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"""
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)):
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)
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