Update app.py

app.py

@@ -8,6 +8,7 @@ import numpy as np
 import cv2
 import dlib
 from io import BytesIO
+import requests
 
 # Get the current working directory
 current_directory = os.path.dirname(os.path.abspath(__file__))
@@ -165,25 +166,64 @@ def recognize_face(image_path):
                 if face_recognition.compare_faces([known_encoding], unknown_encoding)[0]:
                     info = data["info"]
                     email = info.get("email", "Email not provided")
-                    face_matches.append((name, info["instagram_handle"], email))
+                    insta_handle = info["instagram_handle"]
+                    insta_info = fetch_instagram_info(insta_handle)
+                    face_matches.append((name, insta_handle, email, insta_info))
 
             if face_matches:
                 matches.extend(face_matches)
             else:
-                matches.append(("Unknown", "Unknown", "Unknown"))
+                matches.append(("Unknown", "Unknown", "Unknown", {}))
 
         if matches:
             results = []
-            for name, insta_handle, email in matches:
+            for name, insta_handle, email, insta_info in matches:
                 insta_link = f"https://www.instagram.com/{insta_handle}/"
                 insta_link_html = f'<a href="{insta_link}" target="_blank"><font color="red">{insta_handle}</font></a>'
-                results.append(f"- It's a picture of {name}! Insta handle: {insta_link_html}, Email: {email}")
+                full_name = insta_info.get('full_name', 'N/A')
+                biography = insta_info.get('biography', 'N/A')
+                follower_count = insta_info.get('follower_count', 'N/A')
+                following_count = insta_info.get('following_count', 'N/A')
+                results.append(
+                    f"- It's a picture of {name}! Insta handle: {insta_link_html}, Email: {email}, "
+                    f"Full Name: {full_name}, Biography: {biography}, Followers: {follower_count}, Following: {following_count}"
+                )
             log_action(st.session_state.auth_state["user"].email, "Recognized face")
             return "\n".join(results)
         else:
             return "Face not found in the database."
     except Exception as e:
         return f"Failed to recognize face: {str(e)}"
+
+def fetch_instagram_info(insta_handle):
+    url = "https://instagram-scraper-api2.p.rapidapi.com/v1/info"
+    querystring = {"username_or_id_or_url": insta_handle}
+
+    headers = {
+        "x-rapidapi-key": "bc2b15f577msh345ac5a5b422c7ep106f73jsn580b1c25e0d9",
+        "x-rapidapi-host": "instagram-scraper-api2.p.rapidapi.com"
+    }
+
+    response = requests.get(url, headers=headers, params=querystring)
+
+    if response.status_code == 200:
+        data = response.json().get('data', {})
+        return {
+            'full_name': data.get('full_name', 'N/A'),
+            'biography': data.get('biography', 'N/A'),
+            'profile_pic_url_hd': data.get('profile_pic_url_hd', 'N/A'),
+            'follower_count': data.get('follower_count', 'N/A'),
+            'following_count': data.get('following_count', 'N/A')
+        }
+    else:
+        return {
+            'full_name': 'N/A',
+            'biography': 'N/A',
+            'profile_pic_url_hd': 'N/A',
+            'follower_count': 'N/A',
+            'following_count': 'N/A'
+        }
+
         
 # Update recognize_face_optimal function to handle multiple face encodings
 def recognize_face_optimal(image_path):