
+
+create_image_grid(images)
+
 def run(image):
   image = np.array(image, dtype=np.float32) / 255.0
   images = multi_view_diffusion_pipeline("", image, guidance_scale=5, num_inference_steps=30, elevation=0)