from flask import Flask, request, jsonify, render_template, url_for
from PIL import Image
import os
import numpy as np
import config
import face_recognition
from utils import faceUtils

app = Flask(__name__)


@app.route('/upload_face', methods=['POST'])
def upload_face_api():
    if 'file' not in request.files:
        return jsonify({'error': 'No file part in the request'}), 400
    # 检查文件大小（例如，限制为 2MB）
    file = request.files['file']
    if file.content_length > 2 * 1024 * 1024:
        return jsonify({'error': 'File is too large'}), 400
    name = file.filename.split('.')[0]
    try:
        # 创建一个唯一的文件名
        image_path = os.path.join(config.UPLOAD_FOLDER, file.filename)
        encoding_path = os.path.join(config.UPLOAD_FOLDER, f"{name}.npy")
        # 将上传的文件保存到磁盘
        file.save(image_path)
        # 加载图像并转换为 RGB
        image = Image.open(image_path).convert('RGB')
        image_np = np.array(image)
        # 使用 face_recognition 提取人脸特征
        face_locations = face_recognition.face_locations(image_np)
        if len(face_locations) == 0:
            return jsonify({'error': 'No faces found in the image'}), 400
        face_encodings = face_recognition.face_encodings(image_np, face_locations)
        # 假设只处理图像中的第一张脸 将新上传的人脸特征和姓名存储到字典中
        face_encoding = face_encodings[0]
        faceUtils.face_data[name] = face_encoding
        # 将特征保存为 NumPy 文件
        np.save(encoding_path, face_encoding)
        return jsonify({'message': 'Face uploaded and features extracted successfully'}), 200
    except Exception as e:
        return jsonify({'error': str(e)}), 500


@app.route('/compare_faces', methods=['POST'])
def compare_faces_api():
    if 'face' not in request.files:
        return jsonify({'error': 'No face image part in the request'}), 400
    face = request.files['face']
    try:
        # 加载并处理上传的人脸图像
        image1 = Image.open(face).convert('RGB')
        image1_np = np.array(image1)
        face_locations1 = face_recognition.face_locations(image1_np)
        if len(face_locations1) == 0:
            return jsonify({'error': 'No faces found in the image'}), 400
        face_encodings1 = face_recognition.face_encodings(image1_np, face_locations1)
        face_encoding1 = face_encodings1[0]
        # 比较上传的人脸与已知人脸
        best_match, best_distance = faceUtils.compare_faces(face_encoding1)
        if best_match is None:
            return jsonify({'matched_name': 'Unknown', 'confidence': best_distance}), 200
        else:
            return jsonify({'matched_name': best_match, 'confidence': best_distance}), 200
    except Exception as e:
        return jsonify({'error': str(e)}), 500


@app.route('/list_faces', methods=['GET'])
def list_faces():
    images = os.listdir(config.UPLOAD_FOLDER)
    image_files = [{'filename': f, 'url': url_for('static', filename='uploads/' + f)}
                   for f in images if f.lower().endswith(('.png', '.jpg', '.jpeg', '.gif'))]
    return jsonify(image_files)


@app.route('/')
def index():
    # 渲染 templates 文件夹中的 index.html 文件
    return render_template('index.html')


if __name__ == '__main__':
    faceUtils.load_known_face_encodings()
    app.run(debug=True)