Python augmenters.MotionBlur方法代码示例

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def _load_augmentation_aug_non_geometric():
    return iaa.Sequential([
        iaa.Sometimes(0.3, iaa.Multiply((0.5, 1.5), per_channel=0.5)),
        iaa.Sometimes(0.2, iaa.JpegCompression(compression=(70, 99))),
        iaa.Sometimes(0.2, iaa.GaussianBlur(sigma=(0, 3.0))),
        iaa.Sometimes(0.2, iaa.MotionBlur(k=15, angle=[-45, 45])),
        iaa.Sometimes(0.2, iaa.MultiplyHue((0.5, 1.5))),
        iaa.Sometimes(0.2, iaa.MultiplySaturation((0.5, 1.5))),
        iaa.Sometimes(0.34, iaa.MultiplyHueAndSaturation((0.5, 1.5),
                                                         per_channel=True)),
        iaa.Sometimes(0.34, iaa.Grayscale(alpha=(0.0, 1.0))),
        iaa.Sometimes(0.2, iaa.ChangeColorTemperature((1100, 10000))),
        iaa.Sometimes(0.1, iaa.GammaContrast((0.5, 2.0))),
        iaa.Sometimes(0.2, iaa.SigmoidContrast(gain=(3, 10),
                                               cutoff=(0.4, 0.6))),
        iaa.Sometimes(0.1, iaa.CLAHE()),
        iaa.Sometimes(0.1, iaa.HistogramEqualization()),
        iaa.Sometimes(0.2, iaa.LinearContrast((0.5, 2.0), per_channel=0.5)),
        iaa.Sometimes(0.1, iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0)))
    ]) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_simple_parameters(self):
        # simple scenario
        aug = iaa.MotionBlur(k=3, angle=0, direction=0.0)
        matrix_func = aug.matrix
        matrices = [
            matrix_func(
                np.zeros((128, 128, 3), dtype=np.uint8),
                3,
                iarandom.RNG(i)
            ) for i in range(10)
        ]
        expected = np.float32([
            [0, 1.0/3, 0],
            [0, 1.0/3, 0],
            [0, 1.0/3, 0]
        ])
        for matrices_image in matrices:
            for matrix_channel in matrices_image:
                assert np.allclose(matrix_channel, expected) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_simple_parameters_angle_is_90(self):
        # 90deg angle
        aug = iaa.MotionBlur(k=3, angle=90, direction=0.0)
        matrix_func = aug.matrix
        matrices = [
            matrix_func(
                np.zeros((128, 128, 3), dtype=np.uint8),
                3,
                iarandom.RNG(i)
            ) for i in range(10)
        ]
        expected = np.float32([
            [0, 0, 0],
            [1.0/3, 1.0/3, 1.0/3],
            [0, 0, 0]
        ])
        for matrices_image in matrices:
            for matrix_channel in matrices_image:
                assert np.allclose(matrix_channel, expected) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_simple_parameters_angle_is_45(self):
        # 45deg angle
        aug = iaa.MotionBlur(k=3, angle=45, direction=0.0, order=0)
        matrix_func = aug.matrix
        matrices = [
            matrix_func(
                np.zeros((128, 128, 3), dtype=np.uint8),
                3,
                iarandom.RNG(i)
            ) for i in range(10)
        ]
        expected = np.float32([
            [0, 0, 1.0/3],
            [0, 1.0/3, 0],
            [1.0/3, 0, 0]
        ])
        for matrices_image in matrices:
            for matrix_channel in matrices_image:
                assert np.allclose(matrix_channel, expected) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_direction_is_1(self):
        # direction 1.0
        aug = iaa.MotionBlur(k=3, angle=0, direction=1.0)
        matrix_func = aug.matrix
        matrices = [
            matrix_func(
                np.zeros((128, 128, 3), dtype=np.uint8),
                3,
                iarandom.RNG(i)
            ) for i in range(10)
        ]
        expected = np.float32([
            [0, 1.0/1.5, 0],
            [0, 0.5/1.5, 0],
            [0, 0.0/1.5, 0]
        ])
        for matrices_image in matrices:
            for matrix_channel in matrices_image:
                assert np.allclose(matrix_channel, expected, rtol=0, atol=1e-2) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_direction_is_minus_1(self):
        # direction -1.0
        aug = iaa.MotionBlur(k=3, angle=0, direction=-1.0)
        matrix_func = aug.matrix
        matrices = [
            matrix_func(
                np.zeros((128, 128, 3), dtype=np.uint8),
                3,
                iarandom.RNG(i)
            ) for i in range(10)
        ]
        expected = np.float32([
            [0, 0.0/1.5, 0],
            [0, 0.5/1.5, 0],
            [0, 1.0/1.5, 0]
        ])
        for matrices_image in matrices:
            for matrix_channel in matrices_image:
                assert np.allclose(matrix_channel, expected, rtol=0, atol=1e-2) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_k_is_3_angle_is_90_verify_results(self):
        # test of actual augmenter
        img = np.zeros((7, 7, 3), dtype=np.uint8)
        img[3-1:3+2, 3-1:3+2, :] = 255
        aug = iaa.MotionBlur(k=3, angle=90, direction=0.0)
        img_aug = aug.augment_image(img)
        v1 = (255*(1/3))
        v2 = (255*(1/3)) * 2
        v3 = (255*(1/3)) * 3
        expected = np.float32([
            [0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0],
            [0, v1, v2, v3, v2, v1, 0],
            [0, v1, v2, v3, v2, v1, 0],
            [0, v1, v2, v3, v2, v1, 0],
            [0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0]
        ]).astype(np.uint8)
        expected = np.tile(expected[..., np.newaxis], (1, 1, 3))
        assert np.allclose(img_aug, expected) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def main():
    image = ia.data.quokka(0.5)
    height, width = image.shape[0], image.shape[1]
    center_x = width // 2
    center_y = height // 2
    r = int(min(image.shape[0], image.shape[1]) / 3)

    cv2.namedWindow("aug", cv2.WINDOW_NORMAL)
    cv2.imshow("aug", image[:, :, ::-1])
    cv2.waitKey(TIME_PER_STEP)

    for angle in cycle(np.arange(0, 360, DEG_PER_STEP)):
        rad = np.deg2rad(angle-90)
        point_x = int(center_x + r * np.cos(rad))
        point_y = int(center_y + r * np.sin(rad))

        aug = iaa.MotionBlur(k=35, angle=angle, direction=-1.0)
        img_aug = aug.augment_image(image)
        img_aug[
            point_y-POINT_SIZE:point_y+POINT_SIZE+1,
            point_x-POINT_SIZE:point_x+POINT_SIZE+1,
            :] = np.array([0, 255, 0])

        aug_inv = iaa.MotionBlur(k=35, angle=angle, direction=1.0)
        img_aug_inv = aug_inv.augment_image(image)
        img_aug_inv[
            point_y - POINT_SIZE:point_y + POINT_SIZE + 1,
            point_x - POINT_SIZE:point_x + POINT_SIZE + 1,
            :] = np.array([0, 255, 0])

        cv2.imshow("aug", np.hstack([img_aug[:, :, ::-1], img_aug_inv[:, :, ::-1]]))
        cv2.waitKey(TIME_PER_STEP) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_simple_parameters_angle_is_list(self):
        # random angle
        aug = iaa.MotionBlur(k=3, angle=[0, 90], direction=0.0)
        matrix_func = aug.matrix
        matrices = [
            matrix_func(
                np.zeros((128, 128, 3), dtype=np.uint8),
                3,
                iarandom.RNG(i)
            ) for i in range(50)
        ]
        expected1 = np.float32([
            [0, 1.0/3, 0],
            [0, 1.0/3, 0],
            [0, 1.0/3, 0]
        ])
        expected2 = np.float32([
            [0, 0, 0],
            [1.0/3, 1.0/3, 1.0/3],
            [0, 0, 0],
        ])
        nb_seen = [0, 0]
        for matrices_image in matrices:
            assert np.allclose(matrices_image[0], matrices_image[1])
            assert np.allclose(matrices_image[1], matrices_image[2])
            for matrix_channel in matrices_image:
                if np.allclose(matrix_channel, expected1):
                    nb_seen[0] += 1
                elif np.allclose(matrix_channel, expected2):
                    nb_seen[1] += 1
        assert nb_seen[0] > 0
        assert nb_seen[1] > 0 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_k_is_list_angle_90(self):
        # random k
        aug = iaa.MotionBlur(k=[3, 5], angle=90, direction=0.0)
        matrix_func = aug.matrix
        matrices = [
            matrix_func(
                np.zeros((128, 128, 3), dtype=np.uint8),
                3,
                iarandom.RNG(i)
            ) for i in range(50)
        ]
        expected1 = np.float32([
            [0, 0, 0],
            [1.0/3, 1.0/3, 1.0/3],
            [0, 0, 0],
        ])
        expected2 = np.float32([
            [0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0],
            [1.0/5, 1.0/5, 1.0/5, 1.0/5, 1.0/5],
            [0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0],
        ])
        nb_seen = [0, 0]
        for matrices_image in matrices:
            assert np.allclose(matrices_image[0], matrices_image[1])
            assert np.allclose(matrices_image[1], matrices_image[2])
            for matrix_channel in matrices_image:
                if (matrix_channel.shape == expected1.shape
                        and np.allclose(matrix_channel, expected1)):
                    nb_seen[0] += 1
                elif (matrix_channel.shape == expected2.shape
                      and np.allclose(matrix_channel, expected2)):
                    nb_seen[1] += 1
        assert nb_seen[0] > 0
        assert nb_seen[1] > 0 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_failure_on_continuous_kernel_sizes(self):
        # k with choice [a, b, c, ...] must error in case of non-discrete
        # values
        got_exception = False
        try:
            _ = iaa.MotionBlur(k=[3, 3.5, 4])
        except Exception as exc:
            assert "to only contain integer" in str(exc)
            got_exception = True
        assert got_exception

    # TODO extend this to test sampled kernel sizes 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_k_is_tuple(self):
        # no error in case of (a, b), checks for #215
        aug = iaa.MotionBlur(k=(3, 7))
        for _ in range(10):
            _ = aug.augment_image(np.zeros((11, 11, 3), dtype=np.uint8)) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def test_pickleable(self):
        aug = iaa.MotionBlur((3, 11), seed=1)
        runtest_pickleable_uint8_img(aug, iterations=10) 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def random_motion_blur(image, prob=.1):
    """
    Random add motion blur on image

    # Arguments
        image: origin image for motion blur
            PIL Image object containing image data
        prob: probability for blur,
            scalar to control the blur probability.

    # Returns
        image: adjusted PIL Image object.
    """
    motion_blur = rand() < prob
    if motion_blur:
        img = np.array(image)
        # random blur severity from 1 to 5
        severity = np.random.randint(1, 6)

        seq = iaa.Sequential([iaa.imgcorruptlike.MotionBlur(severity=severity)])
        #seq = iaa.Sequential([iaa.MotionBlur(k=30)])

        img = seq(images=np.expand_dims(img, 0))
        image = Image.fromarray(img[0])

    return image 

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MotionBlur [as 别名]
def build_augmentation_pipeline(self, height=None, width=None, apply_prob=0.5):
        sometimes = lambda aug: iaa.Sometimes(apply_prob, aug)
        pipeline = iaa.Sequential(random_order=False)
        cfg = self.cfg
        if cfg.get("fliplr", False):
            opt = cfg.get("fliplr", False)
            if type(opt) == int:
                pipeline.add(sometimes(iaa.Fliplr(opt)))
            else:
                pipeline.add(sometimes(iaa.Fliplr(0.5)))
        if cfg.get("rotation", False):
            opt = cfg.get("rotation", False)
            if type(opt) == int:
                pipeline.add(sometimes(iaa.Affine(rotate=(-opt, opt))))
            else:
                pipeline.add(sometimes(iaa.Affine(rotate=(-10, 10))))
        if cfg.get("hist_eq", False):
            pipeline.add(sometimes(iaa.AllChannelsHistogramEqualization()))
        if cfg.get("motion_blur", False):
            opts = cfg.get("motion_blur", False)
            if type(opts) == list:
                opts = dict(opts)
                pipeline.add(sometimes(iaa.MotionBlur(**opts)))
            else:
                pipeline.add(sometimes(iaa.MotionBlur(k=7, angle=(-90, 90))))
        if cfg.get("covering", False):
            pipeline.add(
                sometimes(iaa.CoarseDropout((0, 0.02), size_percent=(0.01, 0.05)))
            )  # , per_channel=0.5)))
        if cfg.get("elastic_transform", False):
            pipeline.add(sometimes(iaa.ElasticTransformation(sigma=5)))
        if cfg.get("gaussian_noise", False):
            opt = cfg.get("gaussian_noise", False)
            if type(opt) == int or type(opt) == float:
                pipeline.add(
                    sometimes(
                        iaa.AdditiveGaussianNoise(
                            loc=0, scale=(0.0, opt), per_channel=0.5
                        )
                    )
                )
            else:
                pipeline.add(
                    sometimes(
                        iaa.AdditiveGaussianNoise(
                            loc=0, scale=(0.0, 0.05 * 255), per_channel=0.5
                        )
                    )
                )
        if height is not None and width is not None:
            pipeline.add(
                iaa.Sometimes(
                    cfg.cropratio, iaa.CropAndPad(percent=(-0.3, 0.1), keep_size=False)
                )
            )
            pipeline.add(iaa.Resize({"height": height, "width": width}))
        return pipeline