wehub-resource-sync
220 lines
6.5 KiB
Python
220 lines
6.5 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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import unittest
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import numpy as np
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import paddle
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from paddle.vision.transforms import transforms
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SEED = 2022
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class TestTransformUnitTestBase(unittest.TestCase):
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def setUp(self):
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self.img = (np.random.rand(*self.get_shape()) * 255.0).astype(
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np.float32
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)
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self.set_trans_api()
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self.init_dy_res()
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def init_dy_res(self):
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# Obtain the dynamic transform result first before test_transform.
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self.dy_res = self.dynamic_transform()
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if isinstance(self.dy_res, paddle.Tensor):
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self.dy_res = self.dy_res.numpy()
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def get_shape(self):
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return (3, 64, 64)
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def set_trans_api(self):
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self.api = transforms.Resize(size=16)
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def dynamic_transform(self):
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paddle.seed(SEED)
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img_t = paddle.to_tensor(self.img)
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return self.api(img_t)
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def static_transform(self):
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paddle.enable_static()
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paddle.seed(SEED)
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main_program = paddle.static.Program()
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with paddle.static.program_guard(main_program):
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x = paddle.static.data(
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shape=self.get_shape(), dtype=paddle.float32, name='img'
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)
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out = self.api(x)
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exe = paddle.static.Executor()
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res = exe.run(main_program, fetch_list=[out], feed={'img': self.img})
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paddle.disable_static()
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return res[0]
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def test_transform(self):
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st_res = self.static_transform()
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np.testing.assert_almost_equal(self.dy_res, st_res)
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class TestResize(TestTransformUnitTestBase):
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def set_trans_api(self):
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self.api = transforms.Resize(size=(16, 16))
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class TestResizeError(TestTransformUnitTestBase):
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def test_transform(self):
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pass
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def test_error(self):
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paddle.enable_static()
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# Not support while w<=0 or h<=0, but received w=-1, h=-1
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with self.assertRaises(NotImplementedError):
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main_program = paddle.static.Program()
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with paddle.static.program_guard(main_program):
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x = paddle.static.data(
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shape=[-1, -1, -1], dtype=paddle.float32, name='img'
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)
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self.api(x)
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paddle.disable_static()
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class TestRandomVerticalFlip0(TestTransformUnitTestBase):
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def set_trans_api(self):
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self.api = transforms.RandomVerticalFlip(prob=0)
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class TestRandomVerticalFlip1(TestTransformUnitTestBase):
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def set_trans_api(self):
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self.api = transforms.RandomVerticalFlip(prob=1)
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class TestRandomHorizontalFlip0(TestTransformUnitTestBase):
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def set_trans_api(self):
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self.api = transforms.RandomHorizontalFlip(0)
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class TestRandomHorizontalFlip1(TestTransformUnitTestBase):
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def set_trans_api(self):
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self.api = transforms.RandomHorizontalFlip(1)
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class TestRandomCrop_random(TestTransformUnitTestBase):
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def get_shape(self):
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return (3, 240, 240)
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def set_trans_api(self):
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self.crop_size = (224, 224)
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self.api = transforms.RandomCrop(self.crop_size)
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def assert_test_random_equal(self, res, eps=1e-4):
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_, h, w = self.get_shape()
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c_h, c_w = self.crop_size
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res_assert = True
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for y_offset in range(h - c_h + 1):
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for x_offset in range(w - c_w + 1):
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diff_abs_sum = np.abs(
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self.img[
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:, y_offset : y_offset + c_h, x_offset : x_offset + c_w
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]
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- res
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).sum()
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if diff_abs_sum < eps:
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res_assert = False
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break
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if not res_assert:
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break
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assert not res_assert
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def test_transform(self):
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st_res = self.static_transform()
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self.assert_test_random_equal(self.dy_res)
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self.assert_test_random_equal(st_res)
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class TestRandomCrop_same(TestTransformUnitTestBase):
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def get_shape(self):
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return (3, 224, 224)
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def set_trans_api(self):
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self.crop_size = (224, 224)
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self.api = transforms.RandomCrop(self.crop_size)
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class FixedAngleRandomRotation(transforms.RandomRotation):
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# Keep the rotation path under test, but bypass separate dy/static RNGs.
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def __init__(self, angle, **kwargs):
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self.angle = float(np.float32(angle))
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super().__init__((self.angle, self.angle), **kwargs)
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def _get_param(self, degrees):
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del degrees
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if paddle.in_dynamic_mode():
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return self.angle
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return paddle.full([1], self.angle, dtype='float32')
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class TestRandomRotation(TestTransformUnitTestBase):
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def set_trans_api(self):
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self.api = FixedAngleRandomRotation(33.0)
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class TestRandomRotation_expand_True(TestTransformUnitTestBase):
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def set_trans_api(self):
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self.api = FixedAngleRandomRotation(33.0, expand=True, fill=3)
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class TestRandomErasing(TestTransformUnitTestBase):
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def set_trans_api(self):
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self.value = 100
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self.scale = (0.02, 0.33)
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self.ratio = (0.3, 3.3)
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self.api = transforms.RandomErasing(
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prob=1, value=self.value, scale=self.scale, ratio=self.ratio
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)
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def test_transform(self):
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st_res = self.static_transform()
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self.assert_test_erasing(self.dy_res)
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self.assert_test_erasing(st_res)
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def assert_test_erasing(self, arr):
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_, h, w = arr.shape
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area = h * w
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height = (arr[2] == self.value).cumsum(1)[:, -1].max()
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width = (arr[2] == self.value).cumsum(0)[-1].max()
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erasing_area = height * width
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assert self.ratio[0] < height / width < self.ratio[1]
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assert self.scale[0] < erasing_area / area < self.scale[1]
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class TestRandomResizedCrop(TestTransformUnitTestBase):
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def set_trans_api(self, eps=10e-5):
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c, h, w = self.get_shape()
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size = h, w
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scale = (1 - eps, 1.0)
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ratio = (1 - eps, 1.0)
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self.api = transforms.RandomResizedCrop(size, scale=scale, ratio=ratio)
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if __name__ == "__main__":
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unittest.main()
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