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app.py

@@ -58,8 +58,12 @@ class ImageEvaluator:
         
         total_files = len(image_files)
         for i, img_path in enumerate(image_files):
-            if progress:
-                progress(i / total_files, f"Processing image {i+1}/{total_files}")
+            # Safe progress update without accessing internal attributes
+            if progress is not None:
+                try:
+                    progress((i + 1) / total_files, f"Processing image {i+1}/{total_files}")
+                except Exception as e:
+                    print(f"Progress update error (non-critical): {e}")
             
             # Extract metadata
             metadata = self.metadata_extractor.extract_metadata(img_path)
@@ -89,8 +93,12 @@ class ImageEvaluator:
         
         total_files = len(image_files)
         for i, img_path in enumerate(image_files):
-            if progress:
-                progress(i / total_files, f"Evaluating image {i+1}/{total_files}")
+            # Safe progress update without accessing internal attributes
+            if progress is not None:
+                try:
+                    progress((i + 1) / total_files, f"Evaluating image {i+1}/{total_files}")
+                except Exception as e:
+                    print(f"Progress update error (non-critical): {e}")
             
             # Get metadata if available
             metadata = self.metadata_cache.get(img_path, {})
@@ -205,7 +213,7 @@ def create_interface():
         'report_path': None
     }
     
-    def upload_images(files, progress=gr.Progress()):
+    def upload_images(files):
         """Handle image upload and processing."""
         # Reset state
         state['uploaded_images'] = []
@@ -221,8 +229,9 @@ def create_interface():
         state['uploaded_images'] = image_paths
         
         # Extract metadata and group images
-        progress(0, "Extracting metadata...")
-        metadata_by_model, metadata_by_prompt = evaluator.process_images(image_paths, progress)
+        # Use a simple progress message instead of Gradio Progress object
+        print("Extracting metadata...")
+        metadata_by_model, metadata_by_prompt = evaluator.process_images(image_paths)
         state['metadata_by_model'] = metadata_by_model
         state['metadata_by_prompt'] = metadata_by_prompt
         
@@ -242,14 +251,15 @@ def create_interface():
             f"Found {len(metadata_by_prompt)} unique prompts."
         )
     
-    def evaluate_images(progress=gr.Progress()):
+    def evaluate_images():
         """Evaluate all uploaded images."""
         if not state['uploaded_images']:
             return "No images uploaded. Please upload images first."
         
         # Evaluate images
-        progress(0, "Evaluating images...")
-        evaluation_results = evaluator.evaluate_images(state['uploaded_images'], progress)
+        # Use a simple progress message instead of Gradio Progress object
+        print("Evaluating images...")
+        evaluation_results = evaluator.evaluate_images(state['uploaded_images'])
         state['evaluation_results'] = evaluation_results
         
         return f"Evaluated {len(evaluation_results)} images with all metrics."
@@ -406,4 +416,5 @@ def create_interface():
 # Launch the application
 if __name__ == "__main__":
     interface = create_interface()
-    interface.launch(share=True)
+    # Remove share=True for HuggingFace Spaces
+    interface.launch()