77 lines
2.4 KiB
Python
77 lines
2.4 KiB
Python
from flask import Flask, request, jsonify
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from flask_cors import CORS
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import face_recognition
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import os
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import numpy as np
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import pickle
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app = Flask(__name__)
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CORS(app)
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#pip install Flask flask-cors face_recognition
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# Directory to save student images and encodings
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STUDENT_IMAGES_DIR = 'student_images'
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STUDENT_ENCODINGS_FILE = 'student_encodings.pkl'
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# Ensure the directory exists
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os.makedirs(STUDENT_IMAGES_DIR, exist_ok=True)
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# Load existing encodings if available
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if os.path.exists(STUDENT_ENCODINGS_FILE):
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with open(STUDENT_ENCODINGS_FILE, 'rb') as f:
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student_encodings = pickle.load(f)
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else:
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student_encodings = {}
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@app.route('/upload_images', methods=['POST'])
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def upload_images():
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student_id = request.form.get('student_id')
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if 'images' not in request.files or not student_id:
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return jsonify({"error": "No images or student ID provided"}), 400
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images = request.files.getlist('images')
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encodings = []
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for image in images:
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image_path = os.path.join(STUDENT_IMAGES_DIR, f"{student_id}_{image.filename}")
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image.save(image_path)
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# Load the image and get the face encodings
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img = face_recognition.load_image_file(image_path)
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img_encodings = face_recognition.face_encodings(img)
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if img_encodings:
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encodings.append(img_encodings[0])
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if encodings:
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student_encodings[student_id] = np.mean(encodings, axis=0)
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# Save the encodings to file
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with open(STUDENT_ENCODINGS_FILE, 'wb') as f:
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pickle.dump(student_encodings, f)
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return jsonify({"message": "Images uploaded and processed successfully"}), 200
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else:
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return jsonify({"error": "No faces found in the uploaded images"}), 400
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@app.route('/recognize', methods=['POST'])
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def recognize():
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if 'image' not in request.files:
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return jsonify({"error": "No image provided"}), 400
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image = request.files['image']
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img = face_recognition.load_image_file(image)
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img_encodings = face_recognition.face_encodings(img)
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if img_encodings:
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img_encoding = img_encodings[0]
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distances = {student_id: np.linalg.norm(encoding - img_encoding) for student_id, encoding in student_encodings.items()}
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student_id = min(distances, key=distances.get)
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return jsonify({"student_id": student_id}), 200
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else:
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return jsonify({"error": "No face found in the uploaded image"}), 400
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if __name__ == '__main__':
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app.run(debug=True)
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