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face-anti-spoof's Introduction

人脸翻拍检测

  1. feature_apply: 使用模型进行预测
  2. feature_svm: 特征提取并生成数据保存
  3. feature_train: 训练模型

fisher.py

  1. generate_gmm: 训练GMM模型,并保存N个kernel的均值、方差和权重 1.1 folder_descriptors: 遍历文件夹下的图片,并生成图像特征 1.1.1 image_descriptors: 对输入的图像生成SIFT特征 1.2 dictionary: 训练GMM模型,并返回均值、方差和权重
  2. fisher_features: 遍历文件夹,按照文件夹返回fisher向量 2.1 get_fisher_vectors_from_folder: 遍历文件夹下的图片,生成fisher向量 2.1.1 image_descriptors: 对输入的图像生成SIFT特征 2.1.2 fisher_vector: 对输入的图像特征生成fisher向量 2.1.2.1 likelihood_statistics: 极大似然分析 2.1.2.1.1 likelihood_moment 2.1.2.2 fisher_vector_weights 2.1.2.3 fisher_vector_means 2.1.2.4 fisher_vector_sigma 2.1.2.5 normalize: 正态化特征
  3. train: 训练分类模型

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