forked from huawei/mindspore2022
301 lines
12 KiB
Python
301 lines
12 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""
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Test Places365 dataset operators
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"""
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import os
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import matplotlib.pyplot as plt
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import numpy as np
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import pytest
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from PIL import Image
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import mindspore.dataset as ds
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from mindspore import log as logger
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DATA_DIR = "../data/dataset/testPlaces365Data"
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def load_places365(path):
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"""
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Feature: load_places365.
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Description: load places365.
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Expectation: get data of places365 dataset.
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"""
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images_path = os.path.realpath(os.path.join(path, 'val_256'))
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labels_path = os.path.realpath(os.path.join(path, 'places365_val.txt'))
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images = []
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labels = []
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with open(labels_path, 'r') as f:
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for line in f.readlines():
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file_path, label = line.split()
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image = np.array(Image.open(images_path + file_path))
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label = int(label)
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images.append(image)
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labels.append(label)
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return images, labels
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def visualize_dataset(images, labels):
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"""
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Feature: visualize_dataset.
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Description: visualize places365 dataset.
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Expectation: plot images.
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"""
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num_samples = len(images)
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for i in range(num_samples):
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plt.subplot(1, num_samples, i + 1)
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plt.imshow(images[i].squeeze(), cmap=plt.cm.gray)
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plt.title(labels[i])
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plt.show()
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def test_places365_content_check():
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"""
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Feature: test_places365_content_check.
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Description: validate Places365Dataset image readings.
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Expectation: get correct number of data and correct content.
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"""
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logger.info("Test Places365Dataset Op with content check")
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sampler = ds.SequentialSampler(num_samples=4)
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data1 = ds.Places365Dataset(dataset_dir=DATA_DIR, usage='val', small=True, decode=True, sampler=sampler)
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_, labels = load_places365(DATA_DIR)
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num_iter = 0
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# in this example, each dictionary has keys "image" and "label"
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image_list, label_list = [], []
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for i, data in enumerate(data1.create_dict_iterator(num_epochs=1, output_numpy=True)):
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image_list.append(data["image"])
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label_list.append("label {}".format(data["label"]))
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# due to the precision problem, the following two doesn't total equal.
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# np.testing.assert_array_equal(data["image"], images[i])
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np.testing.assert_array_equal(data["label"], labels[i])
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num_iter += 1
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assert num_iter == 4
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def test_places365_basic():
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"""
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Feature: test_places365_basic.
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Description: test basic usage of Places365Dataset.
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Expectation: get correct number of data.
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"""
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logger.info("Test places365Dataset Op")
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# case 1: test loading whole dataset
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data1 = ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True)
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num_iter1 = 0
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for _ in data1.create_dict_iterator(num_epochs=1):
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num_iter1 += 1
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assert num_iter1 == 4
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# case 2: test num_samples
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data2 = ds.Places365Dataset(DATA_DIR, usage='train-standard', small=True, decode=True, num_samples=4)
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num_iter2 = 0
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for _ in data2.create_dict_iterator(num_epochs=1):
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num_iter2 += 1
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assert num_iter2 == 4
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# case 3: test repeat
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data3 = ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, num_samples=4)
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data3 = data3.repeat(5)
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num_iter3 = 0
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for _ in data3.create_dict_iterator(num_epochs=1):
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num_iter3 += 1
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assert num_iter3 == 20
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# case 4: test batch with drop_remainder=False
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data4 = ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, num_samples=4)
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assert data4.get_dataset_size() == 4
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assert data4.get_batch_size() == 1
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data4 = data4.batch(batch_size=2) # drop_remainder is default to be False
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assert data4.get_dataset_size() == 2
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assert data4.get_batch_size() == 2
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num_iter4 = 0
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for _ in data4.create_dict_iterator(num_epochs=1):
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num_iter4 += 1
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assert num_iter4 == 2
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# case 5: test batch with drop_remainder=True
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data5 = ds.Places365Dataset(DATA_DIR, usage='train-standard', small=True, decode=True, num_samples=4)
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assert data5.get_dataset_size() == 4
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assert data5.get_batch_size() == 1
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data5 = data5.batch(batch_size=3, drop_remainder=True) # the rest of incomplete batch will be dropped
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assert data5.get_dataset_size() == 1
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assert data5.get_batch_size() == 3
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num_iter5 = 0
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for _ in data5.create_dict_iterator(num_epochs=1):
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num_iter5 += 1
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assert num_iter5 == 1
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def test_places365_pk_sampler():
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"""
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Feature: test_places365_pk_sampler.
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Description: test usage of Places365Dataset with PKSampler.
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Expectation: get correct number of data.
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"""
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logger.info("Test Places365Dataset Op with PKSampler")
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sampler = ds.PKSampler(1)
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data = ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, sampler=sampler)
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num_iter = 0
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golden = [0, 1]
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label_list = []
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for item in data.create_dict_iterator(num_epochs=1, output_numpy=True):
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label_list.append(item["label"])
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num_iter += 1
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np.testing.assert_array_equal(golden, label_list)
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assert num_iter == 2
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def test_places365_sequential_sampler():
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"""
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Feature: test_places365_sequential_sampler.
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Description: test usage of Places365Dataset with SequentialSampler.
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Expectation: get correct number of data.
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"""
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logger.info("Test Places365Dataset Op with SequentialSampler")
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num_samples = 4
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sampler = ds.SequentialSampler(num_samples=num_samples)
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data1 = ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, sampler=sampler)
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data2 = ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, shuffle=False, num_samples=num_samples)
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label_list1, label_list2 = [], []
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num_iter = 0
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for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1), data2.create_dict_iterator(num_epochs=1)):
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label_list1.append(item1["label"].asnumpy())
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label_list2.append(item2["label"].asnumpy())
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num_iter += 1
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np.testing.assert_array_equal(label_list1, label_list2)
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assert num_iter == num_samples
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def test_places365_exception():
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"""
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Feature: test_places365_exception.
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Description: test error cases for Places365Dataset.
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Expectation: raise exception.
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"""
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logger.info("Test error cases for Places365Dataset")
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error_msg_1 = "sampler and shuffle cannot be specified at the same time"
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with pytest.raises(RuntimeError, match=error_msg_1):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, shuffle=False, sampler=ds.PKSampler(3))
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error_msg_2 = "sampler and sharding cannot be specified at the same time"
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with pytest.raises(RuntimeError, match=error_msg_2):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True,
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sampler=ds.PKSampler(3), num_shards=2, shard_id=0)
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error_msg_3 = "num_shards is specified and currently requires shard_id as well"
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with pytest.raises(RuntimeError, match=error_msg_3):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, num_shards=4)
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error_msg_4 = "shard_id is specified but num_shards is not"
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with pytest.raises(RuntimeError, match=error_msg_4):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, shard_id=0)
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error_msg_5 = "Input shard_id is not within the required interval"
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with pytest.raises(ValueError, match=error_msg_5):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, num_shards=2, shard_id=-1)
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with pytest.raises(ValueError, match=error_msg_5):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, num_shards=2, shard_id=2)
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with pytest.raises(ValueError, match=error_msg_5):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, num_shards=2, shard_id=5)
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error_msg_6 = "num_parallel_workers exceeds"
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with pytest.raises(ValueError, match=error_msg_6):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, shuffle=False, num_parallel_workers=0)
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with pytest.raises(ValueError, match=error_msg_6):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, shuffle=False, num_parallel_workers=256)
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with pytest.raises(ValueError, match=error_msg_6):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, shuffle=False, num_parallel_workers=-2)
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error_msg_7 = "Argument shard_id"
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with pytest.raises(TypeError, match=error_msg_7):
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ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, num_shards=2, shard_id="0")
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def test_places365_visualize(plot=False):
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"""
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Feature: test_places365_visualize.
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Description: visualize Places365Dataset results.
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Expectation: get correct number of data and plot them.
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"""
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logger.info("Test Places365Dataset visualization")
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data1 = ds.Places365Dataset(DATA_DIR, usage='val', small=True, decode=True, num_samples=4, shuffle=False)
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num_iter = 0
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image_list, label_list = [], []
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for item in data1.create_dict_iterator(num_epochs=1, output_numpy=True):
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image = item["image"]
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label = item["label"]
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image_list.append(image)
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label_list.append("label {}".format(label))
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assert isinstance(image, np.ndarray)
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assert image.shape == (256, 256, 3)
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assert image.dtype == np.uint8
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assert label.dtype == np.uint32
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num_iter += 1
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assert num_iter == 4
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if plot:
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visualize_dataset(image_list, label_list)
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def test_places365_usage():
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"""
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Feature: test_places365_usage.
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Description: validate Places365Dataset image readings.
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Expectation: get correct number of data.
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"""
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logger.info("Test Places365Dataset usage flag")
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def test_config(usage, places365_path=None):
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if places365_path is None:
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places365_path = DATA_DIR
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try:
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data = ds.Places365Dataset(places365_path, usage=usage, small=True, decode=True, shuffle=False)
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num_rows = 0
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for _ in data.create_dict_iterator(num_epochs=1, output_numpy=True):
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num_rows += 1
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except (ValueError, TypeError, RuntimeError) as e:
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print(str(e))
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return str(e)
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return num_rows
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assert test_config("val") == 4
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assert "usage is not within the valid set of ['train-standard', 'train-challenge', 'val']" in test_config("invalid")
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assert "Argument usage with value ['list'] is not of type [<class 'str'>]" in test_config(["list"])
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# change this directory to the folder that contains all places365 files
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train_standard_files_path = DATA_DIR
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# the following tests on the entire datasets
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if train_standard_files_path is not None:
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assert test_config("train-standard", train_standard_files_path) == 4
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assert test_config("val", train_standard_files_path) == 4
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# change this directory to the folder that contains all places365 files
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train_challenge_files_path = DATA_DIR
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# the following tests on the entire datasets
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if train_challenge_files_path is not None:
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assert test_config("train-challenge", train_challenge_files_path) == 4
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assert test_config("val", train_standard_files_path) == 4
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if __name__ == '__main__':
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test_places365_content_check()
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test_places365_basic()
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test_places365_pk_sampler()
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test_places365_sequential_sampler()
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test_places365_exception()
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test_places365_visualize(plot=True)
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test_places365_usage()
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