Feature Map Visualization

#Load the model
model = VGG16()

# Summary of the model
model.summary()

--


for layer in model.layers:
    
    if 'conv' not in layer.name:
        continue    
    filters , bias = layer.get_weights()
    print(layer.name , filters.shape)

--

# retrieve weights from the second hidden layer
filters , bias = model.layers[1].get_weights()

--

# normalize filter values to 0-1 so we can visualize them
f_min, f_max = filters.min(), filters.max()
filters = (filters - f_min) / (f_max - f_min)

--

from matplotlib import pyplot

n_filters =6
ix=1
fig = pyplot.figure(figsize=(20,15))
for i in range(n_filters):
    # get the filters
    f = filters[:,:,:,i]
    for j in range(3):
        # subplot for 6 filters and 3 channels
        pyplot.subplot(n_filters,3,ix)
        pyplot.imshow(f[:,:,j] ,cmap='gray')
        ix+=1
#plot the filters 
pyplot.show()

--

for i in range(len(model.layers)):
    layer = model.layers[i]
    if 'conv' not in layer.name:
        continue    
    print(i , layer.name , layer.output.shape)

--

model = Model(inputs=model.inputs , outputs=model.layers[1].output)

--

image = load_img("C:/Users/mnis9/Seal Eng Image/CV-gpu/All images/Image508.jpg" , target_size=(224,224))

# convert the image to an array
image = img_to_array(image)
# expand dimensions so that it represents a single 'sample'
image = expand_dims(image, axis=0)

--

image = preprocess_input(image)

--

#calculating features_map
features = model.predict(image)

fig = pyplot.figure(figsize=(20,15))
for i in range(1,features.shape[3]+1):

    pyplot.subplot(8,8,i)
    pyplot.imshow(features[0,:,:,i-1] , cmap='gray')
    
pyplot.show()

--

model2 = VGG16()

--

blocks = [ 2, 5 , 9 , 13 , 17]
outputs = [model2.layers[i].output for i in blocks]

model2 = Model( inputs= model2.inputs, outputs = outputs)

--

feature_map = model2.predict(image)

for i,fmap in zip(blocks,feature_map):
    fig = pyplot.figure(figsize=(20,15))
    #https://stackoverflow.com/a/12444777
    fig.suptitle("BLOCK_{}".format(i) , fontsize=20)
    for i in range(1,features.shape[3]+1):

        pyplot.subplot(8,8,i)
        pyplot.imshow(fmap[0,:,:,i-1] , cmap='gray')
    
pyplot.show()