Update app.py

app.py

@@ -103,7 +103,7 @@ def process_frame(frame):
         cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
         cv2.putText(frame, emotion, (x, y+h), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
 
-    return frame
+    return frame, faces  # Return the frame and the detected faces
 
 # Attendance recording
 def record_attendance(name, roll_no, emotion):
@@ -116,60 +116,88 @@ def record_attendance(name, roll_no, emotion):
     conn.commit()
     conn.close()
 
-# User Interface
-st.title("Student Registration and Attendance")
-
-# Choose input method for the image (webcam or file upload)
-capture_mode = st.radio("Choose an option to upload your image", ["Use Webcam", "Upload File"])
-
-if capture_mode == "Use Webcam":
-    picture = st.camera_input("Take a picture")  # Capture image using webcam
-elif capture_mode == "Upload File":
-    picture = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
-
-# Input fields for student details
-name = st.text_input("Enter your name")
-roll_no = st.text_input("Enter your roll number")
-
-# Handle image upload or webcam capture
-if st.button("Register"):
-    if not name or not roll_no:
-        st.error("Please fill in both name and roll number.")
-    elif not picture:
-        st.error("Please upload or capture an image.")
-    else:
-        try:
-            # Open the image based on capture mode
-            if capture_mode == "Use Webcam" and picture:
-                image = Image.open(picture)
-            elif capture_mode == "Upload File" and picture:
-                image = Image.open(picture)
-
-            # Save the image locally and upload it to Hugging Face
-            image_path = save_image_to_hugging_face(image, name, roll_no)
-
-            # Save user data to the database
-            save_to_database(name, roll_no, image_path)
-
-            # Detect faces and emotions
-            cap = cv2.VideoCapture(0)
-            while True:
-                ret, frame = cap.read()
-                if not ret:
-                    break
-
-                frame = process_frame(frame)
-                st.image(frame, channels="BGR", use_column_width=True)
+# User Interface - Streamlit tabs
+st.title("Student Registration and Attendance System")
+
+tabs = st.selectbox("Choose Functionality", ["Register Student", "Record Attendance", "View Attendance"])
+
+if tabs == "Register Student":
+    st.subheader("Student Registration")
+
+    # Choose input method for the image (webcam or file upload)
+    capture_mode = st.radio("Choose an option to upload your image", ["Use Webcam", "Upload File"])
+
+    if capture_mode == "Use Webcam":
+        picture = st.camera_input("Take a picture")  # Capture image using webcam
+    elif capture_mode == "Upload File":
+        picture = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+    # Input fields for student details
+    name = st.text_input("Enter your name")
+    roll_no = st.text_input("Enter your roll number")
+
+    # Handle image upload or webcam capture
+    if st.button("Register"):
+        if not name or not roll_no:
+            st.error("Please fill in both name and roll number.")
+        elif not picture:
+            st.error("Please upload or capture an image.")
+        else:
+            try:
+                # Open the image based on capture mode
+                if capture_mode == "Use Webcam" and picture:
+                    image = Image.open(picture)
+                elif capture_mode == "Upload File" and picture:
+                    image = Image.open(picture)
+
+                # Save the image locally and upload it to Hugging Face
+                image_path = save_image_to_hugging_face(image, name, roll_no)
+
+                # Save user data to the database
+                save_to_database(name, roll_no, image_path)
+
+                st.success("Registration Successful!")
+
+            except Exception as e:
+                st.error(f"An error occurred: {e}")
+
+elif tabs == "Record Attendance":
+    st.subheader("Record Attendance")
+
+    # Initialize the webcam for face detection and emotion recognition
+    cap = cv2.VideoCapture(0)
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        # Process the frame to detect faces and emotions
+        frame, faces = process_frame(frame)
+
+        # Show the image with detected faces and emotions
+        st.image(frame, channels="BGR", use_column_width=True)
+
+        # When a face is detected, assume it's the person for attendance
+        if len(faces) > 0:
+            # Assume the first face detected corresponds to the student
+            x, y, w, h = faces[0]
+            # Extract the emotion from the frame (for simplicity, use the first detected face)
+            name = "John Doe"  # Replace with the actual name after face recognition
+            roll_no = "12345"  # Replace with the actual roll number
+            emotion = emotion_labels[np.argmax(model.predict(cv2.resize(frame[y:y+h, x:x+w], (48, 48)).reshape(1, 48, 48, 3)))]  # Get emotion of detected face
+
+            # Record attendance based on the detected information
+            if st.button("Record Attendance"):
                 record_attendance(name, roll_no, emotion)
+                st.success(f"Attendance recorded for {name} ({roll_no}) with emotion: {emotion}")
                 break  # Stop after capturing one frame
 
-            cap.release()
+    cap.release()
 
-        except Exception as e:
-            st.error(f"An error occurred: {e}")
+elif tabs == "View Attendance":
+    st.subheader("View Attendance Records")
 
-# Display registered students
-if st.checkbox("Show registered students"):
     conn = sqlite3.connect(DATABASE)
     cursor = conn.cursor()
     cursor.execute("SELECT name, roll_no, image_path, timestamp FROM students")