MXNet Sample

MXNet Sample

  1. import pickle
  2. import numpy as np
  3.  
  4. def cos_curve(x):
  5.     return 0.25 * np.sin(2 * x * np.pi + 0.5 * np.pi) + 0.5
  6.  
  7. np.random.seed(123)
  8. samples = []
  9. labels = []
  10.  
  11. sample_density = 50
  12. for i in range(sample_density):
  13.     x1, x2 = np.random.random(2)
  14.  
  15.     bound = cos_curve(x1)
  16.  
  17.     if bound - 0.1 < x2 <= bound + 0.1:
  18.         continue
  19.     else:
  20.         samples.append((x1, x2))
  21.  
  22.         if x2 > bound:
  23.             labels.append(1)
  24.         else:
  25.             labels.append(0)
  26.  
  27. with open('data.pkl', 'wb') as f:
  28.     pickle.dump((samples, labels), f)
  29.  
  30. import matplotlib.pyplot as plt
  31.  
  32. for i, sample in enumerate(samples):
  33.     plt.plot(sample[0], sample[1], 'o' if labels[i] else '^',
  34.              mec='r' if labels[i] else 'b',
  35.              mfc='none',
  36.              markersize=10)
  37. x1 = np.linspace(0, 1)
  38. plt.plot(x1, cos_curve(x1), 'k--')
  39. plt.show()
  40.  
  41. #
  42.  
  43. import numpy as np
  44. import mxnet as mx
  45.  
  46. data = mx.sym.Variable('data')
  47.  
  48. fc1 = mx.sym.FullyConnected(data=data, name='fc1', num_hidden=2)
  49.  
  50. sigmoid1 = mx.sym.Activation(data=fc1, name='sigmoid1', act_type='sigmoid')
  51.  
  52. fc2 = mx.sym.FullyConnected(data=sigmoid1, name='fc2', num_hidden=2)
  53.  
  54. mlp = mx.sym.SoftmaxOutput(data=fc2, name='softmax')
  55.  
  56. shape = {'data': (2,)}
  57. mlp_dot = mx.viz.plot_network(symbol=mlp, shape=shape)
  58. mlp_dot.render('simple_mlp.gv', view=True)
  59.  
  60. #
  61.  
  62. import pickle
  63. import logging
  64.  
  65. with open('data.pkl', 'rb') as f:
  66.     samples, labels = pickle.load(f)
  67.  
  68. logging.getLogger().setLevel(logging.DEBUG)
  69.  
  70. batch_size = len(labels)
  71. samples = np.array(samples)
  72. labels = np.array(labels)
  73.  
  74. train_iter = mx.io.NDArrayIter(samples, labels, batch_size)
  75.  
  76. model = mx.model.FeedForward.create(
  77.     symbol=mlp,
  78.     X=train_iter,
  79.     num_epoch=1000,
  80.     learning_rate=0.1,
  81.     momentum=0.99
  82. )
  83. '''
  84. model = mx.model.FeedForward(
  85.     symbol=mlp,
  86.     num_epoch=1000,
  87.     learning_rate=0.1
  88.     momentum=0.99
  89. )
  90. model.fit(X=train_iter)
  91. '''
  92. print(model.predict(mx.nd.array([[0.5, 0.5]])))
  93.  
  94. #
  95.  
  96. import matplotlib.pyplot as plt
  97. from mpl_toolkits.mplot3d import Axes3D
  98.  
  99. X = np.arange(0, 1.05, 0.05)
  100. Y = np.arange(0, 1.05, 0.05)
  101. X, Y = np.meshgrid(X, Y)
  102.  
  103. grids = mx.nd.array([[X[i][j], Y[i][j]] for i in range(X.shape[0]) for j in range(X.shape[1])])
  104.  
  105. grid_probs = model.predict(grids)[:, 1].reshape(X.shape)
  106.  
  107. fig = plt.figure('Sample Surface')
  108. ax = fig.gca(projection='3d')
  109.  
  110. ax.plot_surface(X, Y, grid_probs, alpha=0.15, color='k', rstride=2, cstride=2, lw=0.5)
  111.  
  112. samples0 = samples[labels==0]
  113. samples0_probs = model.predict(samples0)[:, 1]
  114. samples1 = samples[labels==1]
  115. samples1_probs = model.predict(samples1)[:, 1]
  116.  
  117. ax.scatter(samples0[:, 0], samples0[:, 1], samples0_probs, c='r', marker='o', s=50)
  118. ax.scatter(samples1[:, 0], samples1[:, 1], samples1_probs, c='b', marker='^', s=50)
  119.  
  120. plt.show()


Matplotlib RGB & OpenCV BGR

Matplotlib RGB & OpenCV BGR

  1. import matplotlib.pyplot as plt
  2. import numpy as np
  3. import cv2
  4.  
  5. img = np.array([
  6.     [[255, 0, 0], [0, 255, 0], [0, 0, 255]],
  7.     [[255, 255, 0], [255, 0, 255], [0, 255, 255]],
  8.     [[255, 255, 255], [128, 128, 128], [0, 0, 0]],
  9. ], dtype=np.uint8)
  10.  
  11. plt.imsave('img_pyplot.png', img)
  12. cv2.imwrite('img_cv2.jpg', img)


Matplotlib 3D Example 2 : Python

3D Example 2

  1. import matplotlib.pyplot as plt
  2. import numpy as np
  3. from mpl_toolkits.mplot3d import Axes3D
  4.  
  5. np.random.seed(42)
  6.  
  7. n_samples = 500
  8. dim = 3
  9.  
  10. samples = np.random.multivariate_normal(
  11.     np.zeros(dim),
  12.     np.eye(dim),
  13.     n_samples
  14. )
  15.  
  16. for i in range(samples.shape[0]) :
  17.     r = np.power(np.random.random(), 1.0 / 3.0)
  18.     samples[i] *= r / np.linalg.norm(samples[i])
  19.  
  20. upper_samples = []
  21. lower_samples = []
  22. for x, y, z in samples:
  23.     if z > 3 * x + 2 * y - 1:
  24.         upper_samples.append((x, y, z))
  25.     else:
  26.         lower_samples.append((x, y, z))
  27.  
  28. fig = plt.figure('3D scatter plot')
  29. ax = fig.add_subplot(111, projection='3d')
  30. uppers = np.array(upper_samples)
  31. lowers = np.array(lower_samples)
  32.  
  33. ax.scatter(uppers[:, 0], uppers[:, 1], uppers[:, 2], c='r', marker='o')
  34. ax.scatter(uppers[:, 0], uppers[:, 1], uppers[:, 2], c='g', marker='^')
  35.  
  36. plt.show()

Matplotlib 3D Example : Python

3D Example

  1. import matplotlib.pyplot as plt
  2. import numpy as np
  3. from mpl_toolkits.mplot3d import Axes3D
  4.  
  5. np.random.seed(42)
  6.  
  7. n_grids = 51
  8. c = n_grids / 2
  9. nf = 2
  10.  
  11. x = np.linspace(0, 1, n_grids)
  12. y = np.linspace(0, 1, n_grids)
  13. X, Y = np.meshgrid(x, y)
  14.  
  15. spectrum = np.zeros((n_grids, n_grids), dtype=np.complex)
  16. noise = [np.complex(x, y) for x, y in np.random.uniform(-1, 1, ((2 * nf + 1) ** 2 / 2, 2))]
  17. noisy_block = np.concatenate((noise, [0j], np.conjugate(noise[:: -1])))
  18. spectrum[c - nf: c + nf + 1, c - nf: c + nf + 1] = noisy_block.reshape((2 * nf + 1, 2 * nf + 1))
  19. Z = np.real(np.fft.ifft2(np.fft.ifftshift(spectrum)))
  20.  
  21. fig = plt.figure('3D surface & wire')
  22. ax = fig.add_subplot(1, 2, 1, projection='3d')
  23. ax.plot_surface(X, Y, Z, alpha=0.7, cmap='jet', rstride=1, cstride=1, lw=0)
  24.  
  25. ax = fig.add_subplot(1, 2, 2, projection='3d')
  26. ax.plot_wireframe(X, Y, Z, rstride=3, cstride=3, lw=0.5)
  27.  
  28. plt.show()

Matplotlib 2D Example : Python

2D Example

  1. import numpy as np
  2. import matplotlib as mpl
  3. import matplotlib.pyplot as plt
  4.  
  5. mpl.rcParams['xtick.labelsize'] = 24
  6. mpl.rcParams['ytick.labelsize'] = 24
  7. np.random.seed(42)
  8.  
  9. x = np.linspace(0, 5, 100)
  10. y = 2 * np.sin(x) + 0.3 * x ** 2
  11. y_data = y + np.random.normal(scale=0.3, size=100)
  12. plt.figure('data')
  13. plt.plot(x, y_data, '.')
  14.  
  15. plt.figure('model')
  16. plt.plot(x, y)
  17.  
  18. plt.figure('data & model')
  19. plt.plot(x, y, 'k', lw=3)
  20. plt.scatter(x, y_data)
  21.  
  22. plt.savefig('result.png')
  23.  
  24. plt.show()



CMake & Arm Cross compilation based Windows systems (Visual Studio)

CMakeLists.txt

  1. cmake_minimum_required(VERSION 3.12)
  2. project(network_information)
  3.  
  4. SET(CMAKE_SYSTEM_NAME Linux)
  5.  
  6. add_definitions("-std=c++17")
  7.  
  8. # specify the cross compiler
  9. SET(CMAKE_C_COMPILER   arm-linux-gnueabihf-gcc)
  10. SET(CMAKE_CXX_COMPILER arm-linux-gnueabihf-g++)
  11.  
  12. if(${CMAKE_HOST_SYSTEM_NAME} MATCHES "Windows")
  13.     set(BOOST_ROOT "C:/MinGW/msys/1.0/home/d/boost_1_68_0")
  14. else()
  15.     set(BOOST_ROOT /root/Downloads/boost_1_68_0)
  16. endif()
  17.  
  18. set(Boost_USE_STATIC_LIBS ON)
  19. set(Boost_USE_MULTITHREADED ON)
  20.  
  21. include_directories(sdk/inc)
  22. link_directories("sdk/lib")
  23.  
  24. add_executable(network_information
  25. 		network_information.cpp
  26. 		)
  27. TARGET_LINK_LIBRARIES(network_information "-lpthread" "-ldl" "-lpos" "-lrt" "-lpng" "-liconv" "-lfreetype" "-lz")

GNUlinux_config.cmake

  1. set(GNULINUX_PLATFORM ON)
  2. set(CMAKE_SYSTEM_NAME "Linux")
  3. set(CMAKE_SYSTEM_PROCESSOR "arm")
  4.  
  5. if(NOT DEFINED ENV{NE10_LINUX_TARGET_ARCH})
  6.    set(NE10_LINUX_TARGET_ARCH "armv7")
  7. else()
  8.    set(NE10_LINUX_TARGET_ARCH $ENV{NE10_LINUX_TARGET_ARCH})
  9. endif()
  10.  
  11. if(NE10_LINUX_TARGET_ARCH STREQUAL "armv7")
  12.    set(CMAKE_C_COMPILER arm-linux-gnueabihf-gcc)
  13.    set(CMAKE_CXX_COMPILER arm-linux-gnueabihf-g++)
  14.    set(CMAKE_ASM_COMPILER arm-linux-gnueabihf-as)
  15.    find_program(CMAKE_AR NAMES "arm-linux-gnueabihf-ar")
  16.    find_program(CMAKE_RANLIB NAMES "arm-linux-gnueabihf-ranlib")
  17. elseif(NE10_LINUX_TARGET_ARCH STREQUAL "aarch64")
  18.    set(CMAKE_C_COMPILER aarch64-linux-gnu-gcc)
  19.    set(CMAKE_CXX_COMPILER aarch64-linux-gnu-g++)
  20.    set(CMAKE_ASM_COMPILER aarch64-linux-gnu-as)
  21.    find_program(CMAKE_AR NAMES "aarch64-linux-gnu-ar")
  22.    find_program(CMAKE_RANLIB NAMES "aarch64-linux-gnu-ranlib")
  23. endif()
  24.  
  25. mark_as_advanced(CMAKE_AR)
  26. mark_as_advanced(CMAKE_RANLIB)

CMakeSettings.json

  1. {
  2.   "configurations": [
  3.     {
  4.       "environments": [
  5.         {
  6.           "MINGW64_ROOT": "C:\\MinGW\\msys\\1.0\\home\\d\\gcc-linaro-7.3.1-2018.05-i686-mingw32_arm-linux-gnueabihf",
  7.           "BIN_ROOT": "${env.MINGW64_ROOT}\\bin",
  8.           "FLAVOR": "x86_64-w64-mingw32",
  9.           "TOOLSET_VERSION": "7.3.0",
  10.           "PATH": "${env.MINGW64_ROOT}\\bin;${env.MINGW64_ROOT}\\..\\usr\\local\\bin;${env.MINGW64_ROOT}\\..\\usr\\bin;${env.MINGW64_ROOT}\\..\\bin;${env.PATH}",
  11.           "INCLUDE": "${env.INCLUDE};${env.MINGW64_ROOT}\\include\\c++\\${env.TOOLSET_VERSION};${env.MINGW64_ROOT}\\include\\c++\\${env.TOOLSET_VERSION}\\tr1;${env.MINGW64_ROOT}\\include\\c++\\${env.TOOLSET_VERSION}\\${env.FLAVOR}",
  12.           "environment": "mingw_64"
  13.         }
  14.       ],
  15.       "name": "Mingw64-Release",
  16.       "generator": "Ninja",
  17.       "configurationType": "Release",
  18.       "inheritEnvironments": [
  19.         "mingw_64"
  20.       ],
  21.       "buildRoot": "${env.USERPROFILE}\\CMakeBuilds\\${workspaceHash}\\build\\${name}",
  22.       "installRoot": "${env.USERPROFILE}\\CMakeBuilds\\${workspaceHash}\\install\\${name}",
  23.       "cmakeCommandArgs": "",
  24.       "buildCommandArgs": "-v",
  25.       "ctestCommandArgs": "",
  26.       "intelliSenseMode": "linux-gcc-x64",
  27.       "variables": [
  28.         {
  29.           "name": "CMAKE_TOOLCHAIN_FILE",
  30.           "value": "GNUlinux_config.cmake"
  31.         },
  32.         {
  33.           "name": "CMAKE_C_COMPILER",
  34.           "value": "${env.BIN_ROOT}\\arm-linux-gnueabihf-gcc.exe"
  35.         },
  36.         {
  37.           "name": "CMAKE_CXX_COMPILER",
  38.           "value": "${env.BIN_ROOT}\\arm-linux-gnueabihf-g++.exe"
  39.         }
  40.       ]
  41.     }
  42.   ]
  43. }

CMake & Arm Cross compilation based Windows systems (CLion)

CMakeLists.txt

  1. cmake_minimum_required(VERSION 3.12)
  2. project(untitled1)
  3.  
  4. SET(CMAKE_SYSTEM_NAME Linux)
  5.  
  6. add_definitions("-std=c++17")
  7.  
  8. SET(CMAKE_C_COMPILER   arm-linux-gnueabihf-gcc)
  9. SET(CMAKE_CXX_COMPILER arm-linux-gnueabihf-g++)
  10.  
  11. if(${CMAKE_HOST_SYSTEM_NAME} MATCHES "Windows")
  12.     set(BOOST_ROOT "C:/MinGW/msys/1.0/home/d/boost_1_68_0")
  13. else()
  14.     set(BOOST_ROOT /root/Downloads/boost_1_68_0)
  15. endif()
  16.  
  17. set(Boost_USE_STATIC_LIBS ON)
  18. set(Boost_USE_MULTITHREADED ON)
  19.  
  20. find_package(Boost COMPONENTS regex system date_time timer REQUIRED)
  21. if(Boost_FOUND)
  22.     include_directories(${Boost_INCLUDE_DIRS})
  23.     link_directories("${Boost_INCLUDE_DIRS}/stage/lib")
  24.     include_directories(sdk/inc)
  25.     link_directories("sdk/lib")
  26.     MESSAGE( STATUS "Boost_INCLUDE_DIRS = ${Boost_INCLUDE_DIRS}.")
  27.     MESSAGE( STATUS "Boost_LIBRARIES = ${Boost_LIBRARIES}.")
  28.     MESSAGE( STATUS "Boost_LIB_VERSION = ${Boost_LIB_VERSION}.")
  29.  
  30.     add_executable(untitled1 main.cpp)
  31.  
  32.     TARGET_LINK_LIBRARIES(untitled1 ${Boost_LIBRARIES} "-lpthread" "-lpos" "-lrt" "-lpng" "-liconv" "-lfreetype" "-lz" "-l:libboost_system.a")
  33. endif()

GNUlinux_config.cmake

  1. set(GNULINUX_PLATFORM ON)
  2. set(CMAKE_SYSTEM_NAME "Linux")
  3. set(CMAKE_SYSTEM_PROCESSOR "arm")
  4.  
  5. if(NOT DEFINED ENV{NE10_LINUX_TARGET_ARCH})
  6.    set(NE10_LINUX_TARGET_ARCH "armv7")
  7. else()
  8.    set(NE10_LINUX_TARGET_ARCH $ENV{NE10_LINUX_TARGET_ARCH})
  9. endif()
  10.  
  11. if(NE10_LINUX_TARGET_ARCH STREQUAL "armv7")
  12.    set(CMAKE_C_COMPILER arm-linux-gnueabihf-gcc)
  13.    set(CMAKE_CXX_COMPILER arm-linux-gnueabihf-g++)
  14.    set(CMAKE_ASM_COMPILER arm-linux-gnueabihf-as)
  15.    find_program(CMAKE_AR NAMES "arm-linux-gnueabihf-ar")
  16.    find_program(CMAKE_RANLIB NAMES "arm-linux-gnueabihf-ranlib")
  17. elseif(NE10_LINUX_TARGET_ARCH STREQUAL "aarch64")
  18.    set(CMAKE_C_COMPILER aarch64-linux-gnu-gcc)
  19.    set(CMAKE_CXX_COMPILER aarch64-linux-gnu-g++)
  20.    set(CMAKE_ASM_COMPILER aarch64-linux-gnu-as)
  21.    find_program(CMAKE_AR NAMES "aarch64-linux-gnu-ar")
  22.    find_program(CMAKE_RANLIB NAMES "aarch64-linux-gnu-ranlib")
  23. endif()
  24.  
  25. mark_as_advanced(CMAKE_AR)
  26. mark_as_advanced(CMAKE_RANLIB)

The Most Important Thing on Windows

cmake -DCMAKE_TOOLCHAIN_FILE=GNUlinux_config.cmake ..

boost::program_options demo

A Simple Demo

  1. //
  2. // Created by Water on 2018/6/9.
  3. //
  4.  
  5. #include <iostream>
  6. #include <string>
  7. #include <boost/program_options.hpp>
  8. namespace  bpo = boost::program_options;
  9.  
  10. int main(int argc, char const *argv[])
  11. {
  12.     bpo::options_description opts("all options");
  13.     bpo::variables_map vm;
  14.  
  15.     opts.add_options()
  16.             ("filename", bpo::value<std::string>(), "the file name which want to be found")
  17.             ("help", "this is a program to find a specified file");
  18.  
  19.     try{
  20.         bpo::store(bpo::parse_command_line(argc, argv, opts), vm);
  21.     }
  22.     catch(...){
  23.         std::cout << "undefined option!\n";
  24.         return 0;
  25.     }
  26.  
  27.     if(vm.count("help") ){
  28.         std::cout << opts << std::endl;
  29.     }
  30.     if(vm.count("filename") ){
  31.         std::cout << "find " << vm["filename"].as<std::string>() << std::endl;
  32.     }
  33.     if(vm.empty() ){
  34.         std::cout << "no options found \n";
  35.     }
  36.     return 0;
  37. }

Test

How to Set Default Value

  1. //
  2. // Created by Water on 2018/6/9.
  3. //
  4.  
  5. #include <iostream>
  6. #include <vector>
  7. #include <string>
  8. #include <boost/program_options.hpp>
  9. namespace bpo = boost::program_options;
  10.  
  11. int main(int argc, char const *argv[])
  12. {
  13.     std::vector<std::string> v_para;
  14.     std::string port;
  15.     int baud = 0;
  16.     int timeout = 0;
  17.     bpo::options_description opt("all options");
  18.  
  19.     opt.add_options()
  20.             ("v_para,v", bpo::value<std::vector<std::string> >()->multitoken(), "Serial v_para")
  21.             ("port,p", bpo::value<std::string>(&port)->default_value("COM1"), "Serial Port")
  22.             ("baud,b", bpo::value<int>(&baud)->default_value(115200), "Serial Baud")
  23.             ("timeout,t", bpo::value<int>(&timeout)->default_value(5000), "Timeout")
  24.             ("help", "a demo ( default value )");
  25.  
  26.     bpo::variables_map vm;
  27.  
  28.     try{
  29.         bpo::store(parse_command_line(argc, argv, opt), vm);
  30.     }
  31.     catch(...){
  32.         std::cout << "undefined option!\n";
  33.         return 0;
  34.     }
  35.  
  36.     bpo::notify(vm);
  37.  
  38.     if(vm.count("help") ){
  39.         std::cout << opt << std::endl;
  40.         return 0;
  41.     }
  42.     if(vm.count("v_para") ){
  43.         std::cout << "v_para:";
  44.         for(auto& str : vm["v_para"].as<std::vector<std::string> >() )
  45.             std::cout << str << " ";
  46.         std::cout << std::endl;
  47.     }
  48.     std::cout << "port:" << port << std::endl;
  49.     std::cout << "baud:" << baud << std::endl;
  50.     std::cout << "timeout:" << timeout << std::endl;
  51.     return 0;
  52. }

Test

Apache Axis2/C Installation Guide (Windows)

First

http://archive.apache.org/dist/ws/axis2/c/1_6_0/axis2c-bin-1.6.0-win32.zip
ftp://ftp.zlatkovic.com/libxml/libxml2-2.7.8.win32.zip
ftp://ftp.zlatkovic.com/libxml/iconv-1.9.2.win32.zip
ftp://ftp.zlatkovic.com/libxml/zlib-1.2.5.win32.zip
http://archive.apache.org/dist/httpd/binaries/win32/httpd-2.2.25-win32-x86-openssl-0.9.8y.msi

Install Axis2/C

  1. Extract the binary distribution to a folder of your choice.(example: C:\axis2c-bin-1.6.0-win32)
  2. Copy the iconv.dll, libxml2.dll and zlib1.dll to C:\axis2c-bin-1.6.0-win32\lib
  3. Set the variable AXIS2C_HOME to the deploy folder (C:\axis2c-bin-1.6.0-win32)
  4. Add the path to lib directory to the PATH variable (%AXIS2C_HOME%\lib)

Install Apache 2.2

  1. Copy C:\axis2c-bin-1.6.0-win32\lib\mod_axis2.dll C:\Apache22\modules\mod_axis2.so
  2. Edit the Apache2’s configuration file (generally httpd.conf) and add the following directives
  3. LoadModule axis2_module modules/mod_axis2.so
    Axis2RepoPath C:/axis2c-bin-1.6.0-win32
    Axis2LogFile C:/axis2c-bin-1.6.0-win32/logs
    Axis2MaxLogFileSize 40
    Axis2LogLevel warn
  4. Restart apache2 and test whether mod_axis2 module is loaded by typing the URL http://localhost/axis2/services in your Web browser