visualkeras: custom vgg16 example#

An example showing the visualkeras function used by a tf.keras.Model model.

# Authors: The scikit-plots developers
# SPDX-License-Identifier: BSD-3-Clause

Force garbage collection

import gc

gc.collect()

# pip install protobuf==5.29.4
import tensorflow as tf

# Clear any session to reset the state of TensorFlow/Keras
tf.keras.backend.clear_session()

from scikitplot import visualkeras

# create VGG16
image_size = 224
model = tf.keras.models.Sequential()
model.add(tf.keras.layers.InputLayer(shape=(image_size, image_size, 3)))

model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(64, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(64, activation="relu", kernel_size=(3, 3)))
model.add(visualkeras.SpacingDummyLayer())

model.add(tf.keras.layers.MaxPooling2D((2, 2), strides=(2, 2)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(128, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(128, activation="relu", kernel_size=(3, 3)))
model.add(visualkeras.SpacingDummyLayer())

model.add(tf.keras.layers.MaxPooling2D((2, 2), strides=(2, 2)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(256, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(256, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(256, activation="relu", kernel_size=(3, 3)))
model.add(visualkeras.SpacingDummyLayer())

model.add(tf.keras.layers.MaxPooling2D((2, 2), strides=(2, 2)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(512, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(512, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(512, activation="relu", kernel_size=(3, 3)))
model.add(visualkeras.SpacingDummyLayer())

model.add(tf.keras.layers.MaxPooling2D((2, 2), strides=(2, 2)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(512, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(512, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.ZeroPadding2D((1, 1)))
model.add(tf.keras.layers.Conv2D(512, activation="relu", kernel_size=(3, 3)))
model.add(tf.keras.layers.MaxPooling2D())
model.add(visualkeras.SpacingDummyLayer())

model.add(tf.keras.layers.Flatten())

model.add(tf.keras.layers.Dense(4096, activation="relu"))
model.add(tf.keras.layers.Dropout(0.5))
model.add(tf.keras.layers.Dense(4096, activation="relu"))
model.add(tf.keras.layers.Dropout(0.5))
model.add(tf.keras.layers.Dense(1000, activation="softmax"))
# model.summary()

Now visualize the model!

from collections import defaultdict

color_map = defaultdict(dict)
color_map[tf.keras.layers.Conv2D]["fill"] = "orange"
color_map[tf.keras.layers.ZeroPadding2D]["fill"] = "gray"
color_map[tf.keras.layers.Dropout]["fill"] = "pink"
color_map[tf.keras.layers.MaxPooling2D]["fill"] = "red"
color_map[tf.keras.layers.Dense]["fill"] = "green"
color_map[tf.keras.layers.Flatten]["fill"] = "teal"

from PIL import ImageFont

ImageFont.load_default()

<PIL.ImageFont.FreeTypeFont object at 0x7fe1c3a0b410>

img_vgg16 = visualkeras.layered_view(
    model,
    type_ignore=[visualkeras.SpacingDummyLayer],
    # to_file="result_images/vgg16.png",
    save_fig=True,
    save_fig_filename="vgg16.png",
)

img_vgg16_legend = visualkeras.layered_view(
    model,
    type_ignore=[visualkeras.SpacingDummyLayer],
    legend=True,
    font={
        "font_size": 61,
        # 'use_default_font': False,
        # 'font_path': '/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf'
    },
    # to_file="result_images/vgg16_legend.png",
    save_fig=True,
    save_fig_filename="vgg16_legend.png",
)

img_vgg16_spacing_layers = visualkeras.layered_view(
    model,
    type_ignore=[],
    spacing=0,
    # to_file="result_images/vgg16_spacing_layers.png",
    save_fig=True,
    save_fig_filename="vgg16_spacing_layers.png",
)

img_vgg16_type_ignore = visualkeras.layered_view(
    model,
    type_ignore=[
        tf.keras.layers.ZeroPadding2D,
        tf.keras.layers.Dropout,
        tf.keras.layers.Flatten,
        visualkeras.SpacingDummyLayer,
    ],
    # to_file="result_images/vgg16_type_ignore.png",
    save_fig=True,
    save_fig_filename="vgg16_type_ignore.png",
)

img_vgg16_color_map = visualkeras.layered_view(
    model,
    type_ignore=[visualkeras.SpacingDummyLayer],
    color_map=color_map,
    # to_file="result_images/vgg16_color_map.png",
    save_fig=True,
    save_fig_filename="vgg16_color_map.png",
)

img_vgg16_flat = visualkeras.layered_view(
    model,
    type_ignore=[visualkeras.SpacingDummyLayer],
    draw_volume=False,
    # to_file="result_images/vgg16_flat.png",
    save_fig=True,
    save_fig_filename="vgg16_flat.png",
)

img_vgg16_scaling = visualkeras.layered_view(
    model,
    type_ignore=[visualkeras.SpacingDummyLayer],
    # legend=True,
    min_z=1,
    min_xy=1,
    max_z=4096,
    max_xy=4096,
    scale_z=0.5,
    scale_xy=11,
    # font={'font_size': 99},
    # to_file="result_images/vgg16_scaling.png",
    save_fig=True,
    save_fig_filename="vgg16_scaling.png",
)