#include?“Classifier.h“

Classifier::Classifier（const?string&?deploy_file
??????????????????????????????const?string&?caffe_model_file
??????????????????????????????const?string&?label_file
??????????????????????????????const?string&?mean_file）?{
#ifdef?CPU_ONLY
??Caffe::set_mode（Caffe::CPU）;
#else
??Caffe::set_mode（Caffe::GPU）;
#endif

??/*?Load?the?network.?*/
??//?此時已經給網絡中所有的Blob分配好了內存空間
??net_.reset（new?Net（deploy_file?TEST））;?//?加載網絡參數，deploy.prototxt
??net_->CopyTrainedlayersFrom（caffe_model_file）;?//?加載權值參數，snapshot_iter_38680.caffemodel

??CHECK_EQ（net_->num_inputs（）?1）?<??CHECK_EQ（net_->num_outputs（）?1）?<
??//?第0個Blob就是數據層（輸入層）
??Blob*?input_layer?=?net_->input_blobs（）[0];
??num_channels_?=?input_layer->channels（）;
??CHECK（num_channels_?==?3?||?num_channels_?==?1）
????<yer?should?have?1?or?3?channels.“;
??input_geometry_?=?cv::Size（input_layer->width（）?input_layer->height（））;

??/*?Load?the?binaryproto?mean?file.?*/
??if（mean_file.empty（）||mean_file.size（）==0）
??{
????mean_?=?cv::Mat（input_geometry_?CV_MAKETYPE（CV_32FC1num_channels_）?Scalar（000））;
??}
??else
??{
????SetMean（mean_file）;
??}
??

??/*?Load?labels.?*/
??std::ifstream?labels（label_file.c_str（））;
??CHECK（labels）?<??string?line;
??while?（std::getline（labels?line））
????labels_.push_back（string（line））;

??//?第一個輸出Blob對于分類，就是最后輸出的類別數
??Blob*?output_layer?=?net_->output_blobs（）[0];

??//?channels就表示類別數
??CHECK_EQ（labels_.size（）?output_layer->channels（））
????<yer?dimension.“;
}

static?bool?PairCompare（const?std::pair&?lhs
????????????????????????const?std::pair&?rhs）?{
??return?lhs.first?>?rhs.first;
}

/*?Return?the?indices?of?the?top?N?values?of?vector?v.?*/
static?std::vector?Argmax（const?std::vector&?v?int?N）?{
??std::vector?>?pairs;
??for?（size_t?i?=?0;?i?????pairs.push_back（std::make_pair（v[i]?static_cast（i）））;

??//?對第一個到第三個參數當中的前N個大（或者?。┑臄颠M行排序（后面的就不管了），N的個數由第二個參數與第一個參數的差決定。
??std::partial_sort（pairs.begin（）?pairs.begin（）?+?N?pairs.end（）?PairCompare）;

??std::vector?result;
??for?（int?i?=?0;?i?????result.push_back（pairs[i].second）;
??return?result;
}

/*?步驟：
?*?1.?Mat經過預處理（灰度化，縮放為網絡數據層大小，轉換為float?減去均值）輸入數據層Blob（即轉化為數據層Blob）
*??2.?網絡前向轉播，獲取輸出Blob
*
*/
/*?Return?the?top?N?predictions.?*/
std::vector?Classifier::Classify（const?cv::Mat&?img?int?N）
{
??std::vector?output?=?Predict（img）;

??N?=?std::min（labels_.size（）?N）;
??std::vector?maxN?=?Argmax（output?N）;
??std::vector?predictions;
??for?（int?i?=?0;?i?????int?idx?=?maxN[i];
????predictions.push_back（std::make_pair（labels_[idx]?output[idx]））;
??}

??r

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件??????18012??2018-04-26?23:09??Caffe_SSD\Caffe_SSD.pro

?????文件??????18707??2018-03-10?18:49??Caffe_SSD\Caffe_SSD.pro.user

?????文件??????18693??2018-03-03?17:10??Caffe_SSD\Caffe_SSD.pro.user.42a87c0

?????文件??????23780??2018-03-02?21:32??Caffe_SSD\Caffe_SSD.pro.user.6fd70a7

?????文件???????8229??2017-06-26?14:21??Caffe_SSD\Classifier.cpp

?????文件???????1094??2018-03-02?22:50??Caffe_SSD\Classifier.h

?????文件???????7610??2018-04-26?23:11??Caffe_SSD\convert_annoset.cpp

?????文件???????4552??2018-04-26?23:11??Caffe_SSD\main.cpp

?????文件???????9378??2018-01-02?11:07??Caffe_SSD\source\include\caffe\blob.hpp

?????文件????????634??2018-01-02?11:07??Caffe_SSD\source\include\caffe\caffe.hpp

?????文件???????6179??2018-01-02?11:07??Caffe_SSD\source\include\caffe\common.hpp

?????文件???????2161??2018-01-02?11:07??Caffe_SSD\source\include\caffe\data_reader.hpp

?????文件???????9001??2018-01-02?11:07??Caffe_SSD\source\include\caffe\data_transformer.hpp

?????文件??????10935??2018-01-02?11:07??Caffe_SSD\source\include\caffe\filler.hpp

?????文件???????1382??2018-01-02?11:07??Caffe_SSD\source\include\caffe\internal_thread.hpp

?????文件??????18495??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layer.hpp

?????文件???????2343??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\absval_layer.hpp

?????文件???????3352??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\accuracy_layer.hpp

?????文件???????1309??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\annotated_data_layer.hpp

?????文件???????2727??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\argmax_layer.hpp

?????文件???????6692??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\base_conv_layer.hpp

?????文件???????2948??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\base_data_layer.hpp

?????文件???????3025??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\batch_norm_layer.hpp

?????文件???????2825??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\batch_reindex_layer.hpp

?????文件???????1875??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\bias_layer.hpp

?????文件???????2307??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\bnll_layer.hpp

?????文件???????3130??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\concat_layer.hpp

?????文件???????4076??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\contrastive_loss_layer.hpp

?????文件???????3930??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\conv_layer.hpp

?????文件???????2802??2018-01-02?11:07??Caffe_SSD\source\include\caffe\layers\crop_layer.hpp

............此處省略390個文件信息