Update app.py

app.py

@@ -1,67 +1,29 @@
 import gradio as gr
 import pipeline
 
-# Custom CSS for larger interface
 custom_css = """
-.gradio-container {
-    max-width: 1400px !important;
-}
-#component-0, #component-1, #component-2 {
-    min-height: 500px !important;
-}
-.output-class {
-    min-height: 300px !important;
-    font-size: 24px !important;
-    padding: 30px !important;
-}
-.input-image, .input-video, .input-audio {
-    min-height: 500px !important;
-}
+.gradio-container { max-width: 1400px !important; }
 """
 
-title = "EfficientNetV2 Deepfakes Detector"
-description = "Multimodal Deepfake Detection using EfficientNetV2 (Video/Image) and RawNet (Audio)."
-
-# Image Interface with larger components
 image_interface = gr.Interface(
     fn=pipeline.deepfakes_image_predict,
     inputs=gr.Image(label="Upload Image", height=500),
-    outputs=gr.Textbox(label="Detection Result", lines=8, scale=2),
-    examples=["images/images_lady.jpg", "images/images_fake_image.jpg"],
-    cache_examples=False,
-    title="Image Deepfake Detection",
-    description="Upload an image to detect if it's real or fake"
+    outputs=gr.Textbox(label="Detection Result", lines=8),
+    title="Image Deepfake Detection"
 )
 
-# Video Interface with larger components  
 video_interface = gr.Interface(
     fn=pipeline.deepfakes_video_predict,
     inputs=gr.Video(label="Upload Video", height=500),
-    outputs=gr.Textbox(label="Detection Result", lines=8, scale=2),
-    examples=["videos/celeb_synthesis.mp4", "videos/real-1.mp4"],
-    cache_examples=False,
-    title="Video Deepfake Detection",
-    description="Upload a video to detect if it's real or fake (frame-by-frame analysis)"
-)
-
-# Audio Interface (New)
-audio_interface = gr.Interface(
-    fn=pipeline.deepfakes_audio_predict,
-    inputs=gr.Audio(sources=["upload", "microphone"], label="Upload Audio", type="numpy"),
-    outputs=gr.Textbox(label="Detection Result", lines=8, scale=2),
-    # examples=["audio/real_sample.wav", "audio/fake_sample.wav"], # Uncomment if you have example audio files
-    cache_examples=False,
-    title="Audio Deepfake Detection",
-    description="Upload an audio file or record microphone to detect if it's real or fake (Deepfake)"
+    outputs=gr.Textbox(label="Detection Result", lines=8),
+    title="Video Deepfake Detection"
 )
 
 app = gr.TabbedInterface(
-    interface_list=[image_interface, video_interface, audio_interface], 
-    tab_names=['Image inference', 'Video inference', 'Audio inference'],
-    css=custom_css,
-    title=title,
-    theme=gr.themes.Soft()
+    interface_list=[image_interface, video_interface],
+    tab_names=['Image inference', 'Video inference'],
+    css=custom_css
 )
 
-if __name__ == '__main__':
-    app.launch()
+if __name__ == "__main__":
+    app.launch()