人脸真伪检测：使用训练模型识别图像中的人脸真伪

import cv2 from face_recognition import FaceDetector

class TestFaceDetector: '初始化类，传入训练模型路径和待检测图片路径' def init(self, model_path, image_path): self.model_path = model_path self.image_path = image_path

'运行测试，加载图片和模型，检测人脸，绘制方框并标注概率'
def run_test(self):
    # 加载图片
    image = cv2.imread(self.image_path)

    # 加载人脸检测模型
    face_detector = FaceDetector(self.model_path)

    # 检测图片中的人脸
    faces = face_detector.detect_faces(image)

    # 为每个检测到的人脸绘制方框并添加标签
    for face in faces:
        # 获取方框坐标
        x, y, w, h = face['box']

        # 绘制方框
        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)

        # 获取人脸真实性的概率
        prob_real = face['prob_real']

        # 使用真实性概率作为标签
        label = 'Real: {:.2f}%'.format(prob_real * 100)
        cv2.putText(image, label, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

    # 显示带有方框和标签的图片
    cv2.imshow('Image', image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

if name == 'main': model_path = 'path/to/model' image_path = 'path/to/image' test = TestFaceDetector(model_path, image_path) test.run_test()