Update examples

app.py

@@ -15,7 +15,10 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model.to(device)
 
 # load image examples
-urls = ['https://assetsnffrgf-a.akamaihd.net/assets/m/502013285/univ/art/502013285_univ_sqr_xl.jpg']
+urls = ['https://avatars.githubusercontent.com/u/326577?v=4',
+        'https://upload.wikimedia.org/wikipedia/commons/thumb/6/6e/Football_%28soccer_ball%29.svg/1200px-Football_%28soccer_ball%29.svg.png'
+        'https://ichef.bbci.co.uk/news/976/cpsprodpb/12A9B/production/_111434467_gettyimages-1143489763.jpg',
+        ]
 for idx, url in enumerate(urls):
   image = Image.open(requests.get(url, stream=True).raw)
   image.save(f"image_{idx}.png")
@@ -42,7 +45,9 @@ def process_image(image):
     samples_img = [np.reshape(np.rint(127.5 * (clusters[s] + 1.0)), [n_px, n_px, 3]).astype(np.uint8) for s in samples] 
     
     # stack images horizontally
-    result = np.hstack(samples_img)
+    row1 = np.hstack(samples_img[:4])
+    row2 = np.hstack(samples_img[4:])
+    result = np.vstack([row1, row2])
     
     # return as PIL Image
     completion = Image.fromarray(result)
@@ -52,7 +57,7 @@ def process_image(image):
 title = "Interactive demo: ImageGPT"
 description = "Demo for OpenAI's ImageGPT: Generative Pretraining from Pixels. To use it, simply upload an image or use the example image below and click 'submit'. Results will show up in a few seconds."
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2109.10282'>ImageGPT: Generative Pretraining from Pixels</a> | <a href='https://openai.com/blog/image-gpt/'>Official blog</a></p>"
-examples =[["image_0.png"]]
+examples =[f"image_{idx}.png" for idx in range(len(urls))]
 
 iface = gr.Interface(fn=process_image, 
                      inputs=gr.inputs.Image(type="pil"),