caffe代码DataTransform

/////////////////TransformationParameter的caffe消息定义
/*
// Message that stores parameters used to apply transformation
// to the data layer's data
message TransformationParameter {
  // For data pre-processing, we can do simple scaling and subtracting the
  // data mean, if provided. Note that the mean subtraction is always carried
  // out before scaling.
  optional float scale = 1 [default = 1];
  // Specify if we want to randomly mirror data.
  optional bool mirror = 2 [default = false];
  // Specify if we would like to randomly crop an image.
  optional uint32 crop_size = 3 [default = 0];
  // mean_file and mean_value cannot be specified at the same time
  optional string mean_file = 4;
  // if specified can be repeated once (would substract it from all the channels)
  // or can be repeated the same number of times as channels
  // (would subtract them from the corresponding channel)
  repeated float mean_value = 5;
  // Force the decoded image to have 3 color channels.
  optional bool force_color = 6 [default = false];
  // Force the decoded image to have 1 color channels.
  optional bool force_gray = 7 [default = false];
}
*/
/*
DataTransformer类主要负责对数据进行预处理， 比如减去均值、进行crop，镜像，强制设置为彩色强制设置为灰度图像以及像素值的缩放，此外该类还将Datum、const vector<Datum>、cv::Mat&、vector<cv::Mat> 、Blob<Dtype>*类型的数据变换到目标大小的blob。负责对上述类型的数据推断其shape。
*/
#ifndef CAFFE_DATA_TRANSFORMER_HPP
#define CAFFE_DATA_TRANSFORMER_HPP
#include <vector>
#include "caffe/blob.hpp"
#include "caffe/common.hpp"
#include "caffe/proto/caffe.pb.h"

namespace caffe {

/**
 * @brief Applies common transformations to the input data, such as
 * scaling, mirroring, substracting the image mean...
 */
template <typename Dtype>
class DataTransformer {
 public:
  explicit DataTransformer(const TransformationParameter& param, Phase phase);
  virtual ~DataTransformer() {}

  /**
   * @brief Initialize the Random number generations if needed by the
   *    transformation.
   */
// 初始化随机数生成器，因为在对数据进行变换的时候有可能用到，比如说打乱数据的输入顺序
  void InitRand();

  /**
   * @brief Applies the transformation defined in the data layer's
   * transform_param block to the data.
   *
   * @param datum
   *    Datum containing the data to be transformed.
   * @param transformed_blob
   *    This is destination blob. It can be part of top blob's data if
   *    set_cpu_data() is used. See data_layer.cpp for an example.
   */
// 对Datum的数据进行变换，放入到transformed_blob中
  void Transform(const Datum& datum, Blob<Dtype>* transformed_blob);

  /**
   * @brief Applies the transformation defined in the data layer's
   * transform_param block to a vector of Datum.
   *
   * @param datum_vector
   *    A vector of Datum containing the data to be transformed.
   * @param transformed_blob
   *    This is destination blob. It can be part of top blob's data if
   *    set_cpu_data() is used. See memory_layer.cpp for an example.
   */
// 对Datum容器的数据进行变换翻入到transformed_blob
  void Transform(const vector<Datum> & datum_vector,
                Blob<Dtype>* transformed_blob);

#ifdef USE_OPENCV
  /**
   * @brief Applies the transformation defined in the data layer's
   * transform_param block to a vector of Mat.
   *
   * @param mat_vector
   *    A vector of Mat containing the data to be transformed.
   * @param transformed_blob
   *    This is destination blob. It can be part of top blob's data if
   *    set_cpu_data() is used. See memory_layer.cpp for an example.
   */
// 如果定义OpenCV还可能对mat容器数据类型的数据进行变换
  void Transform(const vector<cv::Mat> & mat_vector,
                Blob<Dtype>* transformed_blob);

  /**
   * @brief Applies the transformation defined in the data layer's
   * transform_param block to a cv::Mat
   *
   * @param cv_img
   *    cv::Mat containing the data to be transformed.
   * @param transformed_blob
   *    This is destination blob. It can be part of top blob's data if
   *    set_cpu_data() is used. See image_data_layer.cpp for an example.
   */
// 将opencv读取的单个图像转换到blob中去
  void Transform(const cv::Mat& cv_img, Blob<Dtype>* transformed_blob);
#endif  // USE_OPENCV

  /**
   * @brief Applies the same transformation defined in the data layer's
   * transform_param block to all the num images in a input_blob.
   *
   * @param input_blob
   *    A Blob containing the data to be transformed. It applies the same
   *    transformation to all the num images in the blob.
   * @param transformed_blob
   *    This is destination blob, it will contain as many images as the
   *    input blob. It can be part of top blob's data.
   */
// 将输入的blob进行变换，可能是取出blob的中的一部分数据到新的blob
  void Transform(Blob<Dtype>* input_blob, Blob<Dtype>* transformed_blob);

  /**
   * @brief Infers the shape of transformed_blob will have when
   *    the transformation is applied to the data.
   *
   * @param datum
   *    Datum containing the data to be transformed.
   */
// 根据Datum获取blob的形状
  vector<int> InferBlobShape(const Datum& datum);
  /**
   * @brief Infers the shape of transformed_blob will have when
   *    the transformation is applied to the data.
   *    It uses the first element to infer the shape of the blob.
   *
   * @param datum_vector
   *    A vector of Datum containing the data to be transformed.
   */
// 根据Datum容器获取blob的形状
  vector<int> InferBlobShape(const vector<Datum> & datum_vector);
  /**
   * @brief Infers the shape of transformed_blob will have when
   *    the transformation is applied to the data.
   *    It uses the first element to infer the shape of the blob.
   *
   * @param mat_vector
   *    A vector of Mat containing the data to be transformed.
   */
#ifdef USE_OPENCV
// 根据Mat容器获取blob的形状
  vector<int> InferBlobShape(const vector<cv::Mat> & mat_vector);
  /**
   * @brief Infers the shape of transformed_blob will have when
   *    the transformation is applied to the data.
   *
   * @param cv_img
   *    cv::Mat containing the data to be transformed.
   */
// 根据Mat获取blob的形状
  vector<int> InferBlobShape(const cv::Mat& cv_img);
#endif  // USE_OPENCV

 protected:
   /**
   * @brief Generates a random integer from Uniform({0, 1, ..., n-1}).
   *
   * @param n
   *    The upperbound (exclusive) value of the random number.
   * @return
   *    A uniformly random integer value from ({0, 1, ..., n-1}).
   */
// 生成从0到n-1的服从均匀分布的随机数,要求继承他的都必须实现如何生成随机数
  virtual int Rand(int n);
// 将给定的Datum进行转换
  void Transform(const Datum& datum, Dtype* transformed_data);

  // 变换所使用的参数
  TransformationParameter param_;
  // 随机数生成器的种子
  shared_ptr<Caffe::RNG> rng_;
  // 是训练还是测试？
  Phase phase_;
  // 数据均值 blob
  Blob<Dtype> data_mean_;
  // 数据均值blob的容器
  vector<Dtype> mean_values_;
};

}  // namespace caffe

#endif  // CAFFE_DATA_TRANSFORMER_HPP_