import CNN as cnn
# Load image
img = skimage.data.chelsea()
#img = skimage.data.camera()
# Converting the image into gray.
img = skimage.color.rgb2gray(img)
# 1st convolution layer
l1Filter = numpy.zeros((2, 3, 3))
l1Filter[0, :, :] = numpy.array([[[-1, 0, 1], [-1, 0, 1], [-1, 0, 1]]])
l1Filter[1, :, :] = numpy.array([[[1, 1, 1], [0, 0, 0], [-1, -1, -1]]])
print("\nWorking with conv layer 1")
l1FeatureMap = cnn.Conv(img, l1Filter)
print("\nReLU")
l1FeatureMapRelu = cnn.Relu(l1FeatureMap)
print("\nPooling")
l1FeatureMapReluPool = cnn.Pooling(l1FeatureMapRelu, 2, 2)
print("End of conv layer 1\n")
# 2nd convolution layer
l2Filter = numpy.random.rand(3, 5, 5, l1FeatureMapReluPool.shape[-1])
print("\nWorking with conv layer 2")
l2FeatureMap = cnn.Conv(l1FeatureMapReluPool, l2Filter)
print("\nReLU")
l2FeatureMapRelu = cnn.Relu(l2FeatureMap)
print("\nPooling")
