forked from mindspore-Ecosystem/mindspore
241 lines
9.2 KiB
Python
241 lines
9.2 KiB
Python
# Copyright 2021-2022 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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Testing Rotate Python API
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"""
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import cv2
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import numpy as np
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import mindspore.dataset as ds
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import mindspore.dataset.vision as vision
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from mindspore import log as logger
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from mindspore.dataset.vision.utils import Inter
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from util import visualize_image, diff_mse
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DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
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SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
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IMAGE_FILE = "../data/dataset/apple.jpg"
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FOUR_DIM_DATA = [[[[1, 2, 3], [3, 4, 3]], [[5, 6, 3], [7, 8, 3]]],
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[[[9, 10, 3], [11, 12, 3]], [[13, 14, 3], [15, 16, 3]]]]
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FIVE_DIM_DATA = [[[[[1, 2, 3], [3, 4, 3]], [[5, 6, 3], [7, 8, 3]]],
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[[[9, 10, 3], [11, 12, 3]], [[13, 14, 3], [15, 16, 3]]]]]
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FOUR_DIM_RES = [[[[3, 4, 3], [7, 8, 3]], [[1, 2, 3], [5, 6, 3]]],
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[[[11, 12, 3], [15, 16, 3]], [[9, 10, 3], [13, 14, 3]]]]
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FIVE_DIM_RES = [[[[3, 4, 3], [7, 8, 3]], [[1, 2, 3], [5, 6, 3]]],
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[[[11, 12, 3], [15, 16, 3]], [[9, 10, 3], [13, 14, 3]]]]
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def test_rotate_pipeline_with_expanding(plot=False):
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"""
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Feature: Rotate
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Description: Test Rotate of Cpp implementation in pipeline mode with expanding
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Expectation: Output is the same as expected output
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"""
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logger.info("test_rotate_pipeline_with_expanding")
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# First dataset
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dataset1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
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decode_op = vision.Decode()
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rotate_op = vision.Rotate(90, expand=True)
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dataset1 = dataset1.map(operations=decode_op, input_columns=["image"])
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dataset1 = dataset1.map(operations=rotate_op, input_columns=["image"])
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# Second dataset
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dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
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dataset2 = dataset2.map(operations=decode_op, input_columns=["image"])
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num_iter = 0
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for data1, data2 in zip(dataset1.create_dict_iterator(num_epochs=1, output_numpy=True),
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dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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if num_iter > 0:
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break
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rotate_ms = data1["image"]
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original = data2["image"]
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rotate_cv = cv2.rotate(original, cv2.ROTATE_90_COUNTERCLOCKWISE)
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mse = diff_mse(rotate_ms, rotate_cv)
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logger.info("rotate_{}, mse: {}".format(num_iter + 1, mse))
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assert mse == 0
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num_iter += 1
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if plot:
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visualize_image(original, rotate_ms, mse, rotate_cv)
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def test_rotate_video_op_1d():
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"""
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Feature: Rotate
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Description: Test Rotate op by processing tensor with dim 1
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Expectation: Error is raised as expected
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"""
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logger.info("Test Rotate with 1 dimension input")
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data = [1]
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input_mindspore = np.array(data).astype(np.uint8)
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rotate_op = vision.Rotate(90, expand=False)
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try:
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rotate_op(input_mindspore)
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except RuntimeError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert "Rotate: the image tensor should have at least two dimensions. You may need to perform " \
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"Decode first." in str(e)
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def test_rotate_video_op_4d_without_expanding():
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"""
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Feature: Rotate
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Description: Test Rotate op by processing tensor with dim more than 3 (dim 4) without expanding
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Expectation: Output is the same as expected output
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"""
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logger.info("Test Rotate with 4 dimension input")
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input_4_dim = np.array(FOUR_DIM_DATA).astype(np.uint8)
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input_4_shape = input_4_dim.shape
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num_batch = input_4_shape[0]
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out_4_list = []
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batch_1d = 0
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while batch_1d < num_batch:
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out_4_list.append(cv2.rotate(input_4_dim[batch_1d], cv2.ROTATE_90_COUNTERCLOCKWISE))
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batch_1d += 1
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out_4_cv = np.array(out_4_list).astype(np.uint8)
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out_4_mindspore = vision.Rotate(90, expand=False)(input_4_dim)
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mse = diff_mse(out_4_mindspore, out_4_cv)
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assert mse < 0.001
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def test_rotate_video_op_5d_without_expanding():
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"""
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Feature: Rotate
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Description: Test Rotate op by processing tensor with dim more than 3 (dim 5) without expanding
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Expectation: Output is the same as expected output
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"""
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logger.info("Test Rotate with 5 dimension input")
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input_5_dim = np.array(FIVE_DIM_DATA).astype(np.uint8)
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input_5_shape = input_5_dim.shape
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num_batch_1d = input_5_shape[0]
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num_batch_2d = input_5_shape[1]
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out_5_list = []
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batch_1d = 0
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batch_2d = 0
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while batch_1d < num_batch_1d:
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while batch_2d < num_batch_2d:
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out_5_list.append(cv2.rotate(input_5_dim[batch_1d][batch_2d], cv2.ROTATE_90_COUNTERCLOCKWISE))
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batch_2d += 1
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batch_1d += 1
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out_5_cv = np.array(out_5_list).astype(np.uint8)
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out_5_mindspore = vision.Rotate(90, expand=False)(input_5_dim)
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mse = diff_mse(out_5_mindspore, out_5_cv)
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assert mse < 0.001
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def test_rotate_video_op_precision_eager():
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"""
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Feature: Rotate op
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Description: Test Rotate op by processing tensor with dim more than 3 (dim 4) in eager mode
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Expectation: The dataset is processed successfully
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"""
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logger.info("Test Rotate eager with 4 dimension input")
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input_mindspore = np.array(FOUR_DIM_DATA).astype(np.uint8)
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rotate_op = vision.Rotate(90, expand=False)
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out_mindspore = rotate_op(input_mindspore)
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mse = diff_mse(out_mindspore, np.array(FOUR_DIM_RES).astype(np.uint8))
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assert mse < 0.001
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def test_rotate_video_op_precision_pipeline():
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"""
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Feature: Rotate op
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Description: Test Rotate op by processing tensor with dim more than 3 (dim 5) in pipeline mode
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Expectation: The dataset is processed successfully
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"""
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logger.info("Test Rotate pipeline with 5 dimension input")
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data = np.array(FIVE_DIM_DATA).astype(np.uint8)
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expand_data = np.expand_dims(data, axis=0)
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dataset = ds.NumpySlicesDataset(expand_data, column_names=["col1"], shuffle=False)
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rotate_op = vision.Rotate(90, expand=False)
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dataset = dataset.map(operations=rotate_op, input_columns=["col1"])
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for item in dataset.create_dict_iterator(output_numpy=True):
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mse = diff_mse(item["col1"], np.array(FIVE_DIM_RES).astype(np.uint8))
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assert mse < 0.001
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def test_rotate_pipeline_without_expanding():
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"""
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Feature: Rotate
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Description: Test Rotate of Cpp implementation in pipeline mode without expanding
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Expectation: Output is the same as expected output
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"""
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logger.info("test_rotate_pipeline_without_expanding")
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# Create a Dataset then decode and rotate the image
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dataset = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
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decode_op = vision.Decode()
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resize_op = vision.Resize((64, 128))
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rotate_op = vision.Rotate(30)
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dataset = dataset.map(operations=decode_op, input_columns=["image"])
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dataset = dataset.map(operations=resize_op, input_columns=["image"])
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dataset = dataset.map(operations=rotate_op, input_columns=["image"])
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for data in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
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rotate_img = data["image"]
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assert rotate_img.shape == (64, 128, 3)
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def test_rotate_eager():
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"""
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Feature: Rotate
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Description: Test Rotate in eager mode
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Expectation: Output is the same as expected output
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"""
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logger.info("test_rotate_eager")
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img = cv2.imread(IMAGE_FILE)
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resize_img = vision.Resize((32, 64))(img)
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rotate_img = vision.Rotate(-90, expand=True)(resize_img)
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assert rotate_img.shape == (64, 32, 3)
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def test_rotate_exception():
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"""
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Feature: Rotate
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Description: Test Rotate with invalid parameters
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Expectation: Correct error is raised as expected
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"""
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logger.info("test_rotate_exception")
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try:
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_ = vision.Rotate("60")
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except TypeError as e:
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logger.info("Got an exception in Rotate: {}".format(str(e)))
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assert "not of type [<class 'float'>, <class 'int'>]" in str(e)
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try:
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_ = vision.Rotate(30, Inter.BICUBIC, False, (0, 0, 0))
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except ValueError as e:
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logger.info("Got an exception in Rotate: {}".format(str(e)))
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assert "Value center needs to be a 2-tuple." in str(e)
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try:
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_ = vision.Rotate(-120, Inter.NEAREST, False, (-1, -1), (255, 255))
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except TypeError as e:
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logger.info("Got an exception in Rotate: {}".format(str(e)))
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assert "fill_value should be a single integer or a 3-tuple." in str(e)
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if __name__ == "__main__":
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test_rotate_pipeline_with_expanding(False)
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test_rotate_video_op_1d()
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test_rotate_video_op_4d_without_expanding()
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test_rotate_video_op_5d_without_expanding()
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test_rotate_video_op_precision_eager()
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test_rotate_video_op_precision_pipeline()
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test_rotate_pipeline_without_expanding()
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test_rotate_eager()
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test_rotate_exception()
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