visualkeras ResNetV2 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()
import tensorflow as tf
# Clear any session to reset the state of TensorFlow/Keras
tf.keras.backend.clear_session()

from scikitplot import visualkeras

model = tf.keras.applications.ResNet50V2(
    include_top=True,
    weights=None,  # "imagenet" or 'path/'
    input_tensor=None,
    input_shape=None,
    pooling=None,
    classes=1000,
    classifier_activation="softmax",
    name="resnet50v2",
)
img_resnet50v2 = visualkeras.layered_view(
  model,
  legend=True,
  show_dimension=True,
  to_file='../result_images/resnet50v2.png',
)
try:
    import matplotlib.pyplot as plt
    plt.imshow(img_resnet50v2)
    plt.axis('off')
    plt.show()
except:
    pass

Tags: model-type: classification model-workflow: model building plot-type: visualkeras domain: neural network level: beginner purpose: showcase

# model = tf.keras.applications.ResNet101V2(
#     include_top=True,
#     weights=None,  # "imagenet" or 'path/'
#     input_tensor=None,
#     input_shape=None,
#     pooling=None,
#     classes=1000,
#     classifier_activation="softmax",
#     name="resnet101v2",
# )
# visualkeras.layered_view(
#   model,
#   legend=True,
#   show_dimension=True,
#   to_file='../result_images/resnet101v2.png',
# )

# model = tf.keras.applications.ResNet152V2(
#     include_top=True,
#     weights=None,  # "imagenet" or 'path/'
#     input_tensor=None,
#     input_shape=None,
#     pooling=None,
#     classes=1000,
#     classifier_activation="softmax",
#     name="resnet152v2",
# )
# visualkeras.layered_view(
#   model,
#   legend=True,
#   show_dimension=True,
#   to_file='../result_images/resnet152v2.png',
# )