Update app.py

app.py

@@ -5,35 +5,39 @@ import streamlit as st
 from datetime import datetime
 from PIL import Image
 
-# Directories and Hugging Face Token
-KNOWN_FACES_DIR = "known_faces"
+# Constants
+KNOWN_FACES_DIR = "known_faces"  # Directory to save user images
+DATABASE = "students.db"  # SQLite database file to store student information
+
+# Ensure the directory exists
 os.makedirs(KNOWN_FACES_DIR, exist_ok=True)
 
-# Retrieve the Hugging Face token from the environment
-hf_token = os.getenv("upload")  # Ensure the key matches the secret name
+# Retrieve the Hugging Face token from environment variable
+hf_token = os.getenv("upload")  # The key must match the secret name set in Hugging Face
 if not hf_token:
     raise ValueError("Hugging Face token not found. Ensure it's set as a secret in the Hugging Face Space.")
 
-# Initialize the Hugging Face API
+# Initialize Hugging Face API
 api = HfApi()
 
-# Repository Details
-REPO_NAME = "face_and_emotion_detection"  # Replace with your desired repo name
-REPO_ID = "LovnishVerma/" + REPO_NAME  # Update "LovnishVerma" with your Hugging Face username
-REPO_TYPE = "space"  # Set to 'space' for Streamlit projects
+# Repository Details on Hugging Face
+REPO_NAME = "face_and_emotion_detection"  # Replace with your Hugging Face repository name
+REPO_ID = "LovnishVerma/" + REPO_NAME  # Replace "LovnishVerma" with your Hugging Face username
+REPO_TYPE = "space"  # 'space' type for Streamlit-based projects
 
-# Ensure repository exists
+# Ensure the repository exists or create it
 try:
-    # Specify space_sdk as 'streamlit' for a Streamlit-based Hugging Face Space
     api.create_repo(repo_id=REPO_ID, repo_type=REPO_TYPE, space_sdk="streamlit", token=hf_token, exist_ok=True)
     st.success(f"Repository '{REPO_NAME}' is ready on Hugging Face!")
 except Exception as e:
     st.error(f"Error creating repository: {e}")
 
 # Database setup
-DATABASE = "students.db"
-
 def initialize_database():
+    """
+    Initializes the SQLite database by creating a table to store student data
+    such as name, roll number, image path, and registration timestamp.
+    """
     conn = sqlite3.connect(DATABASE)
     cursor = conn.cursor()
     cursor.execute("""
@@ -49,6 +53,15 @@ def initialize_database():
     conn.close()
 
 def save_to_database(name, roll_no, image_path):
+    """
+    Saves the student's information (name, roll number, image path) to the SQLite database.
+    Ensures roll number is unique.
+
+    Args:
+        name (str): The name of the student.
+        roll_no (str): The roll number of the student.
+        image_path (str): Path to the stored image of the student.
+    """
     conn = sqlite3.connect(DATABASE)
     cursor = conn.cursor()
     try:
@@ -63,19 +76,34 @@ def save_to_database(name, roll_no, image_path):
     finally:
         conn.close()
 
-def save_image_to_hugging_face(image, roll_no):
-    filename = f"{roll_no}_{datetime.now().strftime('%Y%m%d%H%M%S')}.jpg"
+def save_image_to_hugging_face(image, name, roll_no):
+    """
+    Saves the captured image locally in the 'known_faces' directory and uploads it to Hugging Face.
+    The image is renamed using the format 'UserName_RollNo.jpg'.
+
+    Args:
+        image (PIL Image): The image object captured by the user.
+        name (str): The name of the student.
+        roll_no (str): The roll number of the student.
+
+    Returns:
+        str: The local path where the image is saved.
+    """
+    # Rename the image using the format 'UserName_RollNo.jpg'
+    filename = f"{name}_{roll_no}.jpg"
     local_path = os.path.join(KNOWN_FACES_DIR, filename)
+    
+    # Save the image locally to the known_faces directory
     image.save(local_path)
 
-    # Upload to Hugging Face
+    # Try uploading the image to Hugging Face
     try:
         api.upload_file(
             path_or_fileobj=local_path,
             path_in_repo=filename,
             repo_id=REPO_ID,
             repo_type=REPO_TYPE,
-            token=hf_token  # Pass the token directly
+            token=hf_token  # Pass the Hugging Face token directly
         )
         st.success(f"Image uploaded to Hugging Face: {filename}")
     except Exception as e:
@@ -83,30 +111,31 @@ def save_image_to_hugging_face(image, roll_no):
 
     return local_path
 
-# Initialize database
+# Initialize the database when the app starts
 initialize_database()
 
-# Streamlit app
+# Streamlit user interface (UI)
 st.title("Student Registration with Hugging Face Image Upload")
 
-# Input details
+# Input fields for student details
 name = st.text_input("Enter your name")
 roll_no = st.text_input("Enter your roll number")
 
-# Choose image input method
+# 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"])
 
+# Handle webcam capture or file upload
 if capture_mode == "Use Webcam":
     try:
-        picture = st.camera_input("Take a picture")
+        picture = st.camera_input("Take a picture")  # Capture image using webcam
     except Exception as e:
         st.error(f"Error accessing webcam: {e}")
         picture = None
 
 elif capture_mode == "Upload File":
-    picture = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+    picture = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])  # Upload image from file system
 
-# Save and process data
+# Save data and process image on button click
 if st.button("Register"):
     if not name or not roll_no:
         st.error("Please fill in both name and roll number.")
@@ -114,18 +143,19 @@ if st.button("Register"):
         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 locally and upload to Hugging Face
-            image_path = save_image_to_hugging_face(image, roll_no)
+            # Save the image locally and upload it to Hugging Face
+            image_path = save_image_to_hugging_face(image, name, roll_no)
             save_to_database(name, roll_no, image_path)
         except Exception as e:
             st.error(f"An error occurred: {e}")
 
-# Display stored data
+# Display registered student data
 if st.checkbox("Show registered students"):
     conn = sqlite3.connect(DATABASE)
     cursor = conn.cursor()
@@ -138,4 +168,3 @@ if st.checkbox("Show registered students"):
         name, roll_no, image_path, timestamp = row
         st.write(f"**Name:** {name}, **Roll No:** {roll_no}, **Timestamp:** {timestamp}")
         st.image(image_path, caption=f"{name} ({roll_no})", use_column_width=True)
-