def train_top_ground_truth_fish_or_no_fish_resnet_network():
"""
Train the top of the extended resnet fish or no fish network.
"""
import network
tl = network.TransferLearningFishOrNoFish(
class_balance_method="batch",
prediction_class_type="single",
data_type="fish_no_fish_ground_truth_cropped")
tl.build('resnet', input_shape=(300, 300, 3), summary=False)
tl.train_top(epochs=100)
def train_top_fish_or_no_fish_network():
"""
Train the top of the extended xception fish or no fish network.
"""
import network
tl = network.TransferLearningFishOrNoFish(
class_balance_method="batch",
prediction_class_type="single",
data_type="fish_no_fish_candidates_cropped")
tl.build('xception', summary=False)
tl.train_top(epochs=70)
def fine_tune_fish_or_no_fish_vgg_network():
"""
Fine-tune the extended inceptionv4 fish or no fish network. To do this, first the top
of the extended inceptionv4 network must have been trained already.
"""
import network
tl = network.TransferLearningFishOrNoFish(
class_balance_method="batch",
prediction_class_type="single",
data_type="fish_no_fish_candidates_cropped")
tl.build('vgg19', input_shape=(300, 300, 3), summary=False)
tl.fine_tune_extended(
epochs=70,
input_weights_name=
"ext_vgg19.toptrained.e060-tloss0.5310-vloss0.5097.hdf5",
n_layers=17)
def fine_tune_ground_truth_fish_or_no_fish_resnet_network():
"""
Fine-tune the extended resnet fish or no fish network. To do this, first the top
of the extended resnet network must have been trained already.
"""
import network
tl = network.TransferLearningFishOrNoFish(
class_balance_method="batch",
prediction_class_type="single",
data_type="fish_no_fish_ground_truth_cropped")
tl.build('resnet', input_shape=(300, 300, 3), summary=False)
tl.fine_tune_extended(
epochs=70,
input_weights_name=
"fishnofish.ground_truth.ext_resnet.toptrained.e041-tloss0.1008-vloss0.0756.hdf5",
n_layers=75)
def fine_tune_fish_or_no_fish_network():
"""
Fine-tune the extended xception fish or no fish network. To do this, first the top
of the extended xception network must have been trained already.
"""
import network
tl = network.TransferLearningFishOrNoFish(
class_balance_method="batch",
prediction_class_type="single",
data_type="fish_no_fish_candidates_cropped")
tl.build('xception', summary=False)
tl.fine_tune_extended(
epochs=70,
input_weights_name=
"fishnofish.ext_xception.toptrained.e001-tloss0.3366-vloss0.2445.hdf5",
n_layers=125)