__author__ = 'Ayush Singh' from model import load_data, NeuralNetwork input_size = 192 * 320 data_path = "training_data/*.npz" X_train, X_valid, y_train, y_valid = load_data(input_size, data_path) # train a neural network layer_sizes = [input_size, 32, 4] nn = NeuralNetwork() nn.create() nn.train(X_train, y_train, X_valid, y_valid) # evaluate on train data train_accuracy = nn.evaluate(X_train, y_train) print("Train accuracy: ", "{0:.2f}%".format(train_accuracy * 100)) # evaluate on validation data validation_accuracy = nn.evaluate(X_valid, y_valid) print("Validation accuracy: ", "{0:.2f}%".format(validation_accuracy * 100)) # save model model_path = "saved_model/model_test.xml" nn.save_model(model_path)
from model import load_data, NeuralNetwork input_size = 120 * 320 data_path = "training_data/*.npz" X_train, X_valid, y_train, y_valid = load_data(input_size, data_path) # train a neural network layer_sizes = [input_size, 32, 4] nn = NeuralNetwork() nn.create(layer_sizes) nn.train(X_train, y_train) # evaluate on train data train_accuracy = nn.evaluate(X_train, y_train) print("Train accuracy: ", "{0:.2f}%".format(train_accuracy * 100)) # evaluate on validation data validation_accuracy = nn.evaluate(X_valid, y_valid) print("Validation accuracy: ", "{0:.2f}%".format(validation_accuracy * 100)) # save model model_path = "saved_model/nn_model.xml" nn.save_model(model_path)
__author__ = 'zhengwang' from model import load_data, NeuralNetwork input_size = 120 * 320 data_path = "training_data/*.npz" X_train, X_valid, y_train, y_valid = load_data(input_size, data_path) # train a neural network layer_sizes = [input_size, 32, 4] nn = NeuralNetwork() nn.create(layer_sizes) nn.train(X_train, y_train) # evaluate on train data train_accuracy = nn.evaluate(X_train, y_train) print("Train accuracy: ", "{0:.2f}%".format(train_accuracy * 100)) # evaluate on validation data validation_accuracy = nn.evaluate(X_valid, y_valid) print("Validation accuracy: ", "{0:.2f}%".format(validation_accuracy * 100)) # save model model_path = "saved_model/nn_model.xml" nn.save_model(model_path)