Update app.py

app.py

@@ -19,7 +19,8 @@ def softmax(vector):
     e = exp(vector)
     return e / e.sum()
 
-def aiornot(image, model_index):    
+def aiornot(image, model_index):
+    model_index = int(model_index)  # Convert to integer
     mod = models[model_index]
     feature_extractor = AutoFeatureExtractor.from_pretrained(mod)
     model = AutoModelForImageClassification.from_pretrained(mod)
@@ -66,6 +67,10 @@ def calculate_final_prob():
         "AI": f"{1 - fin_out:.4f}"
     }
 
+def clear_results():
+    results_store.clear()
+    return gr.HTML.update(value=""), gr.Label.update(value=None)
+
 with gr.Blocks() as app:
     gr.Markdown("""<center><h1>AI Image Detector<br><h4>(Test Demo - accuracy varies by model)</h4></center>""")
     with gr.Column():
@@ -85,9 +90,9 @@ with gr.Blocks() as app:
                     output_html = gr.HTML()
                     output_label = gr.Label(label="Output")
                     btn.click(aiornot, inputs=[inp, gr.Number(value=i, visible=False)], outputs=[output_html, output_label])
-                    if i == len(models) - 1:  # After the last model, calculate final probability
-                        btn.click(lambda: results_store.clear(), outputs=None)  # Clear results before new detection
-                        btn.click(calculate_final_prob, outputs=fin)
+    
+    btn.click(clear_results, outputs=[output_html, output_label], queue=False)
+    btn.click(calculate_final_prob, outputs=fin)
     load_btn.click(load_url, in_url, [inp, mes])
 
 app.launch(show_api=False, max_threads=24)