| # Lint as: python3 |
| # Copyright 2019 The TensorFlow Authors. All Rights Reserved. |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # ============================================================================== |
| # pylint: disable=g-bad-import-order |
| |
| """Load data from the specified paths and format them for training.""" |
| |
| from __future__ import absolute_import |
| from __future__ import division |
| from __future__ import print_function |
| |
| import json |
| |
| import numpy as np |
| import tensorflow as tf |
| |
| from data_augmentation import augment_data |
| |
| LABEL_NAME = "gesture" |
| DATA_NAME = "accel_ms2_xyz" |
| |
| |
| class DataLoader(object): |
| """Loads data and prepares for training.""" |
| |
| def __init__(self, train_data_path, valid_data_path, test_data_path, |
| seq_length): |
| self.dim = 3 |
| self.seq_length = seq_length |
| self.label2id = {"wing": 0, "ring": 1, "slope": 2, "negative": 3} |
| self.train_data, self.train_label, self.train_len = self.get_data_file( |
| train_data_path, "train") |
| self.valid_data, self.valid_label, self.valid_len = self.get_data_file( |
| valid_data_path, "valid") |
| self.test_data, self.test_label, self.test_len = self.get_data_file( |
| test_data_path, "test") |
| |
| def get_data_file(self, data_path, data_type): # pylint: disable=no-self-use |
| """Get train, valid and test data from files.""" |
| data = [] |
| label = [] |
| with open(data_path, "r") as f: |
| lines = f.readlines() |
| for idx, line in enumerate(lines): # pylint: disable=unused-variable |
| dic = json.loads(line) |
| data.append(dic[DATA_NAME]) |
| label.append(dic[LABEL_NAME]) |
| if data_type == "train": |
| data, label = augment_data(data, label) |
| length = len(label) |
| print(data_type + "_data_length:" + str(length)) |
| return data, label, length |
| |
| def pad(self, data, seq_length, dim): # pylint: disable=no-self-use |
| """Get neighbour padding.""" |
| noise_level = 20 |
| padded_data = [] |
| # Before- Neighbour padding |
| tmp_data = (np.random.rand(seq_length, dim) - 0.5) * noise_level + data[0] |
| tmp_data[(seq_length - |
| min(len(data), seq_length)):] = data[:min(len(data), seq_length)] |
| padded_data.append(tmp_data) |
| # After- Neighbour padding |
| tmp_data = (np.random.rand(seq_length, dim) - 0.5) * noise_level + data[-1] |
| tmp_data[:min(len(data), seq_length)] = data[:min(len(data), seq_length)] |
| padded_data.append(tmp_data) |
| return padded_data |
| |
| def format_support_func(self, padded_num, length, data, label): |
| """Support function for format.(Helps format train, valid and test.)""" |
| # Add 2 padding, initialize data and label |
| length *= padded_num |
| features = np.zeros((length, self.seq_length, self.dim)) |
| labels = np.zeros(length) |
| # Get padding for train, valid and test |
| for idx, (data, label) in enumerate(zip(data, label)): # pylint: disable=redefined-argument-from-local |
| padded_data = self.pad(data, self.seq_length, self.dim) |
| for num in range(padded_num): |
| features[padded_num * idx + num] = padded_data[num] |
| labels[padded_num * idx + num] = self.label2id[label] |
| # Turn into tf.data.Dataset |
| dataset = tf.data.Dataset.from_tensor_slices( |
| (features, labels.astype("int32"))) |
| return length, dataset |
| |
| def format(self): |
| """Format data(including padding, etc.) and get the dataset for the model.""" |
| padded_num = 2 |
| self.train_len, self.train_data = self.format_support_func( |
| padded_num, self.train_len, self.train_data, self.train_label) |
| self.valid_len, self.valid_data = self.format_support_func( |
| padded_num, self.valid_len, self.valid_data, self.valid_label) |
| self.test_len, self.test_data = self.format_support_func( |
| padded_num, self.test_len, self.test_data, self.test_label) |
