Update app.py

app.py

@@ -138,13 +138,17 @@ def detect_video(video):
     # Release resources
     cap.release()
 
-def display_two_videos():
-    # Replace these paths with the paths to your video files
-    video_path_1 = "data/c_base_detected.mp4"
-    video_path_2 = "data/c_tuned_detected.mp4"
+# def display_two_videos():
+#     # Replace these paths with the paths to your video files
+#     video_path_1 = "data/c_base_detected.mp4"
+#     video_path_2 = "data/c_tuned_detected.mp4"
     
+#     return open(video_path_1, "rb"), open(video_path_2, "rb")
+
+def display_two_videos(video_path_1, video_path_2):
     return open(video_path_1, "rb"), open(video_path_2, "rb")
 
+
 label_id_offset = 0    
 REPO_ID = "apailang/mytfodmodel"
 detection_model = load_model(REPO_ID)
@@ -215,12 +219,16 @@ tuned_image = gr.Interface(
 
 video = gr.Interface(
     fn=display_two_videos,
+    inputs=[
+        gr.inputs.Textbox(label="Path to detected base model Video",value="data/c_base_detected.mp4",info="video has been preprocessed"),
+        gr.inputs.Textbox(label="Path to tuned base model  Video",value="data/c_tuned_detected.mp4",info="video has been preprocessed")
+    ],
     outputs=[gr.Video(label="base model"), gr.Video(label="Tuned model")],  # Specify video outputs
-    title="Two Videos Display",
-    description="Displays two videos side by side."
+    title="Comparing base vs tuned detected video",
+    description="using SSD mobile net V2 320x320. Model has been customed trained to detect Character of Luffy and Chopper"
 )
 
-demo = gr.TabbedInterface([base_image,tuned_image, video], ["Image (base model)","Image (tuned model)", "display Video"])
+demo = gr.TabbedInterface([base_image,tuned_image, video], ["Image (Base Model)","Image (Tuned Model)", "Display Detected Video"])
 
 
 if __name__ == "__main__":