Update app.py

app.py

@@ -1,53 +1,51 @@
 import streamlit as st
-import requests
-import face_recognition
 import numpy as np
 from PIL import Image
+import insightface
+import cv2
 import os
-import io
+import tempfile
 
 st.set_page_config(page_title="Face Finder on Internet", layout="centered")
 st.title("🕵️‍♂️ Check if Your Face Exists on the Internet")
 st.markdown("Upload your photo and we'll search for public matches using reverse image search and AI-based face comparison.")
 
-# Function to convert uploaded image to face encoding
-def get_face_encoding(image_file):
-    try:
-        image = face_recognition.load_image_file(image_file)
-        encodings = face_recognition.face_encodings(image)
-        if encodings:
-            return encodings[0]
-        else:
-            return None
-    except Exception as e:
-        st.error(f"Error processing image: {e}")
-        return None
+# Load InsightFace model
+@st.cache_resource
+def load_model():
+    model = insightface.app.FaceAnalysis(name='buffalo_l')
+    model.prepare(ctx_id=0)
+    return model
+
+model = load_model()
 
-# Function to reverse search using Yandex (via redirect to their site)
-def generate_yandex_link(image_bytes):
-    temp_file_path = "temp_image.jpg"
-    with open(temp_file_path, "wb") as f:
-        f.write(image_bytes)
-    return "https://yandex.com/images/search?rpt=imageview&url="
+# Function to extract face embeddings
+def get_face_embedding(image):
+    image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    faces = model.get(image)
+    if faces:
+        return faces[0].embedding
+    else:
+        return None
 
 # UI: Upload image
 uploaded_file = st.file_uploader("Upload your face image (jpg/png)", type=["jpg", "jpeg", "png"])
 
 if uploaded_file:
     # Show uploaded image
-    image = Image.open(uploaded_file)
+    image = Image.open(uploaded_file).convert("RGB")
     st.image(image, caption="Uploaded Image", use_column_width=True)
 
-    # Extract face encoding
-    encoding = get_face_encoding(uploaded_file)
+    # Extract face embedding
+    embedding = get_face_embedding(image)
 
-    if encoding is not None:
-        st.success("Face encoding extracted successfully ✅")
+    if embedding is not None:
+        st.success("Face features extracted successfully ✅")
 
         # Convert image to bytes for reverse search
-        img_byte_arr = io.BytesIO()
-        image.save(img_byte_arr, format='JPEG')
-        img_bytes = img_byte_arr.getvalue()
+        img_byte_arr = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
+        image.save(img_byte_arr.name)
+        img_bytes = open(img_byte_arr.name, 'rb').read()
 
         # Provide links for manual reverse search
         st.subheader("🔍 Search Your Face on the Web")
@@ -55,7 +53,7 @@ if uploaded_file:
 
         with col1:
             st.markdown("[Search on Google](https://images.google.com)")
-            st.caption("Upload the same image there manually")
+            st.caption("Upload the same image manually")
 
         with col2:
             st.markdown("[Search on Yandex](https://yandex.com/images)")
@@ -70,4 +68,4 @@ if uploaded_file:
         st.warning("No face detected in the uploaded image. Try another photo.")
 
 st.markdown("---")
-st.markdown("Created with ❤️ using open-source face recognition models and public search tools.")
+st.markdown("Created with ❤️ using open-source InsightFace and public search tools.")