Update app.py

app.py

@@ -5,7 +5,7 @@ try:
     captioning_pipeline = pipeline(
         "image-to-text", 
         model="nlpconnect/vit-gpt2-image-captioning", 
-        device=-1 #-1 CPU 0 GPU
+        device=-1  # -1 CPU, 0 GPU
     )
 except Exception as e:
     captioning_pipeline = None
@@ -19,15 +19,14 @@ def generate_caption(image):
     if captioning_pipeline is None:
         return "Model failed to load. Check logs for details."
 
-       try:
-           results = captioning_pipeline(image, max_new_tokens=50) # Set a limit on caption length
-           caption = results[0]['generated_text']
-           return caption
+    try:
+        results = captioning_pipeline(image, max_new_tokens=50)  # Set a limit on caption length
+        caption = results[0]['generated_text']
+        return caption
     except Exception as e:
         return f"An error occurred during generation: {e}"
 
-#Gradio Interface Definition
-
+# Gradio Interface Definition
 example_paths = [
     ["examples/dog_park.jpg"],
     ["examples/city_scene.png"],
@@ -40,10 +39,9 @@ iface = gr.Interface(
     outputs=gr.Textbox(label="Generated Caption"),
     title="Custom Image Caption Generator (Hugging Face Space)",
     description="Upload an image and have a generative AI model describe what it sees.",
-    examples=example_paths,  # <-- Add the examples list here
+    examples=example_paths,
     allow_flagging="auto"
 )
 
-# --- 4. Launch ---
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch()