Update app.py

app.py

@@ -1,28 +1,28 @@
-# app.py
-import streamlit as st
-from deepface import DeepFace
+import os
 import requests
 from PIL import Image
+import streamlit as st
+from deepface import DeepFace
 from gtts import gTTS
-import os
 import cv2
 import numpy as np
 
 # Constants
-KNOWN_FOLDER = "known_faces"
+BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+KNOWN_FOLDER = os.path.join(BASE_DIR, "known_faces")
 ESP32_SERVER_URL = "https://esp32-upload-server.onrender.com"
-MODEL_NAME = "ArcFace"
-DETECTOR_BACKEND = "retinaface"
+MODEL_NAME = "ArcFace"  # You can change the model to "VGG-Face" or "Facenet"
+DETECTOR_BACKEND = "retinaface"  # Detector can be "opencv", "mtcnn", "dlib", etc.
 
-# Ensure known folder exists
+# Ensure the known_faces folder exists
 os.makedirs(KNOWN_FOLDER, exist_ok=True)
 
-# Streamlit setup
+# Streamlit Setup
 st.set_page_config(page_title="Second Eye - Enhanced Recognition", layout="centered")
 st.sidebar.title("Navigation")
 page = st.sidebar.radio("Go to", ["Face Recognition", "Upload Known Face"])
 
-# Get latest image from ESP32
+# Image fetching from ESP32
 @st.cache_data(show_spinner=False)
 def get_latest_image():
     try:
@@ -34,7 +34,7 @@ def get_latest_image():
     except:
         return None
 
-# Preprocess the image to enhance quality
+# Enhance image quality
 def preprocess_image(image_path):
     img = cv2.imread(image_path)
     if img is None:
@@ -50,7 +50,7 @@ def preprocess_image(image_path):
     cv2.imwrite(output_path, final_img)
     return output_path
 
-# Check if a face is detected
+# Check if a face is detected in the image
 def is_face_detected(image_path):
     try:
         faces = DeepFace.extract_faces(
@@ -62,7 +62,7 @@ def is_face_detected(image_path):
     except:
         return False
 
-# Compare unknown image with known faces
+# Compare with known faces
 def compare_with_known_faces(unknown_img_path):
     for filename in os.listdir(KNOWN_FOLDER):
         known_img_path = os.path.join(KNOWN_FOLDER, filename)
@@ -86,25 +86,36 @@ if page == "Upload Known Face":
     uploaded = st.file_uploader("Choose an image of a known person", type=["jpg", "jpeg", "png"])
     name = st.text_input("Enter name of the person")
 
-    if uploaded is not None and name.strip() != "":
+    if uploaded and name:
         try:
-            image_bytes = uploaded.read()
-            filename = os.path.join(KNOWN_FOLDER, f"{name.strip().lower().replace(' ', '_')}.jpg")
-            with open(filename, "wb") as f:
-                f.write(image_bytes)
-            st.success(f"✅ Face saved as {name}")
-            st.image(filename, caption="Saved Image", use_column_width=True)
+            # Ensure the image is RGB
+            image = Image.open(uploaded).convert("RGB")
+
+            # Sanitize filename
+            safe_name = name.strip().lower().replace(" ", "_")
+            file_path = os.path.join(KNOWN_FOLDER, f"{safe_name}.jpg")
+
+            # Save image
+            image.save(file_path, format="JPEG")
+
+            # Confirmation message
+            st.success(f"✅ Face saved as {safe_name}")
+            st.image(file_path, caption="Saved Image", use_column_width=True)
+
         except Exception as e:
-            st.error(f"❌ Error saving file: {e}")
+            st.error(f"❌ Error saving image: {e}")
 
-# Face recognition page
+# Face Recognition Page
 elif page == "Face Recognition":
     st.title("Second Eye - Face Recognition")
+    
     if st.button("Capture and Recognize Face"):
         image_url = get_latest_image()
+        
         if image_url:
             st.image(image_url, caption="Captured Image", use_container_width=True)
             response = requests.get(image_url)
+            
             with open("latest.jpg", "wb") as f:
                 f.write(response.content)