Update app.py

app.py

@@ -5,19 +5,33 @@ import mediapipe as mp
 import matplotlib.pyplot as plt
 from PIL import Image
 import numpy as np
+import tempfile
 
 # Initialize MediaPipe Pose for body bounding box detection
 mp_pose = mp.solutions.pose
 
 def analyze_images(img1, img2):
+    # Option 1: Convert PIL images to NumPy arrays
+    img1_array = np.array(img1)
+    img2_array = np.array(img2)
+
+    # Option 2: Save images temporarily as JPEG files
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file1:
+        img1.save(temp_file1, format='JPEG')
+        img1_path = temp_file1.name
+
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file2:
+        img2.save(temp_file2, format='JPEG')
+        img2_path = temp_file2.name
+
     # Face comparison with DeepFace
-    face_result = DeepFace.verify(img1, img2, model_name='VGG-Face')
+    face_result = DeepFace.verify(img1_path, img2_path, model_name='VGG-Face')
     is_same_person = face_result['verified']
     similarity_score = face_result['distance']
 
     # Convert images to OpenCV format
-    img1_cv = cv2.cvtColor(np.array(img1), cv2.COLOR_RGB2BGR)
-    img2_cv = cv2.cvtColor(np.array(img2), cv2.COLOR_RGB2BGR)
+    img1_cv = cv2.cvtColor(img1_array, cv2.COLOR_RGB2BGR)
+    img2_cv = cv2.cvtColor(img2_array, cv2.COLOR_RGB2BGR)
 
     # Body analysis with MediaPipe
     def get_body_info(image):