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README.md

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-# faceRecognitionAndSearcher
-
+# Face Recognition and Search Application
+
+## Overview
+This repository contains a face recognition and search system built with Python. The application allows for the detection, encoding, and storage of facial data in a MongoDB database. It supports searching for similar faces based on the stored data and provides a graphical user interface (GUI) to manage the face search and display results. 
+
+## Features
+- **Face detection and recognition:** Extract faces from images, encode them, and save unique faces to a database.
+- **Database management:** Stores face encodings and image metadata using MongoDB.
+- **Face search functionality:** Find similar faces from the database using face encoding comparison.
+- **Graphical User Interface (GUI):** Built with Tkinter for managing face data and searching faces. (to be updated)
+- **Logging:** Application logs all key actions and events to a log file and console.
+
+## Project Structure
+
+```
+.
+├── database.py        # Handles MongoDB operations and face encoding storage/retrieval
+├── face_detection.py  # Processes images, detects faces, and manages face data storage
+├── gui.py             # GUI implementation for searching and displaying face data
+├── main.py            # Entry point for running the GUI application
+├── search.py          # Contains functions to search faces by ID
+├── images/            # Folder where input images are stored
+└── unique_faces/      # Folder where unique face images are saved
+```
+
+## Dependencies
+Make sure you have the following libraries installed before running the code:
+- `pymongo`: For database operations.
+- `face_recognition`: For facial recognition and encoding.
+- `opencv-python`: For image processing.
+- `pillow`: For handling images in the GUI.
+- `tkinter`: For GUI development (comes pre-installed with Python).
+- `numpy`: For handling face encoding data.
+
+Install all dependencies via `pip`:
+
+```bash
+pip install pymongo face_recognition opencv-python pillow numpy
+```
+
+or 
+
+```bash
+pip install -r requirements.txt
+```
+
+## Usage
+
+### 1. Setting Up MongoDB
+Ensure that MongoDB is running on `localhost:27017` and the database `face_recognition_db` is created. The face encodings and metadata will be stored in the `faces_collection`.
+
+### 2. Running the Face Processing Script
+To extract and save unique faces from images:
+
+1. Place your images in the `images/` folder.
+2. Run the following script to detect faces and store them in MongoDB:
+
+```bash
+python face_detection.py
+```
+
+This will:
+- Extract faces from the images.
+- Store each unique face's encoding and associated metadata in MongoDB.
+- Save each detected face as an image in the `unique_faces/` folder.
+
+### 3. Running the GUI Application
+To launch the face search interface:
+
+```bash
+python main.py
+```
+
+The GUI will display all unique faces. You can select a face and search for its occurrences in the images.
+
+### 4. Searching Faces
+- **Select a face**: Click on a face from the GUI.
+- **Search for occurrences**: Click the "Search Selected Face" button to find where this face appears across the images.
+
+## Logging
+All key operations (face detection, saving, searching) are logged into `app.log`. You can change the logging level for more or less verbosity by modifying the `logging.basicConfig` configuration in each file.
+
+## Customization
+
+- **Face Similarity Tolerance**: Adjust the `FACE_SIMILARITY_TOLERANCE` constant in `database.py` to change how strict the face similarity comparison is.
+- **Unique Faces Directory**: Change the folder where unique faces are saved by modifying the `unique_faces_folder` path in `face_detection.py`.
+
+## Troubleshooting
+- Ensure MongoDB is running and accessible at `localhost:27017`.
+- Make sure the required Python dependencies are installed.
+- Check `app.log` for detailed error logs.
+
+## License
+This project is licensed under the MIT License.