sys.path.insert(0, '../')
import libs
import libs_dataset
import models.model_conv_4d05.src.model as Modelconv_4d05
from dats_config import *
'''
create dataset with pairs training testing
labels corresponds to class IDs
for details see libs_dataset/cells_dataset.py
'''
dataset = libs_dataset.CellsDataset(training_files,
training_labels,
testing_files,
testing_labels,
window_size=128,
classes_count=2,
augmentations_count=100)
#train 100 epochs
epoch_count = 100
#cyclic learning rate cheduler
learning_rates = [0.001, 0.001, 0.0001, 0.0001, 0.0001, 0.00001, 0.00001]
train = libs.Train(dataset,
Modelconv_4d05,
batch_size=256,
learning_rates=learning_rates)
train.step_epochs(epoch_count, log_path="../models/model_conv_4d05")
training_files.append(path + "rbc3_data_sim26.dat")
training_labels = []
training_labels.append(0)
training_labels.append(1)
training_labels.append(0)
training_labels.append(1)
#testing dats + labels
testing_files = []
testing_files.append(path + "rbc0_data_sim26.dat")
testing_files.append(path + "rbc1_data_sim26.dat")
testing_files.append(path + "rbc2_data_sim26.dat")
testing_files.append(path + "rbc3_data_sim26.dat")
testing_labels = []
testing_labels.append(0)
testing_labels.append(1)
testing_labels.append(0)
testing_labels.append(1)
'''
create dataset with pairs training testing
labels corresponds to class IDs
for details see libs_dataset/cells_dataset.py
'''
dataset = libs_dataset.CellsDataset(training_files,
training_labels,
testing_files,
testing_labels,
classes_count=2)
