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)