Update app.py

app.py

@@ -1,4 +1,4 @@
-from flask import Flask, request, jsonify, Response
+from flask import Flask, request, jsonify
 import os
 from werkzeug.utils import secure_filename
 import cv2
@@ -6,10 +6,11 @@ import torch
 import torch.nn.functional as F
 from facenet_pytorch import MTCNN, InceptionResnetV1
 import numpy as np
-import json
+from flask_socketio import SocketIO, emit
 import time
 
 app = Flask(__name__)
+socketio = SocketIO(app, cors_allowed_origins="*")
 
 # Configuration
 UPLOAD_FOLDER = 'uploads'
@@ -52,7 +53,7 @@ def process_frame(frame):
 
     return prediction, output.item()
 
-def event_stream(video_path, sample_rate=30):
+def event_sdef analyze_video(video_path, sample_rate=30):
     cap = cv2.VideoCapture(video_path)
     frame_count = 0
     fake_count = 0
@@ -73,9 +74,9 @@ def event_stream(video_path, sample_rate=30):
                 if prediction == "fake":
                     fake_count += 1
 
-            # Send progress update
+            # Emit progress update
             progress = (frame_count / total_frames) * 100
-            yield f"data: {json.dumps({'progress': progress})}\n\n"
+            socketio.emit('analysis_progress', {'progress': progress})
 
         frame_count += 1
 
@@ -83,10 +84,9 @@ def event_stream(video_path, sample_rate=30):
 
     if total_processed > 0:
         fake_percentage = (fake_count / total_processed) * 100
+        return fake_percentage
     else:
-        fake_percentage = 0
-
-    yield f"data: {json.dumps({'fake_percentage': round(fake_percentage, 2), 'is_likely_deepfake': fake_percentage >= 60})}\n\n"
+        return 0
 
 @app.route('/analyze', methods=['POST'])
 def analyze_video_api():
@@ -101,14 +101,36 @@ def analyze_video_api():
     if file and allowed_file(file.filename):
         filename = secure_filename(file.filename)
         filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
-        file.save(filepath)
+        
+        # Save file and emit upload progress
+        chunk_size = 4096
+        file_size = int(request.headers.get('Content-Length', 0))
+        bytes_read = 0
+        with open(filepath, 'wb') as f:
+            while True:
+                chunk = file.read(chunk_size)
+                if not chunk:
+                    break
+                f.write(chunk)
+                bytes_read += len(chunk)
+                progress = (bytes_read / file_size) * 100
+                socketio.emit('upload_progress', {'progress': progress})
 
         try:
-            return Response(event_stream(filepath), content_type='text/event-stream')
-        finally:
+            fake_percentage = analyze_video(filepath)
             os.remove(filepath)  # Remove the file after analysis
+
+            result = {
+                'fake_percentage': round(fake_percentage, 2),
+                'is_likely_deepfake': fake_percentage >= 60
+            }
+
+            return jsonify(result), 200
+        except Exception as e:
+            os.remove(filepath)  # Remove the file if an error occurs
+            return jsonify({'error': str(e)}), 500
     else:
         return jsonify({'error': 'Invalid file type'}), 400
 
 if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=7860)
+    socketio.run(app, host='0.0.0.0', port=7860)