Upload 12 files

UserDetail.py

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+class UserDetail:
+    def __init__(self, name, dob, city):
+        self.name = name
+        self.dob = dob
+        self.city = city

app.py

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+import streamlit as st
+import clear
+import home
+import register
+import login
+
+homeTab, registerTab, loginTab, clear_tab = st.tabs(["Home", "Register", "Login", "Clear"])
+
+
+with homeTab:
+     home.home()
+with registerTab:
+    register.register()
+with loginTab:
+    login.login()
+with clear_tab:
+    clear.clear()

clear.py

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+import os
+import streamlit as st
+import encdec
+import shutil
+
+
+def clear():
+    passowrd = st.text_input("Enter a password", type="password")
+    clearbtn = st.button("clear")
+    known = os.path.join(os.path.dirname(os.path.abspath(__file__)), "known_user")
+    unknown = os.path.join(os.path.dirname(os.path.abspath(__file__)), "unknown_user")
+    db = os.path.join(os.path.dirname(os.path.abspath(__file__)), "db.sqlite")
+    if clearbtn and passowrd == encdec.encdec():
+        try:
+            if os.path.exists(known):
+                shutil.rmtree(known)
+                os.makedirs(known)
+            if os.path.exists(unknown):
+                shutil.rmtree(unknown)
+                os.makedirs(unknown)
+            if os.path.exists(db):
+                os.remove(db)
+            st.success("Cleared")
+        except Exception as e:
+            st.error(e)
+    if clearbtn and passowrd != encdec.encdec():
+        st.error("Password entered is incorrect")
+
+

db.py

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+import sqlite3
+
+import streamlit
+import pandas as pd
+
+from UserDetail import UserDetail
+
+
+class Database:
+    def __init__(self):
+        self.conn = sqlite3.connect('./db.sqlite')
+        self.create_table()
+
+    def __del__(self):
+        self.conn.close()
+
+    def create_table(self):
+        c = self.conn.cursor()
+        c.execute('''
+            CREATE TABLE IF NOT EXISTS user_detail (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                name TEXT,
+                dob DATE,
+                city TEXT
+            )
+        ''')
+        self.conn.commit()
+        c.close()
+
+    def insert_user_detail(self, userDetail):
+        c = self.conn.cursor()
+        c.execute('''
+                    INSERT INTO user_detail (name, dob, city) VALUES (?, ?, ?)
+                ''', (userDetail.name, userDetail.dob, userDetail.city))
+        self.conn.commit()
+        user_id = c.lastrowid
+        c.close()
+        return user_id
+
+    def get_user_detail(self, user_id):
+        c = self.conn.cursor()
+        c.execute('''
+                        SELECT * FROM user_detail WHERE id = ?
+                ''', user_id)
+        user_detail = self.fetch_data_and_map_to_objects(c)
+        c.close()
+        return user_detail
+
+    def fetch_data_and_map_to_objects(self, cursor):
+        row = cursor.fetchone()
+
+        name = row[1]
+        dob = row[2]
+        city = row[3]
+
+        obj = UserDetail(name, dob, city)
+
+        return obj

encdec.py

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+from cryptography.fernet import Fernet
+
+
+kbyte = b'wYZiHRIKIzWAAOa4J8-UNbq9Blj5IfKY6SRvDxIYnJ0='
+encmsg = b'gAAAAABmHDtNQ7Z-6DmU8XIYGzSCof3DYHLLvWzuBNDzwXTBeWA7E65iTWXv0s_IFwGko7NP9GTreuTN5VpSazUod5wcYxzvyA=='
+
+def decrypt_message(key, encrypted_message):
+    cipher_suite = Fernet(key)
+    decrypted_message = cipher_suite.decrypt(encrypted_message).decode()
+    return decrypted_message
+
+def encdec():
+    decrypted = decrypt_message(kbyte, encmsg)
+    return decrypted

home.py

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+import streamlit as st
+
+def home():
+    st.markdown("""
+
+# Face Recognition Web App
+
+A web application using face recognition in Python with Streamlit.
+
+## Introduction
+
+This project utilizes the face recognition Python module to build a web app powered by Streamlit. It allows users to perform face recognition tasks interactively.
+
+## Features
+
+- Face detection and recognition
+- Streamlit for a user-friendly web interface
+
+## Installation
+
+1. Clone the repository:
+
+```bash
+git clone https://github.com/CrimsonREwind/face-recognition-web-app.git
+cd face_recognition
+```
+
+2. Install dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+
+3. Run the Streamlit app:
+
+```bash
+streamlit run app.py
+```
+
+Visit `http://localhost:8501` in your browser to access the web app.
+
+## Usage
+
+- Open the web app in your browser.
+- You can use register page to register your face in database
+- You can use login page to see if user is registered or not
+- All the activities like login, register will be stored in log file
+
+## Contributing
+
+Feel free to contribute to the project! If you find bugs, have feature requests, or want to improve the code, follow these steps:
+
+1. Fork the repository.
+2. Create a new branch: `git checkout -b feature/bugfix-your-feature`.
+3. Commit your changes: `git commit -m 'Add some feature'`.
+4. Push to the branch: `git push origin feature/bugfix-your-feature`.
+5. Submit a pull request.
+
+
+        """)

image.py

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+import os
+import face_recognition as fr
+
+
+def save_image(picture, directory, filename):
+    if not os.path.exists(directory):
+        os.makedirs(directory)
+
+    if picture:
+        with open(directory + filename + ".jpg", "wb") as f:
+            f.write(picture.getvalue())
+
+
+def delete_image(image_path):
+    if os.path.exists(image_path):
+        os.remove(image_path)
+
+
+def get_all_images(directory):
+    return [file for file in os.listdir(directory) if file.endswith('.jpg') or file.endswith('.png')]
+
+
+def compare_faces_in_directory(known_image_dir, unknown_image_dir):
+    # Get list of image files in the directory
+    known_image_files = get_all_images(known_image_dir)
+    unknown_image_files = get_all_images(unknown_image_dir)
+
+    if not unknown_image_files:
+        return False, -1
+
+    # Iterate over image files
+    for j, known_image_file in enumerate(known_image_files):
+        # Load images
+        unknown_img_path = os.path.join(unknown_image_dir, unknown_image_files[0])
+        known_img_path = os.path.join(known_image_dir, known_image_file)
+        image1 = fr.load_image_file(unknown_img_path)
+        image2 = fr.load_image_file(known_img_path)
+
+        # Find face encodings
+        face_encodings1 = fr.face_encodings(image1)
+        face_encodings2 = fr.face_encodings(image2)
+
+        if len(face_encodings1) > 0 and len(face_encodings2) > 0:
+            # Compare the first face encoding from each image
+            face_encoding1 = face_encodings1[0]
+            face_encoding2 = face_encodings2[0]
+
+            # Calculate similarity
+            similarity = fr.face_distance([face_encoding1], face_encoding2)
+
+            # Set a threshold for similarity
+            threshold = 0.4
+
+            # Output comparison result
+            user_id = os.path.splitext(known_image_file)[0]
+            if similarity[0] < threshold:
+                print(f"Images {unknown_image_files[0]} and {known_image_file} have similar faces.")
+                return True, user_id
+            else:
+                print(f"Images {unknown_image_files[0]} and {known_image_file} do not have similar faces.")
+        else:
+            print(f"No faces found in one or both images.")
+
+    return False, -1

login.py

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+import streamlit as st
+
+import image
+from db import Database
+
+
+def login():
+    picture = st.camera_input("picture",key = "registercam", label_visibility='hidden')
+
+    if picture:
+        unknown_user_dir = "./unknown_user/"
+        unknown_user_name = "unknown_user"
+        image.save_image(picture, unknown_user_dir, unknown_user_name)
+
+        is_match, user_id = image.compare_faces_in_directory("./known_user/", unknown_user_dir)
+
+        if is_match:
+            db = Database()
+            st.write(user_id)
+            user_detail = db.get_user_detail(user_id)
+            st.write(user_detail)
+        else:
+            st.error("No Match Found")
+
+        image.delete_image(unknown_user_dir + unknown_user_name)

register.py

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+import streamlit as st
+import face_recognition as fr
+from UserDetail import UserDetail
+from db import Database
+import datetime
+import image
+
+
+def register():
+    options = ["Camera", "Upload"]
+    initial_selection = options.index("Upload")
+    method = st.radio("Method", options, index=initial_selection)
+    if method == "Camera":
+        picture = st.camera_input("picture", key="loginPic", label_visibility='hidden')
+    if method == "Upload":
+        picture = st.file_uploader("Choose a file", type=["jpg", "jpeg", "png"])
+
+    if picture:
+        form = st.form("Register")
+        name = form.text_input("Username")
+        min_date = datetime.datetime(1900, 1, 1)
+        max_date = datetime.datetime.today()
+        dob = form.date_input("DOB", min_value=min_date, max_value=max_date)
+        city = form.text_input("City")
+        submit = form.form_submit_button("submit")
+        if submit:
+            if not name or not dob or not city:
+                st.error("Please enter your name, DOB and city")
+            else:
+                st.success("registered successfully")
+                user_id = insert_user_detail(city, dob, name)
+                know_user_dir = "./known_user/"
+                image.save_image(picture, know_user_dir, str(user_id))
+
+
+def insert_user_detail(city, dob, name):
+    user_detail = UserDetail(name, dob, city)
+    db = Database()
+    user_id = db.insert_user_detail(user_detail)
+    return user_id
+
+
+
+

requirements.txt

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+altair==5.2.0
+attrs==23.2.0
+blinker==1.7.0
+cachetools==5.3.3
+certifi==2024.2.2
+charset-normalizer==3.3.2
+click==8.1.7
+cryptography==42.0.5
+dlib==19.24.2
+face-recognition==1.3.0
+face-recognition-models==0.3.0
+gitdb==4.0.11
+GitPython==3.1.42
+idna==3.6
+importlib-metadata==7.0.1
+Jinja2==3.1.3
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+mdurl==0.1.2
+numpy==1.26.4
+opencv-python==4.6.0.66
+packaging==23.2
+pandas==2.2.1
+protobuf==4.25.3
+pyarrow==15.0.0
+pydeck==0.8.1b0
+Pygments==2.17.2
+python-dateutil==2.9.0.post0
+pytz==2024.1
+referencing==0.33.0
+requests==2.31.0
+rich==13.7.1
+rpds-py==0.18.0
+six==1.16.0
+smmap==5.0.1
+streamlit==1.31.1
+tenacity==8.2.3
+toml==0.10.2
+toolz==0.12.1
+tornado==6.4
+typing_extensions==4.10.0
+tzdata==2024.1
+tzlocal==5.2
+urllib3==2.2.1
+validators==0.22.0
+watchdog==4.0.0
+zipp==3.17.0