I have this code:
#include <iostream>
#include <io.h>
#include <fcntl.h>
int main()
{
_setmode(_fileno(stdout), _O_U16TEXT);
std::string t_prefix = "\u2554";
std::string t_middle = "";
std::string t_suffix = "\u2557\n\u2551";
int max_message_length = 33;
for (int i = t_middle.length(); i < max_message_length; i++) {
t_middle = "\u2550" + t_middle;
}
std::string complete_message = t_prefix + t_middle + t_suffix;
std::wcout << L"\u2554" << t_middle.c_str() << L"\u2557\n\u2551";
std::wcout << complete_message.c_str();
//std::wcout << L"\u2554\n";
}
The first wout line prints the first and last part right, the middle section prints out garbage because it does not have the L in it. (How do I use the L with a variable?)
The second wout line combines the prefix, message, and suffix prints out garbage since it needs the L switch to print properly? I find a million of examples of how to do it with straight hard coded text L"\u2554\u2550\u2550" ect ect but I wanted the program to be a little more flexible so the game boarder could be wider if so set.
This seems to work and do what I need it to do at least for windows:
#include <io.h>
#include <fcntl.h>
#include <iostream>
#include <string>
int main()
{
_setmode(_fileno(stdout), _O_U8TEXT);
std::wstring t_prefix { L'\u2554' };
std::wstring t_suffix { L"\u2557\n\u2551" };
std::wstring t_middle;
const size_t max_message_length { 33 };
for (size_t i { t_middle.size() }; i < max_message_length; ++i)
{
t_middle += L'\u2550';
}
std::wstring complete_message { t_prefix + t_middle + t_suffix };
std::wcout << complete_message << '\n';
}
and this is suppose to work on linux:
#include <iostream>
int main()
{
std::string t_prefix = "╔";
std::string t_middle;
std::string t_suffix = "╗\n║";
int max_message_length = 33;
for (int i = t_middle.size(); i < max_message_length; ++i)
t_middle = "═" + t_middle;
std::string complete_message = t_prefix + t_middle + t_suffix;
std::cout << complete_message << '\n';
}
I have coded a program that uses mmap as input to fill a integer 2D vector from a .txt file. The code is part of a larger program and will be submitted to a competition. Is there a way to improve the speed using mmap, or by using a different way all together? Here is the code:
#include <fstream>
#include <vector>
#include <algorithm>
#include <cstring>
#include <iostream>
// for mmap:
#include <sys/mman.h>
#include <sys/stat.h>
#include <fcntl.h>
using namespace std;
const char* map_file(const char* fname, size_t& length);
int main()
{
auto start = std::chrono::high_resolution_clock::now();
size_t length;
auto f = map_file("erasmus.in", length);
auto l = f + length;
int i = 0;
bool flag = false;
string lines;
vector<vector<int> > students(10000); //The number of lines is predefined
const char* temp;
while (f && f!=l) {
string element = "";
temp = static_cast<const char*>(memchr(f, '\n', l-f));
for(f = f; f<=temp; f++)
{
if(!isspace(*f))
{
element += *f;
flag = true;
}
if(isspace(*f) && flag == true)
{
flag = false;
int assigned_element = stoi(element);
students[i].push_back(assigned_element);
element = "";
}
}
i++;
temp++;
}
auto finish = std::chrono::high_resolution_clock::now();
std::chrono::duration<double> elapsed1 = finish - start;
FILE* output = fopen("erasmus.out", "w");
for (int i = 0; i < students.size(); i++)
{
for (int j = 0; j < students[i].size(); j++)
{
fprintf(output, "%d ", students[i][j]);
}
fprintf(output, "\n");
}
std::cout << "Elapsed time: " << elapsed1.count() << " s\n";
return 0;
}
void handle_error(const char* msg) {
perror(msg);
exit(255);
}
const char* map_file(const char* directory, size_t& length)
{
int fileDirectory = open(directory, O_RDONLY);
if (fileDirectory == -1)
handle_error("open");
// obtain file size
struct stat sb;
if (fstat(fileDirectory, &sb) == -1)
handle_error("fstat");
length = sb.st_size;
const char* map = static_cast<const char*>(mmap(NULL, length, PROT_READ, MAP_PRIVATE, fileDirectory, 0u));
if (map == MAP_FAILED)
handle_error("mmap");
return map;
}
The file will be executed on a linux system, if this helps to find the optimal answer. At the end of each line of the .txt
there is a space character (' ') and a newline('\n')
Mxnet c++ inference with MXPredSetInput segmentation fault
1. background
I have tried https://github.com/apache/incubator-mxnet/tree/master/example/image-classification/predict-cpp successed.
But when I try to deploy mxnet in c++ with my own model, I met a segmentation fault error:
[17:33:07] src/nnvm/legacy_json_util.cc:209: Loading symbol saved by previous version v1.2.1. Attempting to upgrade...
Signal: SIGSEGV (Segmentation fault)
2. code with error:
MXPredSetInput(pred_hnd, "data", image_data.data(), static_cast<mx_uint>(image_size));
3. tips
First I thought it's because of input data shape not compatible with the model input layer.But I ask model designer, it's a resnet model with conv only, so, any kind input shape should be OK.
4. Download model:
Download them, and put them into model dir.
https://drive.google.com/drive/folders/16MEKNOz_iwquVxHMk9c7igmBNuT6w7wz?usp=sharing
4. code: find: https://github.com/jaysimon/mxnet_cpp_infere
#include <cstdio>
#include <cstdlib>
#include <iostream>
#include <fstream>
#include <vector>
#include <memory>
#include <thread>
#include <iomanip>
#include <opencv2/opencv.hpp>
// Path for c_predict_api
#include <mxnet/c_predict_api.h>
const mx_float DEFAULT_MEAN = 117.0;
static std::string trim(const std::string& input) {
auto not_space = [](int ch) {
return !std::isspace(ch);
};
auto output = input;
output.erase(output.begin(), std::find_if(output.begin(), output.end(), not_space));
output.erase(std::find_if(output.rbegin(), output.rend(), not_space).base(), output.end());
return output;
}
// Read file to buffer
class BufferFile {
public :
std::string file_path_;
std::size_t length_ = 0;
std::unique_ptr<char[]> buffer_;
explicit BufferFile(const std::string& file_path)
: file_path_(file_path) {
std::ifstream ifs(file_path.c_str(), std::ios::in | std::ios::binary);
if (!ifs) {
std::cerr << "Can't open the file. Please check " << file_path << ". \n";
return;
}
ifs.seekg(0, std::ios::end);
length_ = static_cast<std::size_t>(ifs.tellg());
ifs.seekg(0, std::ios::beg);
std::cout << file_path.c_str() << " ... " << length_ << " bytes\n";
// Buffer as null terminated to be converted to string
buffer_.reset(new char[length_ + 1]);
buffer_[length_] = 0;
ifs.read(buffer_.get(), length_);
ifs.close();
}
std::size_t GetLength() {
return length_;
}
char* GetBuffer() {
return buffer_.get();
}
};
void GetImageFile(const std::string& image_file,
mx_float* image_data, int channels,
cv::Size resize_size, const mx_float* mean_data = nullptr) {
// Read all kinds of file into a BGR color 3 channels image
cv::Mat im_ori = cv::imread(image_file, cv::IMREAD_COLOR);
if (im_ori.empty()) {
std::cerr << "Can't open the image. Please check " << image_file << ". \n";
assert(false);
}
cv::Mat im;
resize(im_ori, im, resize_size);
int size = im.rows * im.cols * channels;
mx_float* ptr_image_r = image_data;
mx_float* ptr_image_g = image_data + size / 3;
mx_float* ptr_image_b = image_data + size / 3 * 2;
float mean_b, mean_g, mean_r;
mean_b = mean_g = mean_r = DEFAULT_MEAN;
mean_b = 103.06;
mean_g = 115.9;
mean_r = 123.15;
for (int i = 0; i < im.rows; i++) {
auto data = im.ptr<uchar>(i);
for (int j = 0; j < im.cols; j++) {
if (channels > 1) {
*ptr_image_b++ = static_cast<mx_float>(*data++) - mean_b;
*ptr_image_g++ = static_cast<mx_float>(*data++) - mean_g;
}
*ptr_image_r++ = static_cast<mx_float>(*data++) - mean_r;
}
}
}
// LoadSynsets
// Code from : https://github.com/pertusa/mxnet_predict_cc/blob/master/mxnet_predict.cc
std::vector<std::string> LoadSynset(const std::string& synset_file) {
std::ifstream fi(synset_file.c_str());
if (!fi.is_open()) {
std::cerr << "Error opening synset file " << synset_file << std::endl;
assert(false);
}
std::vector<std::string> output;
std::string synset, lemma;
while (fi >> synset) {
getline(fi, lemma);
output.push_back(lemma);
}
fi.close();
return output;
}
void PrintOutputResult(const std::vector<float>& data, const std::vector<std::string>& synset) {
if (data.size() != synset.size()) {
std::cerr << "Result data and synset size do not match!" << std::endl;
}
float best_accuracy = 0.0;
std::size_t best_idx = 0;
for (std::size_t i = 0; i < data.size(); ++i) {
std::cout << "Accuracy[" << i << "] = " << std::setprecision(8) << data[i] << std::endl;
if (data[i] > best_accuracy) {
best_accuracy = data[i];
best_idx = i;
}
}
std::cout << "Best Result: " << trim(synset[best_idx]) << " (id=" << best_idx << ", " <<
"accuracy=" << std::setprecision(8) << best_accuracy << ")" << std::endl;
}
void predict(PredictorHandle pred_hnd, const std::vector<mx_float> &image_data,
NDListHandle nd_hnd, const std::string &synset_file, int i) {
auto image_size = image_data.size();
// Set Input
//>>>>>>>>>>>>>>>>>>>> Problem code <<<<<<<<<<<<<<<<<<<<<<<
MXPredSetInput(pred_hnd, "data", image_data.data(), static_cast<mx_uint>(image_size));
// <<<<<<<<<<<<<<<<<<<<<<< Problem code <<<<<<<<<<<<<<<<<<<<<<<
// Do Predict Forward
MXPredForward(pred_hnd);
mx_uint output_index = 0;
mx_uint* shape = nullptr;
mx_uint shape_len;
// Get Output Result
MXPredGetOutputShape(pred_hnd, output_index, &shape, &shape_len);
std::size_t size = 1;
for (mx_uint i = 0; i < shape_len; ++i) { size *= shape[i]; }
std::vector<float> data(size);
MXPredGetOutput(pred_hnd, output_index, &(data[0]), static_cast<mx_uint>(size));
// Release NDList
if (nd_hnd) {
MXNDListFree(nd_hnd);
}
// Release Predictor
MXPredFree(pred_hnd);
// Synset path for your model, you have to modify it
auto synset = LoadSynset(synset_file);
// Print Output Data
PrintOutputResult(data, synset);
}
int main(int argc, char* argv[]) {
if (argc < 2) {
std::cout << "No test image here." << std::endl
<< "Usage: ./image-classification-predict apple.jpg [num_threads]" << std::endl;
return EXIT_FAILURE;
}
std::string test_file(argv[1]);
int num_threads = 1;
if (argc == 3)
num_threads = std::atoi(argv[2]);
// Models path for your model, you have to modify it
std::string json_file = "../model/rfcn_dcn_chicken-0000.json";
std::string param_file = "../model/rfcn_dcn_chicken-0000.params";
std::string synset_file = "../model/synset.txt";
std::string nd_file = "../model/mean_224.nd";
BufferFile json_data(json_file);
BufferFile param_data(param_file);
// Parameters
int dev_type = 1; // 1: cpu, 2: gpu
int dev_id = 0; // arbitrary.
mx_uint num_input_nodes = 1; // 1 for feedforward
const char* input_key[1] = { "data" };
const char** input_keys = input_key;
// Image size and channels
int width = 1000;
int height = 562;
int channels = 3;
const mx_uint input_shape_indptr[2] = { 0, 4 };
const mx_uint input_shape_data[4] = { 1,
static_cast<mx_uint>(channels),
static_cast<mx_uint>(height),
static_cast<mx_uint>(width) };
if (json_data.GetLength() == 0 || param_data.GetLength() == 0) {
return EXIT_FAILURE;
}
auto image_size = static_cast<std::size_t>(width * height * channels);
// Read Mean Data
const mx_float* nd_data = nullptr;
NDListHandle nd_hnd = nullptr;
BufferFile nd_buf(nd_file);
if (nd_buf.GetLength() > 0) {
mx_uint nd_index = 0;
mx_uint nd_len;
const mx_uint* nd_shape = nullptr;
const char* nd_key = nullptr;
mx_uint nd_ndim = 0;
MXNDListCreate(static_cast<const char*>(nd_buf.GetBuffer()),
static_cast<int>(nd_buf.GetLength()),
&nd_hnd, &nd_len);
MXNDListGet(nd_hnd, nd_index, &nd_key, &nd_data, &nd_shape, &nd_ndim);
}
// Read Image Data
std::vector<mx_float> image_data(image_size);
GetImageFile(test_file, image_data.data(), channels, cv::Size(width, height), nd_data);
if (num_threads == 1) {
// Create Predictor
PredictorHandle pred_hnd;
MXPredCreate(static_cast<const char*>(json_data.GetBuffer()),
static_cast<const char*>(param_data.GetBuffer()),
static_cast<int>(param_data.GetLength()),
dev_type,
dev_id,
num_input_nodes,
input_keys,
input_shape_indptr,
input_shape_data,
&pred_hnd);
assert(pred_hnd);
predict(pred_hnd, image_data, nd_hnd, synset_file, 0);
} else {
// Create Predictor
std::vector<PredictorHandle> pred_hnds(num_threads, nullptr);
MXPredCreateMultiThread(static_cast<const char*>(json_data.GetBuffer()),
static_cast<const char*>(param_data.GetBuffer()),
static_cast<int>(param_data.GetLength()),
dev_type,
dev_id,
num_input_nodes,
input_keys,
input_shape_indptr,
input_shape_data,
pred_hnds.size(),
pred_hnds.data());
for (auto hnd : pred_hnds)
assert(hnd);
std::vector<std::thread> threads;
for (int i = 0; i < num_threads; i++)
threads.emplace_back(predict, pred_hnds[i], image_data, nd_hnd, synset_file, i);
for (int i = 0; i < num_threads; i++)
threads[i].join();
}
printf("run successfully\n");
return EXIT_SUCCESS;
}
I have written some codes to load 1025 images with OpenCV to process them;these codes are in two versions :
single thread and multi threads; problem is that the results of codes have confused me; because single thread version is faster than multi threads.
What do you think about it?? what's wrong ?
my codes are below.
#include <opencv2/core.hpp>
#include <opencv2/imgcodecs.hpp>
#include <iostream>
#include "ctpl.h"
using namespace std;
using namespace cv;
#define threaded
void loadImage(int id, int param0) {
stringstream stream;
stream << "/home/me/Desktop/Pics/pic (" << param0 << ").jpg";
Mat x = imread(stream.str(), IMREAD_REDUCED_COLOR_8);
}
int main() {
#ifdef threaded
ctpl::thread_pool p(8);
for (int i = 1; i <= 1025; i++) {
p.push(loadImage,i);
}
// for (int i = 0; i < 1025; ++i) {
// pthread_join(threads[i], NULL);
// }
#else
for (int i = 1; i <= 1025; i++) {
stringstream stream;
stream << "/home/me/Desktop/Pics/pic (" << i << ").jpg";
Mat x = imread(stream.str(), IMREAD_REDUCED_COLOR_8);
}
#endif
return 0;
}
I'm trying to implement the function from listing 5.1 here
but when copying into a buffer with read from a file I just get the same character (Í) for the whole array, where string.txt is a copy and paste from the previous link content.
Here is my code:
#include <iostream>
#include <fstream>
#include <string>
#include <cinttypes>
#include <cstdio>
#include <cstring>
const int block_size = 0x4000; //16KB
int search(char* buffer, int searchLength, char* stringToSearch, int stringToSearchLength) {
char * potentialMatch;
while (searchLength) {
potentialMatch = reinterpret_cast<char *>(memchr(buffer, *stringToSearch, searchLength));
if (potentialMatch == NULL)
break;
if (stringToSearchLength == 1) {
return 1;
} else {
if (!memcmp(potentialMatch + 1, stringToSearch + 1, stringToSearchLength - 1))
return 1;
}
searchLength -= potentialMatch - buffer + 1;
buffer = potentialMatch + 1;
}
return 0;
}
int main(int argc, char* argv[]) {
char *toSearch = "Interpreting Where";
int done = 0;
int found = 0;
char *buffer;
int64_t fileSizeLeft = 0;
std::ifstream myFile("string.txt");
if (!myFile.fail()) {
buffer = new char[block_size];
myFile.seekg(0, std::ios::end); //Get file's size
fileSizeLeft = myFile.tellg();
} else {
std::cout << "Cannot open file" << std::endl;
return 1;
}
int toSearchLength = strlen(toSearch);
int stringLeft = toSearchLength - 1;
int first_time = 1;
while (!done && fileSizeLeft > toSearchLength) {
if (first_time) {
myFile.read(buffer, block_size);
found = search(buffer, block_size, toSearch, toSearchLength);
} else {
memcpy(buffer, buffer + stringLeft, stringLeft);
myFile.read(buffer+stringLeft, fileSizeLeft-stringLeft);
found = search(buffer, block_size, toSearch, toSearchLength);
}
fileSizeLeft = fileSizeLeft - block_size;
first_time = 0;
}
if (found) {
std::cout << "String found" << std::endl;
} else {
std::cout << "String not found" << std::endl;
}
myFile.close();
delete[] buffer;
return 0;
}
I hope you can help me see what I'm doing wrong, thanks!
You are setting myFile's position to ios_base::end with seekg:
myFile.seekg(0, ios::end);
Then trying to read from it:
myFile.read(buffer, block_size);
Clearly no data will be read since myFile is already at ios_base::end. And you'll be reading whatever uninitialized data that was already in buffer
What you probably intended to do was to set your myFile position back to the beginning by doing this before reading:
myFile.seekg(0, ios::beg);