Update app.py

app.py

@@ -3,6 +3,16 @@ import subprocess
 import importlib.util
 import gradio as gr
 import logging
+from moviepy.editor import VideoFileClip
+
+# Function to truncate video to 15 seconds
+def truncate_video(video_file):
+    """Truncates video to 15 seconds and saves it as a temporary file."""
+    clip = VideoFileClip(video_file)
+    truncated_clip = clip.subclip(0, min(15, clip.duration))
+    truncated_video_file = "temp_truncated_video.mp4"
+    truncated_clip.write_videofile(truncated_video_file, codec="libx264", audio_codec="aac")
+    return truncated_video_file
 
 # Clone the GitHub repository containing the backend
 def clone_repo():
@@ -57,9 +67,14 @@ backend = import_backend_script("app.py")  # Import app.py from the cloned repos
 # Initialize the analyzer instance from the imported module
 analyzer = backend.DeepfakeAnalyzer()  # Use the imported module's class or function
 
+# Define the Gradio function to analyze the video
 # Define the Gradio function to analyze the video
 def analyze_video(video_file):
-    results = analyzer.analyze_media(video_file)
+    # Truncate the video to 15 seconds
+    truncated_video = truncate_video(video_file)
+    
+    # Pass the truncated video to the analyzer
+    results = analyzer.analyze_media(truncated_video)
     combined_probability = results['combined_assessment']
     audio_analysis = results["audio_analysis"]
     video_probability = results['video_analysis']['probability']
@@ -74,11 +89,6 @@ def analyze_video(video_file):
             "Frames Analyzed": frame_count,
             "Frame Analysis Summary": [
                 {
-                    "Frame Number": frame_result["frame_number"],
-                    "Noise Level": frame_result["noise"],
-                    "Edge Density": frame_result["edge_density"],
-                    "Color Consistency": frame_result["color_consistency"],
-                    "Temporal Difference": frame_result["temporal_difference"],
                     "Probability": frame_result["probability"]
                 }
                 for frame_result in results['video_analysis']['frame_results']
@@ -87,12 +97,13 @@ def analyze_video(video_file):
     }
     return output
 
+
 # Define the Gradio interface
 interface = gr.Interface(
     fn=analyze_video,
     inputs=gr.Video(label="Upload Video"),
     outputs="json",
-    title="Deepfake Analyzer",
+    title="AllMark - Deepfake Analyzer",
     description="Upload a video to analyze for deepfake content."
 )