""" Copyright (c) 2017, Gavin Weiguang Ding All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ import os import numpy as np import matplotlib.pyplot as plt plt.rcdefaults() from matplotlib.lines import Line2D from matplotlib.patches import Rectangle from matplotlib.patches import Circle NumDots = 4 NumConvMax = 8 NumFcMax = 20 White = 1. Light = 0.7 Medium = 0.5 Dark = 0.3 Darker = 0.15 Black = 0. def add_layer(patches, colors, size=(24, 24), num=5, top_left=[0, 0], loc_diff=[3, -3], ): # add a rectangle top_left = np.array(top_left) loc_diff = np.array(loc_diff) loc_start = top_left - np.array([0, size[0]]) for ind in range(num): patches.append(Rectangle(loc_start + ind * loc_diff, size[1], size[0])) if ind % 2: colors.append(Medium) else: colors.append(Light) def add_layer_with_omission(patches, colors, size=(24, 24), num=5, num_max=8, num_dots=4, top_left=[0, 0], loc_diff=[3, -3], ): # add a rectangle top_left = np.array(top_left) loc_diff = np.array(loc_diff) loc_start = top_left - np.array([0, size[0]]) this_num = min(num, num_max) start_omit = (this_num - num_dots) // 2 end_omit = this_num - start_omit start_omit -= 1 for ind in range(this_num): if (num > num_max) and (start_omit < ind < end_omit): omit = True else: omit = False if omit: patches.append( Circle(loc_start + ind * loc_diff + np.array(size) / 2, 0.5)) else: patches.append(Rectangle(loc_start + ind * loc_diff, size[1], size[0])) if omit: colors.append(Black) elif ind % 2: colors.append(Medium) else: colors.append(Light) def add_mapping(patches, colors, start_ratio, end_ratio, patch_size, ind_bgn, top_left_list, loc_diff_list, num_show_list, size_list): start_loc = top_left_list[ind_bgn] \ + (num_show_list[ind_bgn] - 1) * np.array(loc_diff_list[ind_bgn]) \ + np.array([start_ratio[0] * (size_list[ind_bgn][1] - patch_size[1]), - start_ratio[1] * (size_list[ind_bgn][0] - patch_size[0])] ) end_loc = top_left_list[ind_bgn + 1] \ + (num_show_list[ind_bgn + 1] - 1) * np.array( loc_diff_list[ind_bgn + 1]) \ + np.array([end_ratio[0] * size_list[ind_bgn + 1][1], - end_ratio[1] * size_list[ind_bgn + 1][0]]) patches.append(Rectangle(start_loc, patch_size[1], -patch_size[0])) colors.append(Dark) patches.append(Line2D([start_loc[0], end_loc[0]], [start_loc[1], end_loc[1]])) colors.append(Darker) patches.append(Line2D([start_loc[0] + patch_size[1], end_loc[0]], [start_loc[1], end_loc[1]])) colors.append(Darker) patches.append(Line2D([start_loc[0], end_loc[0]], [start_loc[1] - patch_size[0], end_loc[1]])) colors.append(Darker) patches.append(Line2D([start_loc[0] + patch_size[1], end_loc[0]], [start_loc[1] - patch_size[0], end_loc[1]])) colors.append(Darker) def label(xy, text, xy_off=[0, 4]): plt.text(xy[0] + xy_off[0], xy[1] + xy_off[1], text, family='sans-serif', size=8) if __name__ == '__main__': fc_unit_size = 2 layer_width = 40 flag_omit = True patches = [] colors = [] fig, ax = plt.subplots() ############################ # conv layers size_list = [(32, 32), (18, 18), (10, 10), (6, 6), (4, 4)] num_list = [3, 32, 32, 48, 48] x_diff_list = [0, layer_width, layer_width, layer_width, layer_width] text_list = ['Inputs'] + ['Feature\nmaps'] * (len(size_list) - 1) loc_diff_list = [[3, -3]] * len(size_list) num_show_list = list(map(min, num_list, [NumConvMax] * len(num_list))) top_left_list = np.c_[np.cumsum(x_diff_list), np.zeros(len(x_diff_list))] for ind in range(len(size_list)-1,-1,-1): if flag_omit: add_layer_with_omission(patches, colors, size=size_list[ind], num=num_list[ind], num_max=NumConvMax, num_dots=NumDots, top_left=top_left_list[ind], loc_diff=loc_diff_list[ind]) else: add_layer(patches, colors, size=size_list[ind], num=num_show_list[ind], top_left=top_left_list[ind], loc_diff=loc_diff_list[ind]) label(top_left_list[ind], text_list[ind] + '\n{}@{}x{}'.format( num_list[ind], size_list[ind][0], size_list[ind][1])) ############################ # in between layers start_ratio_list = [[0.4, 0.5], [0.4, 0.8], [0.4, 0.5], [0.4, 0.8]] end_ratio_list = [[0.4, 0.5], [0.4, 0.8], [0.4, 0.5], [0.4, 0.8]] patch_size_list = [(5, 5), (2, 2), (5, 5), (2, 2)] ind_bgn_list = range(len(patch_size_list)) text_list = ['Convolution', 'Max-pooling', 'Convolution', 'Max-pooling'] for ind in range(len(patch_size_list)): add_mapping( patches, colors, start_ratio_list[ind], end_ratio_list[ind], patch_size_list[ind], ind, top_left_list, loc_diff_list, num_show_list, size_list) label(top_left_list[ind], text_list[ind] + '\n{}x{} kernel'.format( patch_size_list[ind][0], patch_size_list[ind][1]), xy_off=[26, -65] ) ############################ # fully connected layers size_list = [(fc_unit_size, fc_unit_size)] * 3 num_list = [768, 500, 2] num_show_list = list(map(min, num_list, [NumFcMax] * len(num_list))) x_diff_list = [sum(x_diff_list) + layer_width, layer_width, layer_width] top_left_list = np.c_[np.cumsum(x_diff_list), np.zeros(len(x_diff_list))] loc_diff_list = [[fc_unit_size, -fc_unit_size]] * len(top_left_list) text_list = ['Hidden\nunits'] * (len(size_list) - 1) + ['Outputs'] for ind in range(len(size_list)): if flag_omit: add_layer_with_omission(patches, colors, size=size_list[ind], num=num_list[ind], num_max=NumFcMax, num_dots=NumDots, top_left=top_left_list[ind], loc_diff=loc_diff_list[ind]) else: add_layer(patches, colors, size=size_list[ind], num=num_show_list[ind], top_left=top_left_list[ind], loc_diff=loc_diff_list[ind]) label(top_left_list[ind], text_list[ind] + '\n{}'.format( num_list[ind])) text_list = ['Flatten\n', 'Fully\nconnected', 'Fully\nconnected'] for ind in range(len(size_list)): label(top_left_list[ind], text_list[ind], xy_off=[-10, -65]) ############################ for patch, color in zip(patches, colors): patch.set_color(color * np.ones(3)) if isinstance(patch, Line2D): ax.add_line(patch) else: patch.set_edgecolor(Black * np.ones(3)) ax.add_patch(patch) plt.tight_layout() plt.axis('equal') plt.axis('off') plt.show() fig.set_size_inches(8, 2.5) fig_dir = './' fig_ext = '.png' fig.savefig(os.path.join(fig_dir, 'convnet_fig' + fig_ext), bbox_inches='tight', pad_inches=0)