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Python augmenters.FrequencyNoiseAlpha方法代码示例

本文整理汇总了Python中imgaug.augmenters.FrequencyNoiseAlpha方法的典型用法代码示例。如果您正苦于以下问题:Python augmenters.FrequencyNoiseAlpha方法的具体用法?Python augmenters.FrequencyNoiseAlpha怎么用?Python augmenters.FrequencyNoiseAlpha使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在imgaug.augmenters的用法示例。


在下文中一共展示了augmenters.FrequencyNoiseAlpha方法的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: test_deprecation_warning

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import FrequencyNoiseAlpha [as 别名]
def test_deprecation_warning(self):
        aug1 = iaa.Sequential([])
        aug2 = iaa.Sequential([])

        with warnings.catch_warnings(record=True) as caught_warnings:
            warnings.simplefilter("always")

            aug = iaa.FrequencyNoiseAlpha(first=aug1, second=aug2)

            assert (
                "is deprecated"
                in str(caught_warnings[-1].message)
            )

        assert isinstance(aug, iaa.BlendAlphaFrequencyNoise)
        assert aug.foreground is aug1
        assert aug.background is aug2 
开发者ID:aleju,项目名称:imgaug,代码行数:19,代码来源:test_blend.py

示例2: __init__

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import FrequencyNoiseAlpha [as 别名]
def __init__(self):
        self.seq = iaa.Sequential([
            iaa.Sometimes(0.5, iaa.OneOf([
                iaa.GaussianBlur((0, 3.0)),  # blur images with a sigma between 0 and 3.0
                iaa.AverageBlur(k=(2, 7)),  # blur image using local means with kernel sizes between 2 and 7
                iaa.MedianBlur(k=(3, 11)),  # blur image using local medians with kernel sizes between 2 and 7
            ])),
            iaa.Sometimes(0.5, iaa.AdditiveGaussianNoise(loc=0, scale=(0.0, 0.05 * 255), per_channel=0.5)),
            iaa.Sometimes(0.5, iaa.Add((-10, 10), per_channel=0.5)),
            iaa.Sometimes(0.5, iaa.AddToHueAndSaturation((-20, 20))),
            iaa.Sometimes(0.5, iaa.FrequencyNoiseAlpha(
                exponent=(-4, 0),
                first=iaa.Multiply((0.5, 1.5), per_channel=True),
                second=iaa.LinearContrast((0.5, 2.0))
            )),
            iaa.Sometimes(0.5, iaa.PiecewiseAffine(scale=(0.01, 0.05))),
            iaa.Sometimes(0.5, iaa.PerspectiveTransform(scale=(0.01, 0.1)))
        ], random_order=True) 
开发者ID:WenmuZhou,项目名称:crnn.gluon,代码行数:20,代码来源:augment.py

示例3: main

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import FrequencyNoiseAlpha [as 别名]
def main():
    nb_rows = 8
    nb_cols = 8
    h, w = (128, 128)
    sample_size = 128

    noise_gens = [
        iap.SimplexNoise(),
        iap.FrequencyNoise(exponent=-4, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=-2, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=0, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=2, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=4, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size),
                           upscale_method=["nearest", "linear", "cubic"]),
        iap.IterativeNoiseAggregator(
            other_param=iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size),
                                           upscale_method=["nearest", "linear", "cubic"]),
            iterations=(1, 3),
            aggregation_method=["max", "avg"]
        ),
        iap.IterativeNoiseAggregator(
            other_param=iap.Sigmoid(
                iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size),
                                   upscale_method=["nearest", "linear", "cubic"]),
                threshold=(-10, 10),
                activated=0.33,
                mul=20,
                add=-10
            ),
            iterations=(1, 3),
            aggregation_method=["max", "avg"]
        )
    ]

    samples = [[] for _ in range(len(noise_gens))]
    for _ in range(nb_rows * nb_cols):
        for i, noise_gen in enumerate(noise_gens):
            samples[i].append(noise_gen.draw_samples((h, w)))

    rows = [np.hstack(row) for row in samples]
    grid = np.vstack(rows)
    ia.imshow((grid*255).astype(np.uint8))

    images = [ia.quokka_square(size=(128, 128)) for _ in range(16)]
    seqs = [
        iaa.SimplexNoiseAlpha(first=iaa.EdgeDetect(1.0)),
        iaa.SimplexNoiseAlpha(first=iaa.EdgeDetect(1.0), per_channel=True),
        iaa.FrequencyNoiseAlpha(first=iaa.EdgeDetect(1.0)),
        iaa.FrequencyNoiseAlpha(first=iaa.EdgeDetect(1.0), per_channel=True)
    ]
    images_aug = []

    for seq in seqs:
        images_aug.append(np.hstack(seq.augment_images(images)))
    images_aug = np.vstack(images_aug)
    ia.imshow(images_aug) 
开发者ID:aleju,项目名称:imgaug,代码行数:59,代码来源:check_noise.py

示例4: get_augmentations

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import FrequencyNoiseAlpha [as 别名]
def get_augmentations():
    # applies the given augmenter in 50% of all cases,
    sometimes = lambda aug: iaa.Sometimes(0.5, aug)

    # Define our sequence of augmentation steps that will be applied to every image
    seq = iaa.Sequential([
            # execute 0 to 5 of the following (less important) augmenters per image
            iaa.SomeOf((0, 5),
                [
                    iaa.OneOf([
                        iaa.GaussianBlur((0, 3.0)),
                        iaa.AverageBlur(k=(2, 7)), 
                        iaa.MedianBlur(k=(3, 11)),
                    ]),
                    iaa.Sharpen(alpha=(0, 1.0), lightness=(0.75, 1.5)),
                    iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0)), 
                    # search either for all edges or for directed edges,
                    # blend the result with the original image using a blobby mask
                    iaa.SimplexNoiseAlpha(iaa.OneOf([
                        iaa.EdgeDetect(alpha=(0.5, 1.0)),
                        iaa.DirectedEdgeDetect(alpha=(0.5, 1.0), direction=(0.0, 1.0)),
                    ])),
                    iaa.AdditiveGaussianNoise(loc=0, scale=(0.0, 0.05*255), per_channel=0.5),
                    iaa.OneOf([
                        iaa.Dropout((0.01, 0.1), per_channel=0.5), # randomly remove up to 10% of the pixels
                        iaa.CoarseDropout((0.03, 0.15), size_percent=(0.02, 0.05), per_channel=0.2),
                    ]),
                    iaa.Add((-10, 10), per_channel=0.5), # change brightness of images (by -10 to 10 of original value)
                    iaa.AddToHueAndSaturation((-20, 20)), # change hue and saturation
                    # either change the brightness of the whole image (sometimes
                    # per channel) or change the brightness of subareas
                    iaa.OneOf([
                        iaa.Multiply((0.5, 1.5), per_channel=0.5),
                        iaa.FrequencyNoiseAlpha(
                            exponent=(-4, 0),
                            first=iaa.Multiply((0.5, 1.5), per_channel=True),
                            second=iaa.ContrastNormalization((0.5, 2.0))
                        )
                    ]),
                    iaa.ContrastNormalization((0.5, 2.0), per_channel=0.5), # improve or worsen the contrast
                    sometimes(iaa.ElasticTransformation(alpha=(0.5, 3.5), sigma=0.25)), # move pixels locally around (with random strengths)
                ],
                random_order=True
            )
        ],
        random_order=True
    )
    return seq

### data transforms 
开发者ID:xl-sr,项目名称:CAL,代码行数:52,代码来源:dataloader.py

示例5: main

# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import FrequencyNoiseAlpha [as 别名]
def main():
    nb_rows = 8
    nb_cols = 8
    h, w = (128, 128)
    sample_size = 128

    noise_gens = [
        iap.SimplexNoise(),
        iap.FrequencyNoise(exponent=-4, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=-2, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=0, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=2, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=4, size_px_max=sample_size, upscale_method="cubic"),
        iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size), upscale_method=["nearest", "linear", "cubic"]),
        iap.IterativeNoiseAggregator(
            other_param=iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size), upscale_method=["nearest", "linear", "cubic"]),
            iterations=(1, 3),
            aggregation_method=["max", "avg"]
        ),
        iap.IterativeNoiseAggregator(
            other_param=iap.Sigmoid(
                iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size), upscale_method=["nearest", "linear", "cubic"]),
                threshold=(-10, 10),
                activated=0.33,
                mul=20,
                add=-10
            ),
            iterations=(1, 3),
            aggregation_method=["max", "avg"]
        )
    ]

    samples = [[] for _ in range(len(noise_gens))]
    for _ in range(nb_rows * nb_cols):
        for i, noise_gen in enumerate(noise_gens):
            samples[i].append(noise_gen.draw_samples((h, w)))

    rows = [np.hstack(row) for row in samples]
    grid = np.vstack(rows)
    misc.imshow((grid*255).astype(np.uint8))

    images = [ia.quokka_square(size=(128, 128)) for _ in range(16)]
    seqs = [
        iaa.SimplexNoiseAlpha(first=iaa.EdgeDetect(1.0)),
        iaa.SimplexNoiseAlpha(first=iaa.EdgeDetect(1.0), per_channel=True),
        iaa.FrequencyNoiseAlpha(first=iaa.EdgeDetect(1.0)),
        iaa.FrequencyNoiseAlpha(first=iaa.EdgeDetect(1.0), per_channel=True)
    ]
    images_aug = []

    for seq in seqs:
        images_aug.append(np.hstack(seq.augment_images(images)))
    images_aug = np.vstack(images_aug)
    misc.imshow(images_aug) 
开发者ID:JoshuaPiinRueyPan,项目名称:ViolenceDetection,代码行数:56,代码来源:check_noise.py


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