Update app.py

app.py

@@ -51,7 +51,6 @@ def process_zip(zip_file):
             if not ('real/' in file_list and 'ai/' in file_list):
                 raise ValueError("Zip file must contain 'real' and 'ai' folders")
             
-            yield "Extracting files...", gr.Progress(0)
             z.extractall(temp_dir)
         
         labels, preds, images = [], [], []
@@ -61,8 +60,6 @@ def process_zip(zip_file):
         total_images = sum(len(files) for _, _, files in os.walk(temp_dir))
         processed_images = 0
         
-        yield f"Processing {total_images} images...", gr.Progress(0)
-        
         for folder_name, ground_truth_label in [('real', 1), ('ai', 0)]:
             folder_path = os.path.join(temp_dir, folder_name)
             if not os.path.exists(folder_path):
@@ -93,9 +90,8 @@ def process_zip(zip_file):
                     print(f"Error processing image {img_name}: {e}")
                 
                 processed_images += 1
-                yield f"Processing image {processed_images} of {total_images}...", gr.Progress(processed_images / total_images)
+                gr.Progress(processed_images / total_images)
         
-        yield "Evaluating model...", gr.Progress(1)
         return evaluate_model(labels, preds, false_positives, false_negatives)
     
     except Exception as e:
@@ -320,7 +316,6 @@ def create_gradio_interface():
                     max_file_size=1024  # 1024 MB (1 GB)
                 )
                 batch_btn = gr.Button("Process Batch", interactive=False)
-                progress_output = gr.Textbox(label="Progress")
 
                 with gr.Group():
                     gr.Markdown(f"### Results for {MODEL_NAME}")
@@ -349,7 +344,7 @@ def create_gradio_interface():
         batch_btn.click(
             process_zip,
             zip_file,
-            [progress_output, progress_output, output_acc, output_roc, output_report, output_plots, output_fp_fn],
+            [output_acc, output_roc, output_report, output_plots, output_fp_fn],
             api_name="batch_process"
         )