Micaela Verucchi
264 lines
11 KiB
C++
264 lines
11 KiB
C++
#include "tkDNN/DarknetParser.h"
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namespace tk { namespace dnn {
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std::string darknetParseType(const std::string& line){
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size_t start = line.find("[");
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size_t end = line.find("]");
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if( start == std::string::npos || end == std::string::npos)
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return "";
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start++;
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std::string type = line.substr(start, end-start);
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return type;
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}
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bool divideNameAndValue(const std::string& line, std::string&name, std::string& value){
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size_t sep = line.find("=");
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if(sep == std::string::npos)
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return false;
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name = line.substr(0, sep);
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value = line.substr(sep+1, line.size() - (sep+1));
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return true;
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}
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std::vector<int> fromStringToIntVec(const std::string& line, const char delimiter){
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std::stringstream linestream(line);
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std::string value;
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std::vector<int> values;
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while(getline(linestream,value,delimiter))
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values.push_back(std::stoi(value));
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return values;
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}
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bool darknetParseFields(const std::string& line, darknetFields_t& fields){
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std::string name,value;
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if(!divideNameAndValue(line, name, value))
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return false;
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if(name.find("width") != std::string::npos)
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fields.width = std::stoi(value);
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else if(name.find("height") != std::string::npos)
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fields.height = std::stoi(value);
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else if(name.find("channels") != std::string::npos)
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fields.channels = std::stoi(value);
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else if(name.find("batch_normalize") != std::string::npos)
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fields.batch_normalize = std::stoi(value);
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else if(name.find("filters") != std::string::npos)
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fields.filters = std::stoi(value);
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else if(name.find("activation") != std::string::npos)
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fields.activation = value;
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else if(name.find("size") != std::string::npos){
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fields.size_x = std::stoi(value);
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fields.size_y = std::stoi(value);
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}
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else if(name.find("size_x") != std::string::npos)
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fields.size_x = std::stoi(value);
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else if(name.find("size_y") != std::string::npos)
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fields.size_y = std::stoi(value);
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else if(name.find("stride") != std::string::npos){
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fields.stride_x = std::stoi(value);
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fields.stride_y = std::stoi(value);
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}
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else if(name.find("stride_x") != std::string::npos)
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fields.stride_x = std::stoi(value);
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else if(name.find("stride_y") != std::string::npos)
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fields.stride_y = std::stoi(value);
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else if(name.find("pad") != std::string::npos)
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fields.pad = std::stoi(value);
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else if(name.find("classes") != std::string::npos)
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fields.classes = std::stoi(value);
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else if(name.find("num") != std::string::npos)
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fields.num = std::stoi(value);
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else if(name.find("coords") != std::string::npos)
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fields.coords = std::stoi(value);
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else if(name.find("groups") != std::string::npos)
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fields.groups = std::stoi(value);
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else if(name.find("group_id") != std::string::npos)
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fields.group_id = std::stoi(value);
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else if(name.find("scale_x_y") != std::string::npos)
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fields.scale_xy = std::stof(value);
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else if(name.find("from") != std::string::npos)
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fields.layers.push_back(std::stof(value));
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else if(name.find("mask") != std::string::npos){
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auto vec = fromStringToIntVec(value, ',');
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fields.n_mask = vec.size();
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}
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else if(name.find("layers") != std::string::npos)
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fields.layers = fromStringToIntVec(value, ',');
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else
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std::cout<<"Not supported field: "<<line<<std::endl;
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return true;
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}
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tk::dnn::Network *darknetAddNet(darknetFields_t &fields) {
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//std::cout<<"Add Net: "<<fields.type<<"\n";
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dataDim_t dim(1, fields.channels, fields.height, fields.width);
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return new tk::dnn::Network(dim);
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}
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void darknetAddLayer(tk::dnn::Network *net, darknetFields_t &f, std::string wgs_path, std::vector<tk::dnn::Layer*> &netLayers, const std::vector<std::string>& names) {
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if(net == nullptr)
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FatalError("Cant add a layer without a Net\n");
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// padding compute
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if(f.pad == 1) {
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f.padding_x = f.padding_y = f.size_x /2;
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}
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//std::cout<<"Add layer: "<<f.type<<"\n";
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if(f.type == "convolutional") {
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std::string wgs = wgs_path + "/c" + std::to_string(netLayers.size()) + ".bin";
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//printf("%d (%d,%d) (%d,%d) (%d,%d) %s %d %d\n", f.filters, f.size_x, f.size_y, f.stride_x, f.stride_y, f.padding_x, f.padding_y, wgs.c_str(), f.batch_normalize, f.groups);
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tk::dnn::Conv2d *l= new tk::dnn::Conv2d(net, f.filters, f.size_x, f.size_y, f.stride_x,
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f.stride_y, f.padding_x, f.padding_y, wgs, f.batch_normalize, false, f.groups);
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netLayers.push_back(l);
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} else if(f.type == "maxpool") {
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if(f.stride_x == 1 && f.stride_y == 1)
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netLayers.push_back(new tk::dnn::Pooling(net, f.size_x, f.size_y, f.stride_x, f.stride_y,
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f.padding_x, f.padding_y, tk::dnn::POOLING_MAX_FIXEDSIZE));
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else
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netLayers.push_back(new tk::dnn::Pooling(net, f.size_x, f.size_y, f.stride_x, f.stride_y,
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f.padding_x, f.padding_y, tk::dnn::POOLING_MAX));
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} else if(f.type == "avgpool") {
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netLayers.push_back(new tk::dnn::Pooling(net, f.size_x, f.size_y, f.stride_x, f.stride_y,
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f.padding_x, f.padding_y, tk::dnn::POOLING_AVERAGE));
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} else if(f.type == "shortcut") {
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if(f.layers.size() != 1) FatalError("no layers to shortcut\n");
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int layerIdx = f.layers[0];
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if(layerIdx < 0)
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layerIdx = netLayers.size() + layerIdx;
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if(layerIdx < 0 || layerIdx >= netLayers.size()) FatalError("impossible to shortcut\n");
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//std::cout<<"shortcut to "<<layerIdx<<" "<<netLayers[layerIdx]->getLayerName()<<"\n";
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netLayers.push_back(new tk::dnn::Shortcut(net, netLayers[layerIdx]));
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} else if(f.type == "upsample") {
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netLayers.push_back(new tk::dnn::Upsample(net, f.stride_x));
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} else if(f.type == "route") {
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if(f.layers.size() == 0) FatalError("no layers to Route\n");
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std::vector<tk::dnn::Layer*> layers;
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for(int i=0; i<f.layers.size(); i++) {
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int layerIdx = f.layers[i];
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if(layerIdx < 0)
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layerIdx = netLayers.size() + layerIdx;
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if(layerIdx < 0 || layerIdx >= netLayers.size()) FatalError("impossible to route\n");
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//std::cout<<"Route to "<<layerIdx<<" "<<netLayers[layerIdx]->getLayerName()<<"\n";
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layers.push_back(netLayers[layerIdx]);
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}
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netLayers.push_back(new tk::dnn::Route(net, layers.data(), layers.size(), f.groups, f.group_id));
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} else if(f.type == "reorg") {
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netLayers.push_back(new tk::dnn::Reorg(net, f.stride_x));
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} else if(f.type == "region") {
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netLayers.push_back(new tk::dnn::Region(net, f.classes, f.coords, f.num));
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} else if(f.type == "yolo") {
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std::string wgs = wgs_path + "/g" + std::to_string(netLayers.size()) + ".bin";
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//printf("%d %d %s %d %f\n", f.classes, f.num/f.n_mask, wgs.c_str(), f.n_mask, f.scale_xy);
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tk::dnn::Yolo *l = new tk::dnn::Yolo(net, f.classes, f.num/f.n_mask, wgs, f.n_mask, f.scale_xy);
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if(names.size() != f.classes)
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FatalError("Mismatch between number of classes and names");
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l->classesNames = names;
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netLayers.push_back(l);
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} else{
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FatalError("layer not supported: " + f.type);
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}
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// add activation
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if(netLayers.size() > 0 && f.activation != "linear") {
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tkdnnActivationMode_t act;
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if(f.activation == "relu") act = tkdnnActivationMode_t(CUDNN_ACTIVATION_RELU);
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else if(f.activation == "leaky") act = tk::dnn::ACTIVATION_LEAKY;
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else if(f.activation == "mish") act = tk::dnn::ACTIVATION_MISH;
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else { FatalError("activation not supported: " + f.activation); }
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netLayers[netLayers.size()-1] = new tk::dnn::Activation(net, act);
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};
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}
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std::vector<std::string> darknetReadNames(const std::string& names_file){
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std::ifstream if_names(names_file);
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if(!if_names.is_open())
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FatalError("cloud not open names file: " + names_file);
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std::vector<std::string> names;
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std::string line;
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while(std::getline(if_names, line))
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if(line != "")
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names.push_back(line);
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if_names.close();
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return names;
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}
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tk::dnn::Network* darknetParser(const std::string& cfg_file, const std::string& wgs_path, const std::string& names_file) {
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tk::dnn::Network *net = nullptr;
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// layers without activations to retrive correct id number
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std::vector<tk::dnn::Layer*> netLayers;
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std::ifstream if_cfg(cfg_file);
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if(!if_cfg.is_open())
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FatalError("cloud not open cfg file: " + cfg_file);
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std::vector<std::string> names = darknetReadNames(names_file);
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darknetFields_t fields; // will be filled with layers fields
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std::string line;
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while(std::getline(if_cfg, line)) {
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// remove comments
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std::size_t found = line.find("#");
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if ( found != std::string::npos ) {
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line = line.substr(0, found);
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}
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// skip empty lines
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if(line.size() == 0)
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continue;
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std::string type = darknetParseType(line);
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if(type.size() > 0) {
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// end of filled type
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if(fields.type != "") {
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if(fields.type == "net")
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net = darknetAddNet(fields);
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else
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darknetAddLayer(net, fields, wgs_path, netLayers, names);
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}
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// new type
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//std::cout<<"type: "<<type<<"\n";
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fields = darknetFields_t(); // reset to default
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fields.type = type;
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continue;
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}
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if(darknetParseFields(line, fields)) {
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// already parsed do nothing
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} else {
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FatalError("could not parse line: " + line);
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}
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}
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// end of filled type
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if(fields.type != "") {
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darknetAddLayer(net, fields, wgs_path, netLayers, names);
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}
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if(net == nullptr) {
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FatalError("net not found\n");
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}
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return net;
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}
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}}
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