mindspore/tests/ut/python/dataset/test_random_perspective.py

131 lines
4.9 KiB
Python

# Copyright 2020 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.
# ==============================================================================
"""
Testing RandomPerspective op in DE
"""
import numpy as np
import mindspore.dataset as ds
import mindspore.dataset.transforms.py_transforms
import mindspore.dataset.vision.py_transforms as py_vision
from mindspore.dataset.vision.utils import Inter
from mindspore import log as logger
from util import visualize_list, save_and_check_md5, \
config_get_set_seed, config_get_set_num_parallel_workers
GENERATE_GOLDEN = False
DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
def test_random_perspective_op(plot=False):
"""
Test RandomPerspective in python transformations
"""
logger.info("test_random_perspective_op")
# define map operations
transforms1 = [
py_vision.Decode(),
py_vision.RandomPerspective(),
py_vision.ToTensor()
]
transform1 = mindspore.dataset.transforms.py_transforms.Compose(transforms1)
transforms2 = [
py_vision.Decode(),
py_vision.ToTensor()
]
transform2 = mindspore.dataset.transforms.py_transforms.Compose(transforms2)
# First dataset
data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
data1 = data1.map(input_columns=["image"], operations=transform1)
# Second dataset
data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
data2 = data2.map(input_columns=["image"], operations=transform2)
image_perspective = []
image_original = []
for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1), data2.create_dict_iterator(num_epochs=1)):
image1 = (item1["image"].transpose(1, 2, 0) * 255).astype(np.uint8)
image2 = (item2["image"].transpose(1, 2, 0) * 255).astype(np.uint8)
image_perspective.append(image1)
image_original.append(image2)
if plot:
visualize_list(image_original, image_perspective)
def skip_test_random_perspective_md5():
"""
Test RandomPerspective with md5 comparison
"""
logger.info("test_random_perspective_md5")
original_seed = config_get_set_seed(5)
original_num_parallel_workers = config_get_set_num_parallel_workers(1)
# define map operations
transforms = [
py_vision.Decode(),
py_vision.RandomPerspective(distortion_scale=0.3, prob=0.7,
interpolation=Inter.BILINEAR),
py_vision.Resize(1450), # resize to a smaller size to prevent round-off error
py_vision.ToTensor()
]
transform = mindspore.dataset.transforms.py_transforms.Compose(transforms)
# Generate dataset
data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
data = data.map(input_columns=["image"], operations=transform)
# check results with md5 comparison
filename = "random_perspective_01_result.npz"
save_and_check_md5(data, filename, generate_golden=GENERATE_GOLDEN)
# Restore configuration
ds.config.set_seed(original_seed)
ds.config.set_num_parallel_workers((original_num_parallel_workers))
def test_random_perspective_exception_distortion_scale_range():
"""
Test RandomPerspective: distortion_scale is not in [0, 1], expected to raise ValueError
"""
logger.info("test_random_perspective_exception_distortion_scale_range")
try:
_ = py_vision.RandomPerspective(distortion_scale=1.5)
except ValueError as e:
logger.info("Got an exception in DE: {}".format(str(e)))
assert str(e) == "Input distortion_scale is not within the required interval of (0.0 to 1.0)."
def test_random_perspective_exception_prob_range():
"""
Test RandomPerspective: prob is not in [0, 1], expected to raise ValueError
"""
logger.info("test_random_perspective_exception_prob_range")
try:
_ = py_vision.RandomPerspective(prob=1.2)
except ValueError as e:
logger.info("Got an exception in DE: {}".format(str(e)))
assert str(e) == "Input prob is not within the required interval of (0.0 to 1.0)."
if __name__ == "__main__":
test_random_perspective_op(plot=True)
skip_test_random_perspective_md5()
test_random_perspective_exception_distortion_scale_range()
test_random_perspective_exception_prob_range()