convert n_targets to int, wording change

app.py

@@ -27,7 +27,7 @@ def process_image(input_image, learning_rate, iterations, n_targets, seed):
 
     
     torch.manual_seed(int(seed))
-    random_indices = torch.randperm(1000)[:n_targets].to(pixel_values.device)
+    random_indices = torch.randperm(1000)[:int(n_targets)].to(pixel_values.device)
 
     for iteration in range(int(iterations)):
         model.zero_grad()
@@ -55,7 +55,7 @@ iface = gr.Interface(
         gr.Number(value=4.0, label="Learning Rate"), 
         gr.Number(value=4, label="Iterations"),
         gr.Number(value=420, label="Seed"),
-        gr.Number(value=50, minimum=1, maximum=1000, label="n target classes"),
+        gr.Number(value=50, minimum=1, maximum=1000, label="Number of Random Target Class Activations to Maximise"),
     ],
     outputs=[gr.Image(type="numpy", label="ViT-Dreamed Image")]
 )