upscaled examples a bit

app.py

@@ -267,7 +267,7 @@ def run_main_app(semantic_concept, word, script, font_selected, prompt_suffix, n
     # training loop
     t_range = tqdm(range(num_iter))
     gif_frames = []
-    skip = 5
+    skip = 10
     for step in t_range:
         optim.zero_grad()
 
@@ -289,7 +289,7 @@ def run_main_app(semantic_concept, word, script, font_selected, prompt_suffix, n
 
         if step % skip == 0:
             img_tensor = x.detach().cpu()
-            img_tensor = torch.nn.functional.interpolate(img_tensor, size=(200, 200), mode='bilinear', align_corners=False)
+            img_tensor = torch.nn.functional.interpolate(img_tensor, size=(300, 300), mode='bilinear', align_corners=False)
             img_tensor = img_tensor.permute(0, 2, 3, 1).squeeze(0)
             gif_frames += [img_tensor.numpy()]