app.py

from flask import Flask, request, jsonify
from deepface import DeepFace
import cv2
import numpy as np
import logging
from flask_cors import CORS

app = Flask(__name__)
CORS(app)

logging.basicConfig(level=logging.DEBUG)

@app.route('/detect_emotion', methods=['POST'])
def detect():
    if 'image' not in request.files:
        print('Image not provided')
        return jsonify({
            'status': 'fail', 'message': 'Image not provided'
        }), 400
    file = request.files['image']

    if not file:
        print('Image not as file')
        return jsonify({'status': 'fail', 'message': 'Invalid image data'}), 400
    
    try:
        # Read the image in OpenCV format
        file_bytes = np.frombuffer(file.read(), np.uint8)
        img = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
        
        if img is None:
            print('No image')
            return jsonify({'status': 'fail', 'message': 'Invalid image data'}), 400
        
        new_image_path = f'api/detect_emotion.jpg'
        cv2.imwrite(new_image_path, img)

        objs = DeepFace.analyze(
        img_path = new_image_path, 
        actions = ['emotion'],
        )

        print(objs)
        return jsonify({'status': 'success', 'message': 'emotion detected'})

    except Exception as e:
        app.logger.error(f'Error processing image: {e}')
        return jsonify({'status': 'error', 'message': str(e)}), 500


@app.route('/save_faceimage', methods=['POST'])
def save():
    if 'image' not in request.files or 'name' not in request.form:
        return jsonify({'status': 'fail', 'message': 'Image or name not provided'}), 400
    
    file = request.files['image']
    user_name = request.form['name']

    if not file or not user_name:
        return jsonify({'status': 'fail', 'message': 'Invalid image data or name'}), 400
    
    try:
        # Read the image in OpenCV format
        file_bytes = np.frombuffer(file.read(), np.uint8)
        img = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
        
        if img is None:
            return jsonify({'status': 'fail', 'message': 'Invalid image data'}), 400
        
        new_image_path = f'api/{user_name}.jpg'
        cv2.imwrite(new_image_path, img)
        return jsonify({'status': 'success', 'message': f'Image saved as {new_image_path}'})
    
    except Exception as e:
        app.logger.error(f'Error processing image: {e}')
        return jsonify({'status': 'error', 'message': str(e)}), 500

@app.route('/face_recognition', methods=['POST'])
def recognize():
    if 'image' not in request.files or 'name' not in request.form:
        return jsonify({'status': 'fail', 'message': 'Image or name not provided'}), 400
    
    file = request.files['image']
    user_name = request.form['name']
    
    if not file or not user_name:
        return jsonify({'status': 'fail', 'message': 'Invalid image data or name'}), 400
    
    try:
        # Read the image in OpenCV format
        file_bytes = np.fromstring(file.read(), np.uint8)
        img = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
        
        if img is None:
            return jsonify({'status': 'fail', 'message': 'Invalid image data'}), 400
        
        # Save the captured image temporarily
        captured_image_path = 'api/captured_image.jpg'
        cv2.imwrite(captured_image_path, img)

        # Path to the known image
        known_image_path = f'api/{user_name}.jpg'  # Change this to the path of your known image
        print(known_image_path)
        
        # Perform face verification
        result = DeepFace.verify(img1_path=captured_image_path, img2_path=known_image_path)
        
        if result['verified']:
            return jsonify({'status': 'success', 'message': 'Face recognized'})
        else:
            return jsonify({'status': 'fail', 'message': 'Face not recognized'})
    
    except Exception as e:
        return jsonify({'status': 'error', 'message': str(e)}), 500

if __name__ == "__main__":
    app.run(debug=True)