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example.py
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import skimage.data
import numpy
import matplotlib
import NumPyCNN as numpycnn
"""
Convolutional neural network implementation using NumPy.
An article describing this project is titled "Building Convolutional Neural Network using NumPy from Scratch". It is available in these links: https://www.linkedin.com/pulse/building-convolutional-neural-network-using-numpy-from-ahmed-gad/
https://www.kdnuggets.com/2018/04/building-convolutional-neural-network-numpy-scratch.html
It is also translated into Chinese: http://m.aliyun.com/yunqi/articles/585741
The project is tested using Python 3.5.2 installed inside Anaconda 4.2.0 (64-bit)
NumPy version used is 1.14.0
For more info., contact me:
Ahmed Fawzy Gad
KDnuggets: https://www.kdnuggets.com/author/ahmed-gad
LinkedIn: https://www.linkedin.com/in/ahmedfgad
Facebook: https://www.facebook.com/ahmed.f.gadd
"""
# Reading the image
#img = skimage.io.imread("test.jpg")
#img = skimage.data.checkerboard()
img = skimage.data.chelsea()
#img = skimage.data.camera()
# Converting the image into gray.
img = skimage.color.rgb2gray(img)
# First conv layer
#l1_filter = numpy.random.rand(2,7,7)*20 # Preparing the filters randomly.
l1_filter = numpy.zeros((2,3,3))
l1_filter[0, :, :] = numpy.array([[[-1, 0, 1],
[-1, 0, 1],
[-1, 0, 1]]])
l1_filter[1, :, :] = numpy.array([[[1, 1, 1],
[0, 0, 0],
[-1, -1, -1]]])
print("\n**Working with conv layer 1**")
l1_feature_map = numpycnn.conv(img, l1_filter)
print("\n**ReLU**")
l1_feature_map_relu = numpycnn.relu(l1_feature_map)
print("\n**Pooling**")
l1_feature_map_relu_pool = numpycnn.pooling(l1_feature_map_relu, 2, 2)
print("**End of conv layer 1**\n")
# Second conv layer
l2_filter = numpy.random.rand(3, 5, 5, l1_feature_map_relu_pool.shape[-1])
print("\n**Working with conv layer 2**")
l2_feature_map = numpycnn.conv(l1_feature_map_relu_pool, l2_filter)
print("\n**ReLU**")
l2_feature_map_relu = numpycnn.relu(l2_feature_map)
print("\n**Pooling**")
l2_feature_map_relu_pool = numpycnn.pooling(l2_feature_map_relu, 2, 2)
print("**End of conv layer 2**\n")
# Third conv layer
l3_filter = numpy.random.rand(1, 7, 7, l2_feature_map_relu_pool.shape[-1])
print("\n**Working with conv layer 3**")
l3_feature_map = numpycnn.conv(l2_feature_map_relu_pool, l3_filter)
print("\n**ReLU**")
l3_feature_map_relu = numpycnn.relu(l3_feature_map)
print("\n**Pooling**")
l3_feature_map_relu_pool = numpycnn.pooling(l3_feature_map_relu, 2, 2)
print("**End of conv layer 3**\n")
# Graphing results
fig0, ax0 = matplotlib.pyplot.subplots(nrows=1, ncols=1)
ax0.imshow(img).set_cmap("gray")
ax0.set_title("Input Image")
ax0.get_xaxis().set_ticks([])
ax0.get_yaxis().set_ticks([])
matplotlib.pyplot.savefig("in_img.png", bbox_inches="tight")
matplotlib.pyplot.close(fig0)
# Layer 1
fig1, ax1 = matplotlib.pyplot.subplots(nrows=3, ncols=2)
ax1[0, 0].imshow(l1_feature_map[:, :, 0]).set_cmap("gray")
ax1[0, 0].get_xaxis().set_ticks([])
ax1[0, 0].get_yaxis().set_ticks([])
ax1[0, 0].set_title("L1-Map1")
ax1[0, 1].imshow(l1_feature_map[:, :, 1]).set_cmap("gray")
ax1[0, 1].get_xaxis().set_ticks([])
ax1[0, 1].get_yaxis().set_ticks([])
ax1[0, 1].set_title("L1-Map2")
ax1[1, 0].imshow(l1_feature_map_relu[:, :, 0]).set_cmap("gray")
ax1[1, 0].get_xaxis().set_ticks([])
ax1[1, 0].get_yaxis().set_ticks([])
ax1[1, 0].set_title("L1-Map1ReLU")
ax1[1, 1].imshow(l1_feature_map_relu[:, :, 1]).set_cmap("gray")
ax1[1, 1].get_xaxis().set_ticks([])
ax1[1, 1].get_yaxis().set_ticks([])
ax1[1, 1].set_title("L1-Map2ReLU")
ax1[2, 0].imshow(l1_feature_map_relu_pool[:, :, 0]).set_cmap("gray")
ax1[2, 0].get_xaxis().set_ticks([])
ax1[2, 0].get_yaxis().set_ticks([])
ax1[2, 0].set_title("L1-Map1ReLUPool")
ax1[2, 1].imshow(l1_feature_map_relu_pool[:, :, 1]).set_cmap("gray")
ax1[2, 0].get_xaxis().set_ticks([])
ax1[2, 0].get_yaxis().set_ticks([])
ax1[2, 1].set_title("L1-Map2ReLUPool")
matplotlib.pyplot.savefig("L1.png", bbox_inches="tight")
matplotlib.pyplot.close(fig1)
# Layer 2
fig2, ax2 = matplotlib.pyplot.subplots(nrows=3, ncols=3)
ax2[0, 0].imshow(l2_feature_map[:, :, 0]).set_cmap("gray")
ax2[0, 0].get_xaxis().set_ticks([])
ax2[0, 0].get_yaxis().set_ticks([])
ax2[0, 0].set_title("L2-Map1")
ax2[0, 1].imshow(l2_feature_map[:, :, 1]).set_cmap("gray")
ax2[0, 1].get_xaxis().set_ticks([])
ax2[0, 1].get_yaxis().set_ticks([])
ax2[0, 1].set_title("L2-Map2")
ax2[0, 2].imshow(l2_feature_map[:, :, 2]).set_cmap("gray")
ax2[0, 2].get_xaxis().set_ticks([])
ax2[0, 2].get_yaxis().set_ticks([])
ax2[0, 2].set_title("L2-Map3")
ax2[1, 0].imshow(l2_feature_map_relu[:, :, 0]).set_cmap("gray")
ax2[1, 0].get_xaxis().set_ticks([])
ax2[1, 0].get_yaxis().set_ticks([])
ax2[1, 0].set_title("L2-Map1ReLU")
ax2[1, 1].imshow(l2_feature_map_relu[:, :, 1]).set_cmap("gray")
ax2[1, 1].get_xaxis().set_ticks([])
ax2[1, 1].get_yaxis().set_ticks([])
ax2[1, 1].set_title("L2-Map2ReLU")
ax2[1, 2].imshow(l2_feature_map_relu[:, :, 2]).set_cmap("gray")
ax2[1, 2].get_xaxis().set_ticks([])
ax2[1, 2].get_yaxis().set_ticks([])
ax2[1, 2].set_title("L2-Map3ReLU")
ax2[2, 0].imshow(l2_feature_map_relu_pool[:, :, 0]).set_cmap("gray")
ax2[2, 0].get_xaxis().set_ticks([])
ax2[2, 0].get_yaxis().set_ticks([])
ax2[2, 0].set_title("L2-Map1ReLUPool")
ax2[2, 1].imshow(l2_feature_map_relu_pool[:, :, 1]).set_cmap("gray")
ax2[2, 1].get_xaxis().set_ticks([])
ax2[2, 1].get_yaxis().set_ticks([])
ax2[2, 1].set_title("L2-Map2ReLUPool")
ax2[2, 2].imshow(l2_feature_map_relu_pool[:, :, 2]).set_cmap("gray")
ax2[2, 2].get_xaxis().set_ticks([])
ax2[2, 2].get_yaxis().set_ticks([])
ax2[2, 2].set_title("L2-Map3ReLUPool")
matplotlib.pyplot.savefig("L2.png", bbox_inches="tight")
matplotlib.pyplot.close(fig2)
# Layer 3
fig3, ax3 = matplotlib.pyplot.subplots(nrows=1, ncols=3)
ax3[0].imshow(l3_feature_map[:, :, 0]).set_cmap("gray")
ax3[0].get_xaxis().set_ticks([])
ax3[0].get_yaxis().set_ticks([])
ax3[0].set_title("L3-Map1")
ax3[1].imshow(l3_feature_map_relu[:, :, 0]).set_cmap("gray")
ax3[1].get_xaxis().set_ticks([])
ax3[1].get_yaxis().set_ticks([])
ax3[1].set_title("L3-Map1ReLU")
ax3[2].imshow(l3_feature_map_relu_pool[:, :, 0]).set_cmap("gray")
ax3[2].get_xaxis().set_ticks([])
ax3[2].get_yaxis().set_ticks([])
ax3[2].set_title("L3-Map1ReLUPool")
matplotlib.pyplot.savefig("L3.png", bbox_inches="tight")
matplotlib.pyplot.close(fig3)