gradio base64 fix02

gradio_app.py

@@ -365,17 +365,17 @@ def process_media_unified(media_input, pupil_selection, tv_model, blink_detectio
         tuple: (result_image, result_text)
     """
     try:
-        # Handle None input
-        if media_input is None:
+        # Handle None or empty input
+        if media_input is None or (isinstance(media_input, str) and not media_input.strip()):
             from PIL import Image
             error_img = Image.new('RGB', (400, 200), 'white')
-            return error_img, "No media input provided. Please upload an image or video."
+            return error_img, "No media input provided. Please upload an image or video or provide a base64 data URL."
 
-        # Check if input is a base64 data URL
-        if isinstance(media_input, str) and media_input.startswith('data:'):
-            return process_base64_media(media_input, pupil_selection, tv_model, blink_detection)
+        # Check if input is a base64 data URL (string input)
+        if isinstance(media_input, str) and media_input.strip().startswith('data:'):
+            return process_base64_media(media_input.strip(), pupil_selection, tv_model, blink_detection)
 
-        # Check if input is an image or video
+        # Check if input is an image or video file object
         if hasattr(media_input, 'name'):
             # It's a file object (video)
             file_path = media_input.name
@@ -511,8 +511,8 @@ def create_gradio_interface():
                         api_text_output = gr.Textbox(label="Analysis Results", lines=10)
 
                 api_submit.click(
-                    fn=process_media_unified_with_fallback,
-                    inputs=[api_media_input, api_file_input, api_pupil_selection, api_model, api_blink_detection],
+                    fn=process_media_unified,
+                    inputs=[api_media_input, api_pupil_selection, api_model, api_blink_detection],
                     outputs=[api_output, api_text_output]
                 )