mindspore2022/tests/ut/python/dataset/test_datasets_sbu.py

# Copyright 2021 Huawei Technologies Co., Ltd
#
# 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.
# ==============================================================================
"""
Test USPS dataset operators
"""
import os

import matplotlib.pyplot as plt
import numpy as np
import pytest
from PIL import Image

import mindspore.dataset as ds
import mindspore.dataset.vision.c_transforms as vision
from mindspore import log as logger

DATA_DIR = "../data/dataset/testSBUDataset"
WRONG_DIR = "../data/dataset/testMnistData"


def load_sbu(path):
    """
    load SBU data
    """
    images = []
    captions = []

    file1 = os.path.realpath(os.path.join(path, 'SBU_captioned_photo_dataset_urls.txt'))
    file2 = os.path.realpath(os.path.join(path, 'SBU_captioned_photo_dataset_captions.txt'))

    for line1, line2 in zip(open(file1), open(file2)):
        url = line1.rstrip()
        image = url[23:].replace("/", "_")
        filename = os.path.join(path, 'sbu_images', image)
        if os.path.exists(filename):
            caption = line2.rstrip()
            images.append(np.asarray(Image.open(filename).convert('RGB')).astype(np.uint8))
            captions.append(caption)
    return images, captions


def visualize_dataset(images, captions):
    """
    Helper function to visualize the dataset samples
    """
    num_samples = len(images)
    for i in range(num_samples):
        plt.subplot(1, num_samples, i + 1)
        plt.imshow(images[i].squeeze())
        plt.title(captions[i])
    plt.show()


def test_sbu_content_check():
    """
    Validate SBUDataset image readings
    """
    logger.info("Test SBUDataset Op with content check")
    dataset = ds.SBUDataset(DATA_DIR, decode=True, num_samples=50, shuffle=False)
    images, captions = load_sbu(DATA_DIR)
    num_iter = 0
    # in this example, each dictionary has keys "image" and "caption"
    for i, data in enumerate(dataset.create_dict_iterator(num_epochs=1, output_numpy=True)):
        assert data["image"].shape == images[i].shape
        assert data["caption"].item().decode("utf8") == captions[i]
        num_iter += 1
    assert num_iter == 5


def test_sbu_case():
    """
    Validate SBUDataset cases
    """
    dataset = ds.SBUDataset(DATA_DIR, decode=True)

    dataset = dataset.map(operations=[vision.Resize((224, 224))], input_columns=["image"])
    repeat_num = 4
    dataset = dataset.repeat(repeat_num)
    batch_size = 2
    dataset = dataset.batch(batch_size, drop_remainder=True, pad_info={})

    num = 0
    for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
        num += 1
    # 4 x 5 / 2
    assert num == 10

    dataset = ds.SBUDataset(DATA_DIR, decode=False)

    dataset = dataset.map(operations=[vision.Decode(rgb=True), vision.Resize((224, 224))], input_columns=["image"])
    repeat_num = 4
    dataset = dataset.repeat(repeat_num)
    batch_size = 2
    dataset = dataset.batch(batch_size, drop_remainder=True, pad_info={})

    num = 0
    for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
        num += 1
    # 4 x 5 / 2
    assert num == 10


def test_sbu_basic():
    """
    Validate SBUDataset
    """
    logger.info("Test SBUDataset Op")

    # case 1: test loading whole dataset
    dataset = ds.SBUDataset(DATA_DIR, decode=True)
    num_iter = 0
    for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
        num_iter += 1
    assert num_iter == 5


    # case 2: test num_samples
    dataset = ds.SBUDataset(DATA_DIR, decode=True, num_samples=5)
    num_iter = 0
    for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
        num_iter += 1
    assert num_iter == 5

    # case 3: test repeat
    dataset = ds.SBUDataset(DATA_DIR, decode=True, num_samples=5)
    dataset = dataset.repeat(5)
    num_iter = 0
    for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
        num_iter += 1
    assert num_iter == 25

    # case 4: test batch
    dataset = ds.SBUDataset(DATA_DIR, decode=True, num_samples=5)
    assert dataset.get_dataset_size() == 5
    assert dataset.get_batch_size() == 1

    num_iter = 0
    for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
        num_iter += 1
    assert num_iter == 5

    # case 5: test get_class_indexing
    dataset = ds.SBUDataset(DATA_DIR, decode=True, num_samples=5)
    assert dataset.get_class_indexing() == {}

    # case 6: test get_col_names
    dataset = ds.SBUDataset(DATA_DIR, decode=True, num_samples=5)
    assert dataset.get_col_names() == ["image", "caption"]


def test_sbu_sequential_sampler():
    """
    Test SBUDataset with SequentialSampler
    """
    logger.info("Test SBUDataset Op with SequentialSampler")
    num_samples = 5
    sampler = ds.SequentialSampler(num_samples=num_samples)
    dataset_1 = ds.SBUDataset(DATA_DIR, decode=True, sampler=sampler)
    dataset_2 = ds.SBUDataset(DATA_DIR, decode=True, shuffle=False, num_samples=num_samples)

    num_iter = 0
    for item1, item2 in zip(dataset_1.create_dict_iterator(num_epochs=1, output_numpy=True),
                            dataset_2.create_dict_iterator(num_epochs=1, output_numpy=True)):
        np.testing.assert_array_equal(item1["caption"], item2["caption"])
        num_iter += 1
    assert num_iter == num_samples


def test_sbu_exception():
    """
    Test error cases for SBUDataset
    """
    logger.info("Test error cases for SBUDataset")
    error_msg_1 = "sampler and shuffle cannot be specified at the same time"
    with pytest.raises(RuntimeError, match=error_msg_1):
        ds.SBUDataset(DATA_DIR, decode=True, shuffle=False, sampler=ds.SequentialSampler())

    error_msg_2 = "sampler and sharding cannot be specified at the same time"
    with pytest.raises(RuntimeError, match=error_msg_2):
        ds.SBUDataset(DATA_DIR, decode=True, sampler=ds.SequentialSampler(), num_shards=2, shard_id=0)

    error_msg_3 = "num_shards is specified and currently requires shard_id as well"
    with pytest.raises(RuntimeError, match=error_msg_3):
        ds.SBUDataset(DATA_DIR, decode=True, num_shards=10)

    error_msg_4 = "shard_id is specified but num_shards is not"
    with pytest.raises(RuntimeError, match=error_msg_4):
        ds.SBUDataset(DATA_DIR, decode=True, shard_id=0)

    error_msg_5 = "Input shard_id is not within the required interval"
    with pytest.raises(ValueError, match=error_msg_5):
        ds.SBUDataset(DATA_DIR, decode=True, num_shards=5, shard_id=-1)
    with pytest.raises(ValueError, match=error_msg_5):
        ds.SBUDataset(DATA_DIR, decode=True, num_shards=5, shard_id=5)
    with pytest.raises(ValueError, match=error_msg_5):
        ds.SBUDataset(DATA_DIR, decode=True, num_shards=2, shard_id=5)

    error_msg_6 = "num_parallel_workers exceeds"
    with pytest.raises(ValueError, match=error_msg_6):
        ds.SBUDataset(DATA_DIR, decode=True, shuffle=False, num_parallel_workers=0)
    with pytest.raises(ValueError, match=error_msg_6):
        ds.SBUDataset(DATA_DIR, decode=True, shuffle=False, num_parallel_workers=256)
    with pytest.raises(ValueError, match=error_msg_6):
        ds.SBUDataset(DATA_DIR, decode=True, shuffle=False, num_parallel_workers=-2)

    error_msg_7 = "Argument shard_id"
    with pytest.raises(TypeError, match=error_msg_7):
        ds.SBUDataset(DATA_DIR, decode=True, num_shards=2, shard_id="0")

    def exception_func(item):
        raise Exception("Error occur!")

    error_msg_8 = "The corresponding data files"
    with pytest.raises(RuntimeError, match=error_msg_8):
        dataset = ds.SBUDataset(DATA_DIR, decode=True)
        dataset = dataset.map(operations=exception_func, input_columns=["image"], num_parallel_workers=1)
        for _ in dataset.__iter__():
            pass

    with pytest.raises(RuntimeError, match=error_msg_8):
        dataset = ds.SBUDataset(DATA_DIR, decode=True)
        dataset = dataset.map(operations=vision.Decode(), input_columns=["image"], num_parallel_workers=1)
        for _ in dataset.__iter__():
            pass

    error_msg_9 = "does not exist or permission denied"
    with pytest.raises(ValueError, match=error_msg_9):
        dataset = ds.SBUDataset(WRONG_DIR, decode=True)
        for _ in dataset.__iter__():
            pass

    error_msg_10 = "Argument decode with value"
    with pytest.raises(TypeError, match=error_msg_10):
        dataset = ds.SBUDataset(DATA_DIR, decode="not_bool")
        for _ in dataset.__iter__():
            pass


def test_sbu_visualize(plot=False):
    """
    Visualize SBUDataset results
    """
    logger.info("Test SBUDataset visualization")

    dataset = ds.SBUDataset(DATA_DIR, decode=True, num_samples=10, shuffle=False)
    num_iter = 0
    image_list, caption_list = [], []
    for item in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
        image = item["image"]
        caption = item["caption"].item().decode("utf8")
        image_list.append(image)
        caption_list.append("caption {}".format(caption))
        assert isinstance(image, np.ndarray)

        assert image.dtype == np.uint8
        assert isinstance(caption, str)
        num_iter += 1
    assert num_iter == 5
    if plot:
        visualize_dataset(image_list, caption_list)


def test_sbu_decode():
    """
    Validate SBUDataset image readings
    """
    logger.info("Test SBUDataset decode flag")

    sampler = ds.SequentialSampler(num_samples=50)
    dataset = ds.SBUDataset(dataset_dir=DATA_DIR, decode=False, sampler=sampler)
    dataset_1 = dataset.map(operations=[vision.Decode(rgb=True)], input_columns=["image"])

    dataset_2 = ds.SBUDataset(dataset_dir=DATA_DIR, decode=True, sampler=sampler)

    num_iter = 0
    for item1, item2 in zip(dataset_1.create_dict_iterator(num_epochs=1, output_numpy=True),
                            dataset_2.create_dict_iterator(num_epochs=1, output_numpy=True)):
        np.testing.assert_array_equal(item1["caption"], item2["caption"])
        num_iter += 1

    assert num_iter == 5


if __name__ == '__main__':
    test_sbu_content_check()
    test_sbu_basic()
    test_sbu_case()
    test_sbu_sequential_sampler()
    test_sbu_exception()
    test_sbu_visualize(plot=True)
    test_sbu_decode()