예제 #1
0
def chapter_alpha_masks_introduction():
    # -----------------------------------------
    # example introduction
    # -----------------------------------------
    import imgaug as ia
    from imgaug import augmenters as iaa

    ia.seed(2)

    # Example batch of images.
    # The array has shape (8, 128, 128, 3) and dtype uint8.
    images = np.array([ia.quokka(size=(128, 128)) for _ in range(8)],
                      dtype=np.uint8)

    seqs = [
        iaa.BlendAlpha((0.0, 1.0),
                       foreground=iaa.MedianBlur(11),
                       per_channel=True),
        iaa.BlendAlphaSimplexNoise(foreground=iaa.EdgeDetect(1.0),
                                   per_channel=False),
        iaa.BlendAlphaSimplexNoise(foreground=iaa.EdgeDetect(1.0),
                                   background=iaa.LinearContrast((0.5, 2.0)),
                                   per_channel=0.5),
        iaa.BlendAlphaFrequencyNoise(foreground=iaa.Affine(rotate=(-10, 10),
                                                           translate_px={
                                                               "x": (-4, 4),
                                                               "y": (-4, 4)
                                                           }),
                                     background=iaa.AddToHueAndSaturation(
                                         (-40, 40)),
                                     per_channel=0.5),
        iaa.BlendAlphaSimplexNoise(foreground=iaa.BlendAlphaSimplexNoise(
            foreground=iaa.EdgeDetect(1.0),
            background=iaa.LinearContrast((0.5, 2.0)),
            per_channel=True),
                                   background=iaa.BlendAlphaFrequencyNoise(
                                       exponent=(-2.5, -1.0),
                                       foreground=iaa.Affine(rotate=(-10, 10),
                                                             translate_px={
                                                                 "x": (-4, 4),
                                                                 "y": (-4, 4)
                                                             }),
                                       background=iaa.AddToHueAndSaturation(
                                           (-40, 40)),
                                       per_channel=True),
                                   per_channel=True,
                                   aggregation_method="max",
                                   sigmoid=False)
    ]

    cells = []
    for seq in seqs:
        images_aug = seq(images=images)
        cells.extend(images_aug)

    # ------------

    save("alpha", "introduction.jpg", grid(cells, cols=8, rows=5))
 def __init__(self,
              limit=(0.0, 1.0),
              rotate=(-20, 20),
              per_channel=0.5,
              determint=False):
     self.limit = limit
     self.rotate = rotate
     self.per_channel = per_channel
     self.determint = determint
     self.func = iaa.BlendAlpha(limit,
                                iaa.Affine(rotate=rotate),
                                per_channel=per_channel)
def ol_aug(image, mask):
    # ia.seed(seed)

    # Example batch of images.
    # The array has shape (32, 64, 64, 3) and dtype uint8.
    images = image  # B,H,W,C
    masks = mask  # B,H,W,C

    # print('In Aug',images.shape,masks.shape)
    combo = np.concatenate((images, masks), axis=3)
    # print('COMBO: ',combo.shape)

    seq_all = iaa.Sequential([
        iaa.Fliplr(0.5),  # horizontal flips
        # iaa.PadToFixedSize(width=crop_size[0], height=crop_size[1]),
        # iaa.CropToFixedSize(width=crop_size[0], height=crop_size[1]),
        iaa.Affine(
            scale={"x": (0.9, 1.1), "y": (0.9, 1.1)},
            # scale images to 90-110% of their size, individually per axis
            translate_percent={"x": (-0.1, 0.1), "y": (-0.1, 0.1)},
            # translate by -10 to +10 percent (per axis)
            rotate=(-5, 5),  # rotate by -5 to +5 degrees
            shear=(-3, 3),  # shear by -3 to +3 degrees
        ),
        # iaa.Cutout(nb_iterations=(1, 5), size=0.2, cval=0, squared=False),
    ], random_order=False)  # apply augmenters in random order

    seq_f = iaa.Sequential([
        iaa.Sometimes(0.5,
                      iaa.OneOf([
                          iaa.GaussianBlur((0.0, 3.0)),
                          iaa.MotionBlur(k=(3, 20)),
                      ]),
                      ),
        iaa.Sometimes(0.5,
                      iaa.OneOf([
                          iaa.Multiply((0.8, 1.2), per_channel=0.2),
                          iaa.MultiplyBrightness((0.5, 1.5)),
                          iaa.LinearContrast((0.5, 2.0), per_channel=0.2),
                          iaa.BlendAlpha((0., 1.), iaa.HistogramEqualization()),
                          iaa.MultiplyHueAndSaturation((0.5, 1.5), per_channel=0.2),
                      ]),
                      ),
    ], random_order=False)

    combo_aug = np.array(seq_all.augment_images(images=combo))
    # print('combo_au: ', combo_aug.shape)
    images_aug = combo_aug[:, :, :, :3]
    masks_aug = combo_aug[:, :, :, 3:]
    images_aug = seq_f.augment_images(images=images_aug)

    return images_aug, masks_aug
예제 #4
0
def test_dtype_preservation():
    reseed()

    size = (4, 16, 16, 3)
    images = [
        np.random.uniform(0, 255, size).astype(np.uint8),
        np.random.uniform(0, 65535, size).astype(np.uint16),
        np.random.uniform(0, 4294967295, size).astype(np.uint32),
        np.random.uniform(-128, 127, size).astype(np.int16),
        np.random.uniform(-32768, 32767, size).astype(np.int32),
        np.random.uniform(0.0, 1.0, size).astype(np.float32),
        np.random.uniform(-1000.0, 1000.0, size).astype(np.float16),
        np.random.uniform(-1000.0, 1000.0, size).astype(np.float32),
        np.random.uniform(-1000.0, 1000.0, size).astype(np.float64)
    ]

    default_dtypes = set([arr.dtype for arr in images])
    # Some dtypes are here removed per augmenter, because the respective
    # augmenter does not support them. This test currently only checks whether
    # dtypes are preserved from in- to output for all dtypes that are supported
    # per augmenter.
    # dtypes are here removed via list comprehension instead of
    # `default_dtypes - set([dtype])`, because the latter one simply never
    # removed the dtype(s) for some reason

    def _not_dts(dts):
        return [dt for dt in default_dtypes if dt not in dts]

    augs = [
        (iaa.Add((-5, 5), name="Add"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.AddElementwise((-5, 5), name="AddElementwise"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.AdditiveGaussianNoise(0.01*255, name="AdditiveGaussianNoise"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.Multiply((0.95, 1.05), name="Multiply"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.Dropout(0.01, name="Dropout"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.CoarseDropout(0.01, size_px=6, name="CoarseDropout"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.Invert(0.01, per_channel=True, name="Invert"),
         default_dtypes),
        (iaa.GaussianBlur(sigma=(0.95, 1.05), name="GaussianBlur"),
         _not_dts([np.float16])),
        (iaa.AverageBlur((3, 5), name="AverageBlur"),
         _not_dts([np.uint32, np.int32, np.float16])),
        (iaa.MedianBlur((3, 5), name="MedianBlur"),
         _not_dts([np.uint32, np.int32, np.float16, np.float64])),
        (iaa.BilateralBlur((3, 5), name="BilateralBlur"),
         _not_dts([np.uint16, np.uint32, np.int16, np.int32, np.float16,
                   np.float64])),
        (iaa.Sharpen((0.0, 0.1), lightness=(1.0, 1.2), name="Sharpen"),
         _not_dts([np.uint32, np.int32, np.float16, np.uint32])),
        (iaa.Emboss(alpha=(0.0, 0.1), strength=(0.5, 1.5), name="Emboss"),
         _not_dts([np.uint32, np.int32, np.float16, np.uint32])),
        (iaa.EdgeDetect(alpha=(0.0, 0.1), name="EdgeDetect"),
         _not_dts([np.uint32, np.int32, np.float16, np.uint32])),
        (iaa.DirectedEdgeDetect(alpha=(0.0, 0.1), direction=0,
                                name="DirectedEdgeDetect"),
         _not_dts([np.uint32, np.int32, np.float16, np.uint32])),
        (iaa.Fliplr(0.5, name="Fliplr"), default_dtypes),
        (iaa.Flipud(0.5, name="Flipud"), default_dtypes),
        (iaa.Affine(translate_px=(-5, 5), name="Affine-translate-px"),
         _not_dts([np.uint32, np.int32])),
        (iaa.Affine(translate_percent=(-0.05, 0.05),
                    name="Affine-translate-percent"),
         _not_dts([np.uint32, np.int32])),
        (iaa.Affine(rotate=(-20, 20), name="Affine-rotate"),
         _not_dts([np.uint32, np.int32])),
        (iaa.Affine(shear=(-20, 20), name="Affine-shear"),
         _not_dts([np.uint32, np.int32])),
        (iaa.Affine(scale=(0.9, 1.1), name="Affine-scale"),
         _not_dts([np.uint32, np.int32])),
        (iaa.PiecewiseAffine(scale=(0.001, 0.005), name="PiecewiseAffine"),
         default_dtypes),
        (iaa.ElasticTransformation(alpha=(0.1, 0.2), sigma=(0.1, 0.2),
                                   name="ElasticTransformation"),
         _not_dts([np.float16])),
        (iaa.Sequential([iaa.Identity(), iaa.Identity()],
                        name="SequentialNoop"),
         default_dtypes),
        (iaa.SomeOf(1, [iaa.Identity(), iaa.Identity()], name="SomeOfNoop"),
         default_dtypes),
        (iaa.OneOf([iaa.Identity(), iaa.Identity()], name="OneOfNoop"),
         default_dtypes),
        (iaa.Sometimes(0.5, iaa.Identity(), name="SometimesNoop"),
         default_dtypes),
        (iaa.Sequential([iaa.Add((-5, 5)), iaa.AddElementwise((-5, 5))],
                        name="Sequential"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.SomeOf(1,
                    [iaa.Add((-5, 5)), iaa.AddElementwise((-5, 5))],
                    name="SomeOf"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.OneOf([iaa.Add((-5, 5)), iaa.AddElementwise((-5, 5))],
                   name="OneOf"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.Sometimes(0.5, iaa.Add((-5, 5)), name="Sometimes"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.Identity(name="Identity"), default_dtypes),
        (iaa.BlendAlpha((0.0, 0.1), iaa.Identity(), name="BlendAlphaIdentity"),
         _not_dts([np.float64])),  # float64 requires float128 support
        (iaa.BlendAlphaElementwise((0.0, 0.1), iaa.Identity(),
                                   name="BlendAlphaElementwiseIdentity"),
         _not_dts([np.float64])),  # float64 requires float128 support
        (iaa.BlendAlphaSimplexNoise(iaa.Identity(),
                                    name="BlendAlphaSimplexNoiseIdentity"),
         _not_dts([np.float64])),  # float64 requires float128 support
        (iaa.BlendAlphaFrequencyNoise(exponent=(-2, 2),
                                      foreground=iaa.Identity(),
                                      name="BlendAlphaFrequencyNoiseIdentity"),
         _not_dts([np.float64])),
        (iaa.BlendAlpha((0.0, 0.1), iaa.Add(10), name="BlendAlpha"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.BlendAlphaElementwise((0.0, 0.1), iaa.Add(10),
                                   name="BlendAlphaElementwise"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.BlendAlphaSimplexNoise(iaa.Add(10), name="BlendAlphaSimplexNoise"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.BlendAlphaFrequencyNoise(exponent=(-2, 2),
                                      foreground=iaa.Add(10),
                                      name="BlendAlphaFrequencyNoise"),
         _not_dts([np.uint32, np.int32, np.float64])),
        (iaa.Superpixels(p_replace=0.01, n_segments=64),
         _not_dts([np.float16, np.float32, np.float64])),
        (iaa.Resize({"height": 4, "width": 4}, name="Resize"),
         _not_dts([np.uint16, np.uint32, np.int16, np.int32, np.float32,
                   np.float16, np.float64])),
        (iaa.CropAndPad(px=(-10, 10), name="CropAndPad"),
         _not_dts([np.uint16, np.uint32, np.int16, np.int32, np.float32,
                   np.float16, np.float64])),
        (iaa.Pad(px=(0, 10), name="Pad"),
         _not_dts([np.uint16, np.uint32, np.int16, np.int32, np.float32,
                   np.float16, np.float64])),
        (iaa.Crop(px=(0, 10), name="Crop"),
         _not_dts([np.uint16, np.uint32, np.int16, np.int32, np.float32,
                   np.float16, np.float64]))
    ]

    for (aug, allowed_dtypes) in augs:
        for images_i in images:
            if images_i.dtype in allowed_dtypes:
                images_aug = aug.augment_images(images_i)
                assert images_aug.dtype == images_i.dtype
예제 #5
0
def test_unusual_channel_numbers():
    reseed()

    images = [
        (0, create_random_images((4, 16, 16))),
        (1, create_random_images((4, 16, 16, 1))),
        (2, create_random_images((4, 16, 16, 2))),
        (4, create_random_images((4, 16, 16, 4))),
        (5, create_random_images((4, 16, 16, 5))),
        (10, create_random_images((4, 16, 16, 10))),
        (20, create_random_images((4, 16, 16, 20)))
    ]

    augs = [
        iaa.Add((-5, 5), name="Add"),
        iaa.AddElementwise((-5, 5), name="AddElementwise"),
        iaa.AdditiveGaussianNoise(0.01*255, name="AdditiveGaussianNoise"),
        iaa.Multiply((0.95, 1.05), name="Multiply"),
        iaa.Dropout(0.01, name="Dropout"),
        iaa.CoarseDropout(0.01, size_px=6, name="CoarseDropout"),
        iaa.Invert(0.01, per_channel=True, name="Invert"),
        iaa.GaussianBlur(sigma=(0.95, 1.05), name="GaussianBlur"),
        iaa.AverageBlur((3, 5), name="AverageBlur"),
        iaa.MedianBlur((3, 5), name="MedianBlur"),
        iaa.Sharpen((0.0, 0.1), lightness=(1.0, 1.2), name="Sharpen"),
        iaa.Emboss(alpha=(0.0, 0.1), strength=(0.5, 1.5), name="Emboss"),
        iaa.EdgeDetect(alpha=(0.0, 0.1), name="EdgeDetect"),
        iaa.DirectedEdgeDetect(alpha=(0.0, 0.1), direction=0,
                               name="DirectedEdgeDetect"),
        iaa.Fliplr(0.5, name="Fliplr"),
        iaa.Flipud(0.5, name="Flipud"),
        iaa.Affine(translate_px=(-5, 5), name="Affine-translate-px"),
        iaa.Affine(translate_percent=(-0.05, 0.05),
                   name="Affine-translate-percent"),
        iaa.Affine(rotate=(-20, 20), name="Affine-rotate"),
        iaa.Affine(shear=(-20, 20), name="Affine-shear"),
        iaa.Affine(scale=(0.9, 1.1), name="Affine-scale"),
        iaa.PiecewiseAffine(scale=(0.001, 0.005), name="PiecewiseAffine"),
        iaa.PerspectiveTransform(scale=(0.01, 0.10),
                                 name="PerspectiveTransform"),
        iaa.ElasticTransformation(alpha=(0.1, 0.2), sigma=(0.1, 0.2),
                                  name="ElasticTransformation"),
        iaa.Sequential([iaa.Add((-5, 5)), iaa.AddElementwise((-5, 5))]),
        iaa.SomeOf(1, [iaa.Add((-5, 5)), iaa.AddElementwise((-5, 5))]),
        iaa.OneOf([iaa.Add((-5, 5)), iaa.AddElementwise((-5, 5))]),
        iaa.Sometimes(0.5, iaa.Add((-5, 5)), name="Sometimes"),
        iaa.Identity(name="Noop"),
        iaa.BlendAlpha((0.0, 0.1), iaa.Add(10), name="BlendAlpha"),
        iaa.BlendAlphaElementwise((0.0, 0.1), iaa.Add(10),
                                  name="BlendAlphaElementwise"),
        iaa.BlendAlphaSimplexNoise(iaa.Add(10), name="BlendAlphaSimplexNoise"),
        iaa.BlendAlphaFrequencyNoise(exponent=(-2, 2),
                                     foreground=iaa.Add(10),
                                     name="BlendAlphaSimplexNoise"),
        iaa.Superpixels(p_replace=0.01, n_segments=64),
        iaa.Resize({"height": 4, "width": 4}, name="Resize"),
        iaa.CropAndPad(px=(-10, 10), name="CropAndPad"),
        iaa.Pad(px=(0, 10), name="Pad"),
        iaa.Crop(px=(0, 10), name="Crop")
    ]

    for aug in augs:
        for (nb_channels, images_c) in images:
            if aug.name != "Resize":
                images_aug = aug.augment_images(images_c)
                assert images_aug.shape == images_c.shape
                image_aug = aug.augment_image(images_c[0])
                assert image_aug.shape == images_c[0].shape
            else:
                images_aug = aug.augment_images(images_c)
                image_aug = aug.augment_image(images_c[0])
                if images_c.ndim == 3:
                    assert images_aug.shape == (4, 4, 4)
                    assert image_aug.shape == (4, 4)
                else:
                    assert images_aug.shape == (4, 4, 4, images_c.shape[3])
                    assert image_aug.shape == (4, 4, images_c.shape[3])
예제 #6
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    def test_many_augmenters(self):
        keypoints = []
        for y in sm.xrange(40//5):
            for x in sm.xrange(60//5):
                keypoints.append(ia.Keypoint(y=y*5, x=x*5))

        keypoints_oi = ia.KeypointsOnImage(keypoints, shape=(40, 60, 3))
        keypoints_oi_empty = ia.KeypointsOnImage([], shape=(40, 60, 3))

        augs = [
            iaa.Add((-5, 5), name="Add"),
            iaa.AddElementwise((-5, 5), name="AddElementwise"),
            iaa.AdditiveGaussianNoise(0.01*255, name="AdditiveGaussianNoise"),
            iaa.Multiply((0.95, 1.05), name="Multiply"),
            iaa.Dropout(0.01, name="Dropout"),
            iaa.CoarseDropout(0.01, size_px=6, name="CoarseDropout"),
            iaa.Invert(0.01, per_channel=True, name="Invert"),
            iaa.GaussianBlur(sigma=(0.95, 1.05), name="GaussianBlur"),
            iaa.AverageBlur((3, 5), name="AverageBlur"),
            iaa.MedianBlur((3, 5), name="MedianBlur"),
            iaa.Sharpen((0.0, 0.1), lightness=(1.0, 1.2), name="Sharpen"),
            iaa.Emboss(alpha=(0.0, 0.1), strength=(0.5, 1.5), name="Emboss"),
            iaa.EdgeDetect(alpha=(0.0, 0.1), name="EdgeDetect"),
            iaa.DirectedEdgeDetect(alpha=(0.0, 0.1), direction=0,
                                   name="DirectedEdgeDetect"),
            iaa.Fliplr(0.5, name="Fliplr"),
            iaa.Flipud(0.5, name="Flipud"),
            iaa.Affine(translate_px=(-5, 5), name="Affine-translate-px"),
            iaa.Affine(translate_percent=(-0.05, 0.05),
                       name="Affine-translate-percent"),
            iaa.Affine(rotate=(-20, 20), name="Affine-rotate"),
            iaa.Affine(shear=(-20, 20), name="Affine-shear"),
            iaa.Affine(scale=(0.9, 1.1), name="Affine-scale"),
            iaa.PiecewiseAffine(scale=(0.001, 0.005), name="PiecewiseAffine"),
            iaa.ElasticTransformation(alpha=(0.1, 0.2), sigma=(0.1, 0.2),
                                      name="ElasticTransformation"),
            iaa.BlendAlpha((0.0, 0.1), iaa.Add(10), name="BlendAlpha"),
            iaa.BlendAlphaElementwise((0.0, 0.1), iaa.Add(10),
                                      name="BlendAlphaElementwise"),
            iaa.BlendAlphaSimplexNoise(iaa.Add(10), name="BlendAlphaSimplexNoise"),
            iaa.BlendAlphaFrequencyNoise(exponent=(-2, 2), foreground=iaa.Add(10),
                                         name="BlendAlphaSimplexNoise"),
            iaa.Superpixels(p_replace=0.01, n_segments=64),
            iaa.Resize(0.5, name="Resize"),
            iaa.CropAndPad(px=(-10, 10), name="CropAndPad"),
            iaa.Pad(px=(0, 10), name="Pad"),
            iaa.Crop(px=(0, 10), name="Crop")
        ]

        for aug in augs:
            dss = []
            for i in sm.xrange(10):
                aug_det = aug.to_deterministic()

                kp_fully_empty_aug = aug_det.augment_keypoints([])
                assert kp_fully_empty_aug == []

                kp_first_empty_aug = aug_det.augment_keypoints(keypoints_oi_empty)
                assert len(kp_first_empty_aug.keypoints) == 0

                kp_image = keypoints_oi.to_keypoint_image(size=5)
                with assertWarns(self, iaa.SuspiciousSingleImageShapeWarning):
                    kp_image_aug = aug_det.augment_image(kp_image)
                kp_image_aug_rev = ia.KeypointsOnImage.from_keypoint_image(
                    kp_image_aug,
                    if_not_found_coords={"x": -9999, "y": -9999},
                    nb_channels=1
                )
                kp_aug = aug_det.augment_keypoints([keypoints_oi])[0]
                ds = []
                assert len(kp_image_aug_rev.keypoints) == len(kp_aug.keypoints), (
                    "Lost keypoints for '%s' (%d vs expected %d)" % (
                        aug.name,
                        len(kp_aug.keypoints),
                        len(kp_image_aug_rev.keypoints))
                )

                gen = zip(kp_aug.keypoints, kp_image_aug_rev.keypoints)
                for kp_pred, kp_pred_img in gen:
                    kp_pred_lost = (kp_pred.x == -9999 and kp_pred.y == -9999)
                    kp_pred_img_lost = (kp_pred_img.x == -9999
                                        and kp_pred_img.y == -9999)

                    if not kp_pred_lost and not kp_pred_img_lost:
                        d = np.sqrt((kp_pred.x - kp_pred_img.x) ** 2
                                    + (kp_pred.y - kp_pred_img.y) ** 2)
                        ds.append(d)
                dss.extend(ds)
                if len(ds) == 0:
                    print("[INFO] No valid keypoints found for '%s' "
                          "in test_keypoint_augmentation()" % (str(aug),))
            assert np.average(dss) < 5.0, \
                "Average distance too high (%.2f, with ds: %s)" \
                % (np.average(dss), str(dss))
    def __init__(self,  rgb_mean, randomImg, insize):
        sometimes = lambda aug: iaa.Sometimes(0.7, aug)
        self.rand_img_dir = randomImg
        self.rgb_mean = rgb_mean
        self.inp_dim = insize
        #
        self.randomImgList = glob.glob( randomImg + '*.jpg')

        self.aug = iaa.Sequential([
        sometimes(iaa.Affine(
            scale={"x": (0.8, 1.2), "y": (0.8, 1.2)}, # scale images to 80-120% of their size, individually per axis
            translate_percent={"x": (-0.1, 0.1), "y": (-0.1, 0.1)}, # translate by -20 to +20 percent (per axis)
            rotate=(-25, 25), # rotate by -45 to +45 degrees
            shear=(-6, 6), # shear by -16 to +16 degrees
            order=[0, 1], # use nearest neighbour or bilinear interpolation (fast)
            cval=(0, 255), # if mode is constant, use a cval between 0 and 255
            mode=ia.ALL # use any of scikit-image's warping modes (see 2nd image from the top for examples)
        )),

        iaa.OneOf([
            iaa.Fliplr(0.5),

            iaa.GaussianBlur(
                sigma=iap.Uniform(0.0, 1.0)
            ),

            iaa.BlendAlphaSimplexNoise(
                foreground=iaa.BlendAlphaSimplexNoise(
                    foreground=iaa.EdgeDetect(1.0),
                    background=iaa.LinearContrast((0.1, .8)),
                    per_channel=True
                ),
                background=iaa.BlendAlphaFrequencyNoise(
                    exponent=(-.5, -.1),
                    foreground=iaa.Affine(
                        rotate=(-10, 10),
                        translate_px={"x": (-1, 1), "y": (-1, 1)}
                    ),
                    # background=iaa.AddToHueAndSaturation((-4, 4)),
                    # per_channel=True
                ),
                per_channel=True,
                aggregation_method="max",
                sigmoid=False
            ),

        iaa.BlendAlpha(
            factor=(0.2, 0.8),
            foreground=iaa.Sharpen(1.0, lightness=2),
            background=iaa.CoarseDropout(p=0.1, size_px=8)
        ),

        iaa.BlendAlpha(
            factor=(0.2, 0.8),
            foreground=iaa.Affine(rotate=(-5, 5)),
            per_channel=True
        ),
        iaa.MotionBlur(k=15, angle=[-5, 5]),
        iaa.BlendAlphaCheckerboard(nb_rows=2, nb_cols=(1, 4),
                                       foreground=iaa.AddToHue((-10, 10))),
        iaa.BlendAlphaElementwise((0, 1.0), iaa.AddToHue(10)),
        iaa.BilateralBlur(
                d=(3, 10), sigma_color=(1, 5), sigma_space=(1, 5)),
        iaa.AdditiveGaussianNoise(scale=0.02 * 255),
        iaa.AddElementwise((-5, 5), per_channel=0.5),
        iaa.AdditiveLaplaceNoise(scale=0.01 * 255),
        iaa.AdditivePoissonNoise(20),
        iaa.Cutout(fill_mode="gaussian", fill_per_channel=True),
        iaa.CoarseDropout(0.02, size_percent=0.1),
        iaa.SaltAndPepper(0.1, per_channel=True),
        iaa.JpegCompression(compression=(70, 99)),
        iaa.ImpulseNoise(0.02),
        iaa.Dropout(p=(0, 0.04)),
        iaa.Sharpen(alpha=0.1),
        ]) # oneof

        ])
예제 #8
0
def create_augmenters(height, width, height_augmentable, width_augmentable, only_augmenters):
    def lambda_func_images(images, random_state, parents, hooks):
        return images

    def lambda_func_heatmaps(heatmaps, random_state, parents, hooks):
        return heatmaps

    def lambda_func_keypoints(keypoints, random_state, parents, hooks):
        return keypoints

    def assertlambda_func_images(images, random_state, parents, hooks):
        return True

    def assertlambda_func_heatmaps(heatmaps, random_state, parents, hooks):
        return True

    def assertlambda_func_keypoints(keypoints, random_state, parents, hooks):
        return True

    augmenters_meta = [
        iaa.Sequential([iaa.Noop(), iaa.Noop()], random_order=False, name="Sequential_2xNoop"),
        iaa.Sequential([iaa.Noop(), iaa.Noop()], random_order=True, name="Sequential_2xNoop_random_order"),
        iaa.SomeOf((1, 3), [iaa.Noop(), iaa.Noop(), iaa.Noop()], random_order=False, name="SomeOf_3xNoop"),
        iaa.SomeOf((1, 3), [iaa.Noop(), iaa.Noop(), iaa.Noop()], random_order=True, name="SomeOf_3xNoop_random_order"),
        iaa.OneOf([iaa.Noop(), iaa.Noop(), iaa.Noop()], name="OneOf_3xNoop"),
        iaa.Sometimes(0.5, iaa.Noop(), name="Sometimes_Noop"),
        iaa.WithChannels([1, 2], iaa.Noop(), name="WithChannels_1_and_2_Noop"),
        iaa.Identity(name="Identity"),
        iaa.Noop(name="Noop"),
        iaa.Lambda(func_images=lambda_func_images, func_heatmaps=lambda_func_heatmaps, func_keypoints=lambda_func_keypoints,
                   name="Lambda"),
        iaa.AssertLambda(func_images=assertlambda_func_images, func_heatmaps=assertlambda_func_heatmaps,
                         func_keypoints=assertlambda_func_keypoints, name="AssertLambda"),
        iaa.AssertShape((None, height_augmentable, width_augmentable, None), name="AssertShape"),
        iaa.ChannelShuffle(0.5, name="ChannelShuffle")
    ]
    augmenters_arithmetic = [
        iaa.Add((-10, 10), name="Add"),
        iaa.AddElementwise((-10, 10), name="AddElementwise"),
        #iaa.AddElementwise((-500, 500), name="AddElementwise"),
        iaa.AdditiveGaussianNoise(scale=(5, 10), name="AdditiveGaussianNoise"),
        iaa.AdditiveLaplaceNoise(scale=(5, 10), name="AdditiveLaplaceNoise"),
        iaa.AdditivePoissonNoise(lam=(1, 5), name="AdditivePoissonNoise"),
        iaa.Multiply((0.5, 1.5), name="Multiply"),
        iaa.MultiplyElementwise((0.5, 1.5), name="MultiplyElementwise"),
        iaa.Cutout(nb_iterations=1, name="Cutout-fill_constant"),
        iaa.Dropout((0.01, 0.05), name="Dropout"),
        iaa.CoarseDropout((0.01, 0.05), size_percent=(0.01, 0.1), name="CoarseDropout"),
        iaa.Dropout2d(0.1, name="Dropout2d"),
        iaa.TotalDropout(0.1, name="TotalDropout"),
        iaa.ReplaceElementwise((0.01, 0.05), (0, 255), name="ReplaceElementwise"),
        #iaa.ReplaceElementwise((0.95, 0.99), (0, 255), name="ReplaceElementwise"),
        iaa.SaltAndPepper((0.01, 0.05), name="SaltAndPepper"),
        iaa.ImpulseNoise((0.01, 0.05), name="ImpulseNoise"),
        iaa.CoarseSaltAndPepper((0.01, 0.05), size_percent=(0.01, 0.1), name="CoarseSaltAndPepper"),
        iaa.Salt((0.01, 0.05), name="Salt"),
        iaa.CoarseSalt((0.01, 0.05), size_percent=(0.01, 0.1), name="CoarseSalt"),
        iaa.Pepper((0.01, 0.05), name="Pepper"),
        iaa.CoarsePepper((0.01, 0.05), size_percent=(0.01, 0.1), name="CoarsePepper"),
        iaa.Invert(0.1, name="Invert"),
        # ContrastNormalization
        iaa.JpegCompression((50, 99), name="JpegCompression")
    ]
    augmenters_artistic = [
        iaa.Cartoon(name="Cartoon")
    ]
    augmenters_blend = [
        iaa.BlendAlpha((0.01, 0.99), iaa.Identity(), name="Alpha"),
        iaa.BlendAlphaElementwise((0.01, 0.99), iaa.Identity(), name="AlphaElementwise"),
        iaa.BlendAlphaSimplexNoise(iaa.Identity(), name="SimplexNoiseAlpha"),
        iaa.BlendAlphaFrequencyNoise((-2.0, 2.0), iaa.Identity(), name="FrequencyNoiseAlpha"),
        iaa.BlendAlphaSomeColors(iaa.Identity(), name="BlendAlphaSomeColors"),
        iaa.BlendAlphaHorizontalLinearGradient(iaa.Identity(), name="BlendAlphaHorizontalLinearGradient"),
        iaa.BlendAlphaVerticalLinearGradient(iaa.Identity(), name="BlendAlphaVerticalLinearGradient"),
        iaa.BlendAlphaRegularGrid(nb_rows=(2, 8), nb_cols=(2, 8), foreground=iaa.Identity(), name="BlendAlphaRegularGrid"),
        iaa.BlendAlphaCheckerboard(nb_rows=(2, 8), nb_cols=(2, 8), foreground=iaa.Identity(), name="BlendAlphaCheckerboard"),
        # TODO BlendAlphaSegMapClassId
        # TODO BlendAlphaBoundingBoxes
    ]
    augmenters_blur = [
        iaa.GaussianBlur(sigma=(1.0, 5.0), name="GaussianBlur"),
        iaa.AverageBlur(k=(3, 11), name="AverageBlur"),
        iaa.MedianBlur(k=(3, 11), name="MedianBlur"),
        iaa.BilateralBlur(d=(3, 11), name="BilateralBlur"),
        iaa.MotionBlur(k=(3, 11), name="MotionBlur"),
        iaa.MeanShiftBlur(spatial_radius=(5.0, 40.0), color_radius=(5.0, 40.0),
                          name="MeanShiftBlur")
    ]
    augmenters_collections = [
        iaa.RandAugment(n=2, m=(6, 12), name="RandAugment")
    ]
    augmenters_color = [
        # InColorspace (deprecated)
        iaa.WithColorspace(to_colorspace="HSV", children=iaa.Noop(), name="WithColorspace"),
        iaa.WithBrightnessChannels(iaa.Identity(), name="WithBrightnessChannels"),
        iaa.MultiplyAndAddToBrightness(mul=(0.7, 1.3), add=(-30, 30), name="MultiplyAndAddToBrightness"),
        iaa.MultiplyBrightness((0.7, 1.3), name="MultiplyBrightness"),
        iaa.AddToBrightness((-30, 30), name="AddToBrightness"),
        iaa.WithHueAndSaturation(children=iaa.Noop(), name="WithHueAndSaturation"),
        iaa.MultiplyHueAndSaturation((0.8, 1.2), name="MultiplyHueAndSaturation"),
        iaa.MultiplyHue((-1.0, 1.0), name="MultiplyHue"),
        iaa.MultiplySaturation((0.8, 1.2), name="MultiplySaturation"),
        iaa.RemoveSaturation((0.01, 0.99), name="RemoveSaturation"),
        iaa.AddToHueAndSaturation((-10, 10), name="AddToHueAndSaturation"),
        iaa.AddToHue((-10, 10), name="AddToHue"),
        iaa.AddToSaturation((-10, 10), name="AddToSaturation"),
        iaa.ChangeColorspace(to_colorspace="HSV", name="ChangeColorspace"),
        iaa.Grayscale((0.01, 0.99), name="Grayscale"),
        iaa.KMeansColorQuantization((2, 16), name="KMeansColorQuantization"),
        iaa.UniformColorQuantization((2, 16), name="UniformColorQuantization"),
        iaa.UniformColorQuantizationToNBits((1, 7), name="UniformQuantizationToNBits"),
        iaa.Posterize((1, 7), name="Posterize")
    ]
    augmenters_contrast = [
        iaa.GammaContrast(gamma=(0.5, 2.0), name="GammaContrast"),
        iaa.SigmoidContrast(gain=(5, 20), cutoff=(0.25, 0.75), name="SigmoidContrast"),
        iaa.LogContrast(gain=(0.7, 1.0), name="LogContrast"),
        iaa.LinearContrast((0.5, 1.5), name="LinearContrast"),
        iaa.AllChannelsCLAHE(clip_limit=(2, 10), tile_grid_size_px=(3, 11), name="AllChannelsCLAHE"),
        iaa.CLAHE(clip_limit=(2, 10), tile_grid_size_px=(3, 11), to_colorspace="HSV", name="CLAHE"),
        iaa.AllChannelsHistogramEqualization(name="AllChannelsHistogramEqualization"),
        iaa.HistogramEqualization(to_colorspace="HSV", name="HistogramEqualization"),
    ]
    augmenters_convolutional = [
        iaa.Convolve(np.float32([[0, 0, 0], [0, 1, 0], [0, 0, 0]]), name="Convolve_3x3"),
        iaa.Sharpen(alpha=(0.01, 0.99), lightness=(0.5, 2), name="Sharpen"),
        iaa.Emboss(alpha=(0.01, 0.99), strength=(0, 2), name="Emboss"),
        iaa.EdgeDetect(alpha=(0.01, 0.99), name="EdgeDetect"),
        iaa.DirectedEdgeDetect(alpha=(0.01, 0.99), name="DirectedEdgeDetect")
    ]
    augmenters_edges = [
        iaa.Canny(alpha=(0.01, 0.99), name="Canny")
    ]
    augmenters_flip = [
        iaa.Fliplr(1.0, name="Fliplr"),
        iaa.Flipud(1.0, name="Flipud")
    ]
    augmenters_geometric = [
        iaa.Affine(scale=(0.9, 1.1), translate_percent={"x": (-0.05, 0.05), "y": (-0.05, 0.05)}, rotate=(-10, 10),
                   shear=(-10, 10), order=0, mode="constant", cval=(0, 255), name="Affine_order_0_constant"),
        iaa.Affine(scale=(0.9, 1.1), translate_percent={"x": (-0.05, 0.05), "y": (-0.05, 0.05)}, rotate=(-10, 10),
                   shear=(-10, 10), order=1, mode="constant", cval=(0, 255), name="Affine_order_1_constant"),
        iaa.Affine(scale=(0.9, 1.1), translate_percent={"x": (-0.05, 0.05), "y": (-0.05, 0.05)}, rotate=(-10, 10),
                   shear=(-10, 10), order=3, mode="constant", cval=(0, 255), name="Affine_order_3_constant"),
        iaa.Affine(scale=(0.9, 1.1), translate_percent={"x": (-0.05, 0.05), "y": (-0.05, 0.05)}, rotate=(-10, 10),
                   shear=(-10, 10), order=1, mode="edge", cval=(0, 255), name="Affine_order_1_edge"),
        iaa.Affine(scale=(0.9, 1.1), translate_percent={"x": (-0.05, 0.05), "y": (-0.05, 0.05)}, rotate=(-10, 10),
                   shear=(-10, 10), order=1, mode="constant", cval=(0, 255), backend="skimage",
                   name="Affine_order_1_constant_skimage"),
        iaa.PiecewiseAffine(scale=(0.01, 0.05), nb_rows=4, nb_cols=4, order=1, mode="constant",
                            name="PiecewiseAffine_4x4_order_1_constant"),
        iaa.PiecewiseAffine(scale=(0.01, 0.05), nb_rows=4, nb_cols=4, order=0, mode="constant",
                            name="PiecewiseAffine_4x4_order_0_constant"),
        iaa.PiecewiseAffine(scale=(0.01, 0.05), nb_rows=4, nb_cols=4, order=1, mode="edge",
                            name="PiecewiseAffine_4x4_order_1_edge"),
        iaa.PiecewiseAffine(scale=(0.01, 0.05), nb_rows=8, nb_cols=8, order=1, mode="constant",
                            name="PiecewiseAffine_8x8_order_1_constant"),
        iaa.PerspectiveTransform(scale=(0.01, 0.05), keep_size=False, name="PerspectiveTransform"),
        iaa.PerspectiveTransform(scale=(0.01, 0.05), keep_size=True, name="PerspectiveTransform_keep_size"),
        iaa.ElasticTransformation(alpha=(1, 10), sigma=(0.5, 1.5), order=0, mode="constant", cval=0,
                                  name="ElasticTransformation_order_0_constant"),
        iaa.ElasticTransformation(alpha=(1, 10), sigma=(0.5, 1.5), order=1, mode="constant", cval=0,
                                  name="ElasticTransformation_order_1_constant"),
        iaa.ElasticTransformation(alpha=(1, 10), sigma=(0.5, 1.5), order=1, mode="nearest", cval=0,
                                  name="ElasticTransformation_order_1_nearest"),
        iaa.ElasticTransformation(alpha=(1, 10), sigma=(0.5, 1.5), order=1, mode="reflect", cval=0,
                                  name="ElasticTransformation_order_1_reflect"),
        iaa.Rot90((1, 3), keep_size=False, name="Rot90"),
        iaa.Rot90((1, 3), keep_size=True, name="Rot90_keep_size"),
        iaa.WithPolarWarping(iaa.Identity(), name="WithPolarWarping"),
        iaa.Jigsaw(nb_rows=(3, 8), nb_cols=(3, 8), max_steps=1, name="Jigsaw")
    ]
    augmenters_pooling = [
        iaa.AveragePooling(kernel_size=(1, 16), keep_size=False, name="AveragePooling"),
        iaa.AveragePooling(kernel_size=(1, 16), keep_size=True, name="AveragePooling_keep_size"),
        iaa.MaxPooling(kernel_size=(1, 16), keep_size=False, name="MaxPooling"),
        iaa.MaxPooling(kernel_size=(1, 16), keep_size=True, name="MaxPooling_keep_size"),
        iaa.MinPooling(kernel_size=(1, 16), keep_size=False, name="MinPooling"),
        iaa.MinPooling(kernel_size=(1, 16), keep_size=True, name="MinPooling_keep_size"),
        iaa.MedianPooling(kernel_size=(1, 16), keep_size=False, name="MedianPooling"),
        iaa.MedianPooling(kernel_size=(1, 16), keep_size=True, name="MedianPooling_keep_size")
    ]
    augmenters_imgcorruptlike = [
        iaa.imgcorruptlike.GaussianNoise(severity=(1, 5), name="imgcorruptlike.GaussianNoise"),
        iaa.imgcorruptlike.ShotNoise(severity=(1, 5), name="imgcorruptlike.ShotNoise"),
        iaa.imgcorruptlike.ImpulseNoise(severity=(1, 5), name="imgcorruptlike.ImpulseNoise"),
        iaa.imgcorruptlike.SpeckleNoise(severity=(1, 5), name="imgcorruptlike.SpeckleNoise"),
        iaa.imgcorruptlike.GaussianBlur(severity=(1, 5), name="imgcorruptlike.GaussianBlur"),
        iaa.imgcorruptlike.GlassBlur(severity=(1, 5), name="imgcorruptlike.GlassBlur"),
        iaa.imgcorruptlike.DefocusBlur(severity=(1, 5), name="imgcorruptlike.DefocusBlur"),
        iaa.imgcorruptlike.MotionBlur(severity=(1, 5), name="imgcorruptlike.MotionBlur"),
        iaa.imgcorruptlike.ZoomBlur(severity=(1, 5), name="imgcorruptlike.ZoomBlur"),
        iaa.imgcorruptlike.Fog(severity=(1, 5), name="imgcorruptlike.Fog"),
        iaa.imgcorruptlike.Frost(severity=(1, 5), name="imgcorruptlike.Frost"),
        iaa.imgcorruptlike.Snow(severity=(1, 5), name="imgcorruptlike.Snow"),
        iaa.imgcorruptlike.Spatter(severity=(1, 5), name="imgcorruptlike.Spatter"),
        iaa.imgcorruptlike.Contrast(severity=(1, 5), name="imgcorruptlike.Contrast"),
        iaa.imgcorruptlike.Brightness(severity=(1, 5), name="imgcorruptlike.Brightness"),
        iaa.imgcorruptlike.Saturate(severity=(1, 5), name="imgcorruptlike.Saturate"),
        iaa.imgcorruptlike.JpegCompression(severity=(1, 5), name="imgcorruptlike.JpegCompression"),
        iaa.imgcorruptlike.Pixelate(severity=(1, 5), name="imgcorruptlike.Pixelate"),
        iaa.imgcorruptlike.ElasticTransform(severity=(1, 5), name="imgcorruptlike.ElasticTransform")
    ]
    augmenters_pillike = [
        iaa.pillike.Solarize(p=1.0, threshold=(32, 128), name="pillike.Solarize"),
        iaa.pillike.Posterize((1, 7), name="pillike.Posterize"),
        iaa.pillike.Equalize(name="pillike.Equalize"),
        iaa.pillike.Autocontrast(name="pillike.Autocontrast"),
        iaa.pillike.EnhanceColor((0.0, 3.0), name="pillike.EnhanceColor"),
        iaa.pillike.EnhanceContrast((0.0, 3.0), name="pillike.EnhanceContrast"),
        iaa.pillike.EnhanceBrightness((0.0, 3.0), name="pillike.EnhanceBrightness"),
        iaa.pillike.EnhanceSharpness((0.0, 3.0), name="pillike.EnhanceSharpness"),
        iaa.pillike.FilterBlur(name="pillike.FilterBlur"),
        iaa.pillike.FilterSmooth(name="pillike.FilterSmooth"),
        iaa.pillike.FilterSmoothMore(name="pillike.FilterSmoothMore"),
        iaa.pillike.FilterEdgeEnhance(name="pillike.FilterEdgeEnhance"),
        iaa.pillike.FilterEdgeEnhanceMore(name="pillike.FilterEdgeEnhanceMore"),
        iaa.pillike.FilterFindEdges(name="pillike.FilterFindEdges"),
        iaa.pillike.FilterContour(name="pillike.FilterContour"),
        iaa.pillike.FilterEmboss(name="pillike.FilterEmboss"),
        iaa.pillike.FilterSharpen(name="pillike.FilterSharpen"),
        iaa.pillike.FilterDetail(name="pillike.FilterDetail"),
        iaa.pillike.Affine(scale=(0.9, 1.1),
                           translate_percent={"x": (-0.05, 0.05), "y": (-0.05, 0.05)},
                           rotate=(-10, 10),
                           shear=(-10, 10),
                           fillcolor=(0, 255),
                           name="pillike.Affine"),
    ]
    augmenters_segmentation = [
        iaa.Superpixels(p_replace=(0.05, 1.0), n_segments=(10, 100), max_size=64, interpolation="cubic",
                        name="Superpixels_max_size_64_cubic"),
        iaa.Superpixels(p_replace=(0.05, 1.0), n_segments=(10, 100), max_size=64, interpolation="linear",
                        name="Superpixels_max_size_64_linear"),
        iaa.Superpixels(p_replace=(0.05, 1.0), n_segments=(10, 100), max_size=128, interpolation="linear",
                        name="Superpixels_max_size_128_linear"),
        iaa.Superpixels(p_replace=(0.05, 1.0), n_segments=(10, 100), max_size=224, interpolation="linear",
                        name="Superpixels_max_size_224_linear"),
        iaa.UniformVoronoi(n_points=(250, 1000), name="UniformVoronoi"),
        iaa.RegularGridVoronoi(n_rows=(16, 31), n_cols=(16, 31), name="RegularGridVoronoi"),
        iaa.RelativeRegularGridVoronoi(n_rows_frac=(0.07, 0.14), n_cols_frac=(0.07, 0.14), name="RelativeRegularGridVoronoi"),
    ]
    augmenters_size = [
        iaa.Resize((0.8, 1.2), interpolation="nearest", name="Resize_nearest"),
        iaa.Resize((0.8, 1.2), interpolation="linear", name="Resize_linear"),
        iaa.Resize((0.8, 1.2), interpolation="cubic", name="Resize_cubic"),
        iaa.CropAndPad(percent=(-0.2, 0.2), pad_mode="constant", pad_cval=(0, 255), keep_size=False,
                       name="CropAndPad"),
        iaa.CropAndPad(percent=(-0.2, 0.2), pad_mode="edge", pad_cval=(0, 255), keep_size=False,
                       name="CropAndPad_edge"),
        iaa.CropAndPad(percent=(-0.2, 0.2), pad_mode="constant", pad_cval=(0, 255), name="CropAndPad_keep_size"),
        iaa.Pad(percent=(0.05, 0.2), pad_mode="constant", pad_cval=(0, 255), keep_size=False, name="Pad"),
        iaa.Pad(percent=(0.05, 0.2), pad_mode="edge", pad_cval=(0, 255), keep_size=False, name="Pad_edge"),
        iaa.Pad(percent=(0.05, 0.2), pad_mode="constant", pad_cval=(0, 255), name="Pad_keep_size"),
        iaa.Crop(percent=(0.05, 0.2), keep_size=False, name="Crop"),
        iaa.Crop(percent=(0.05, 0.2), name="Crop_keep_size"),
        iaa.PadToFixedSize(width=width+10, height=height+10, pad_mode="constant", pad_cval=(0, 255),
                           name="PadToFixedSize"),
        iaa.CropToFixedSize(width=width-10, height=height-10, name="CropToFixedSize"),
        iaa.KeepSizeByResize(iaa.CropToFixedSize(height=height-10, width=width-10), interpolation="nearest",
                             name="KeepSizeByResize_CropToFixedSize_nearest"),
        iaa.KeepSizeByResize(iaa.CropToFixedSize(height=height-10, width=width-10), interpolation="linear",
                             name="KeepSizeByResize_CropToFixedSize_linear"),
        iaa.KeepSizeByResize(iaa.CropToFixedSize(height=height-10, width=width-10), interpolation="cubic",
                             name="KeepSizeByResize_CropToFixedSize_cubic"),
    ]
    augmenters_weather = [
        iaa.FastSnowyLandscape(lightness_threshold=(100, 255), lightness_multiplier=(1.0, 4.0),
                               name="FastSnowyLandscape"),
        iaa.Clouds(name="Clouds"),
        iaa.Fog(name="Fog"),
        iaa.CloudLayer(intensity_mean=(196, 255), intensity_freq_exponent=(-2.5, -2.0), intensity_coarse_scale=10,
                       alpha_min=0, alpha_multiplier=(0.25, 0.75), alpha_size_px_max=(2, 8),
                       alpha_freq_exponent=(-2.5, -2.0), sparsity=(0.8, 1.0), density_multiplier=(0.5, 1.0),
                       name="CloudLayer"),
        iaa.Snowflakes(name="Snowflakes"),
        iaa.SnowflakesLayer(density=(0.005, 0.075), density_uniformity=(0.3, 0.9),
                            flake_size=(0.2, 0.7), flake_size_uniformity=(0.4, 0.8),
                            angle=(-30, 30), speed=(0.007, 0.03),
                            blur_sigma_fraction=(0.0001, 0.001), name="SnowflakesLayer"),
        iaa.Rain(name="Rain"),
        iaa.RainLayer(density=(0.03, 0.14),
                      density_uniformity=(0.8, 1.0),
                      drop_size=(0.01, 0.02),
                      drop_size_uniformity=(0.2, 0.5),
                      angle=(-15, 15),
                      speed=(0.04, 0.20),
                      blur_sigma_fraction=(0.001, 0.001),
                      name="RainLayer")
    ]

    augmenters = (
        augmenters_meta
        + augmenters_arithmetic
        + augmenters_artistic
        + augmenters_blend
        + augmenters_blur
        + augmenters_collections
        + augmenters_color
        + augmenters_contrast
        + augmenters_convolutional
        + augmenters_edges
        + augmenters_flip
        + augmenters_geometric
        + augmenters_pooling
        + augmenters_imgcorruptlike
        + augmenters_pillike
        + augmenters_segmentation
        + augmenters_size
        + augmenters_weather
    )

    if only_augmenters is not None:
        augmenters_reduced = []
        for augmenter in augmenters:
            if any([re.search(pattern, augmenter.name) for pattern in only_augmenters]):
                augmenters_reduced.append(augmenter)
        augmenters = augmenters_reduced

    return augmenters
예제 #9
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 iaa.Multiply((0.5, 1.5), per_channel=0.5),
  iaa.Multiply((0.5, 1)),
  iaa.JpegCompression(compression=(70, 99)),
  iaa.BlendAlphaHorizontalLinearGradient(iaa.AddToHue((-100, 100))),
  iaa.BlendAlphaCheckerboard(nb_rows=2, nb_cols=(1, 4),
              foreground=iaa.AddToHue((-100, 100))),
  iaa.GaussianBlur(sigma=(0.0, 1.0)),
  iaa.AddToHueAndSaturation((-50, 50), per_channel=True),
  iaa.GammaContrast((0.5, 2.0), per_channel=True),
  iaa.Affine(rotate=(-15, 15)),
  iaa.Affine(translate_percent={"x": -0.20}, mode=ia.ALL, cval=(0, 255)),
  iaa.Affine(translate_percent={"y": -0.20}, mode=ia.ALL, cval=(0, 255)),
  iaa.Affine(translate_percent={"x": +0.20}, mode=ia.ALL, cval=(0, 255)),
  iaa.Affine(translate_percent={"y": +0.20}, mode=ia.ALL, cval=(0, 255)),
  iaa.BlendAlpha(
     (0.0, 1.0),
     iaa.Affine(rotate=(-20, 20)),
     per_channel=0.5),
 iaa.BlendAlpha([0.25, 0.75], iaa.MedianBlur(13)),
 iaa.BlendAlphaElementwise(
     (0.0, 1.0),
     foreground=iaa.Add(100),
     background=iaa.Multiply(0.2)),
 iaa.BlendAlphaSimplexNoise(iaa.EdgeDetect(1.0)),
 iaa.BlendAlphaSimplexNoise(
     iaa.EdgeDetect(1.0),
     upscale_method="nearest"),
 iaa.BlendAlphaSimplexNoise(
     iaa.EdgeDetect(1.0),
     upscale_method="linear"),
 iaa.BlendAlphaSomeColors(iaa.TotalDropout(1.0)),
 iaa.BlendAlphaSomeColors(
예제 #10
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def chapter_alpha_constant():
    # -----------------------------------------
    # example 1 (sharpen + dropout)
    # -----------------------------------------
    import imgaug as ia
    from imgaug import augmenters as iaa

    ia.seed(1)

    # Example batch of images.
    # The array has shape (8, 128, 128, 3) and dtype uint8.
    images = np.array([ia.quokka(size=(128, 128)) for _ in range(8)],
                      dtype=np.uint8)

    seq = iaa.BlendAlpha(factor=(0.2, 0.8),
                         foreground=iaa.Sharpen(1.0, lightness=2),
                         background=iaa.CoarseDropout(p=0.1, size_px=8))

    images_aug = seq(images=images)

    # ------------

    save("alpha", "alpha_constant_example_basic.jpg",
         grid(images_aug, cols=4, rows=2))

    # -----------------------------------------
    # example 2 (per channel)
    # -----------------------------------------
    import imgaug as ia
    from imgaug import augmenters as iaa

    ia.seed(1)

    # Example batch of images.
    # The array has shape (8, 128, 128, 3) and dtype uint8.
    images = np.array([ia.quokka(size=(128, 128)) for _ in range(8)],
                      dtype=np.uint8)

    seq = iaa.BlendAlpha(factor=(0.2, 0.8),
                         foreground=iaa.Sharpen(1.0, lightness=2),
                         background=iaa.CoarseDropout(p=0.1, size_px=8),
                         per_channel=True)

    images_aug = seq(images=images)

    # ------------

    save("alpha", "alpha_constant_example_per_channel.jpg",
         grid(images_aug, cols=4, rows=2))

    # -----------------------------------------
    # example 3 (affine + per channel)
    # -----------------------------------------
    import imgaug as ia
    from imgaug import augmenters as iaa

    ia.seed(1)

    # Example batch of images.
    # The array has shape (8, 128, 128, 3) and dtype uint8.
    images = np.array([ia.quokka(size=(128, 128)) for _ in range(8)],
                      dtype=np.uint8)

    seq = iaa.BlendAlpha(factor=(0.2, 0.8),
                         foreground=iaa.Affine(rotate=(-20, 20)),
                         per_channel=True)

    images_aug = seq(images=images)

    # ------------

    save("alpha", "alpha_constant_example_affine.jpg",
         grid(images_aug, cols=4, rows=2))
예제 #11
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    def get_aug(self):
        #sometimes_bg = lambda aug: iaa.Sometimes(0.3, aug)
        sometimes_contrast = lambda aug: iaa.Sometimes(0.3, aug)
        sometimes_noise = lambda aug: iaa.Sometimes(0.6, aug)
        sometimes_blur = lambda aug: iaa.Sometimes(0.6, aug)
        sometimes_degrade_quality = lambda aug: iaa.Sometimes(0.9, aug)
        sometimes_blend = lambda aug: iaa.Sometimes(0.2, aug)

        seq = iaa.Sequential(
                [
                # crop some of the images by 0-30% of their height/width
                # Execute 0 to 4 of the following (less important) augmenters per
                    # image. Don't execute all of them, as that would often be way too
                    # strong.
    #             iaa.SomeOf((0, 4),
    #                     [ 
                # change the background color of some of the images chosing any one technique
#                sometimes_bg(iaa.OneOf([
#                            iaa.AddToHueAndSaturation((-60, 60)),
#                            iaa.Multiply((0.6, 1), per_channel=True),
#                            ])),
                #change the contrast of the input images chosing any one technique    
                sometimes_contrast(iaa.OneOf([
                            iaa.LinearContrast((0.5,1.5)),
                            iaa.SigmoidContrast(gain=(3, 5), cutoff=(0.4, 0.6)),
                            iaa.CLAHE(tile_grid_size_px=(3, 21)),
                            iaa.GammaContrast((0.5,1.0))
                            ])),

                #add noise to the input images chosing any one technique 
                sometimes_noise(iaa.OneOf([
                    iaa.AdditiveGaussianNoise(scale=(3,8)),
                    iaa.CoarseDropout((0.001,0.01), size_percent=0.5),
                    iaa.AdditiveLaplaceNoise(scale=(3,10)),
                    iaa.CoarsePepper((0.001,0.01), size_percent=(0.5)),
                    iaa.AdditivePoissonNoise(lam=(3.0,10.0)),
                    iaa.Pepper((0.001,0.01)),
                    iaa.Snowflakes(),
                    iaa.Dropout(0.01,0.01),
                    ])),

                #add blurring techniques to the input image
                sometimes_blur(iaa.OneOf([
                    iaa.AverageBlur(k=(3)),
                    iaa.GaussianBlur(sigma=(1.0)),
                    ])),

                # add techniques to degrade the iamge quality
                sometimes_degrade_quality(iaa.OneOf([
                            iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0)),
                            iaa.Sharpen(alpha=(0.5), lightness=(0.75,1.5)),
                            iaa.BlendAlphaSimplexNoise(
                            foreground=iaa.Multiply(iap.Choice([1.5]), per_channel=False)
                            )
                            ])),

                # blend some patterns in the background    
                sometimes_blend(iaa.OneOf([
                            iaa.BlendAlpha(
                            factor=(0.6,0.8),
                            foreground=iaa.Sharpen(1.0, lightness=1),

                            background=iaa.CoarseDropout(p=0.1, size_px=np.random.randint(30))),

                            iaa.BlendAlphaFrequencyNoise(exponent=(-4),
                                       foreground=iaa.Multiply(iap.Choice([0.5]), per_channel=False)
                                       ),
                            iaa.BlendAlphaSimplexNoise(
                            foreground=iaa.Multiply(iap.Choice([0.5]), per_channel=True)
                            )
                      ])), 

                    ])
        return seq
예제 #12
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    elif augmentation == 'invert_img':
        transform = InvertImg(always_apply=True)
        transformed_image = transform(image=image)['image']

    ## Artistic

    elif augmentation == 'cartoon':
        transform = iaa.Cartoon(blur_ksize=3, segmentation_size=1.0,
                                saturation=2.0, edge_prevalence=1.0)
        transformed_image = transform(image=image)

    ## Blend

    elif augmentation == 'blend_alpha':
        transform = iaa.BlendAlpha(0.5, iaa.Grayscale(1.0))
        transformed_image = transform(image=image)

    elif augmentation == 'blend_alpha_simplex_noise':
        transform = iaa.BlendAlphaSimplexNoise(iaa.EdgeDetect(1.0))
        transformed_image = transform(image=image)

    elif augmentation == 'blend_alpha_some_colors':
        transform = iaa.BlendAlphaSomeColors(iaa.Grayscale(1.0))
        transformed_image = transform(image=image)

    elif augmentation == 'blend_alpha_regular_grid':
        transform = iaa.BlendAlphaRegularGrid(nb_rows=(4, 6), nb_cols=(1, 4),
                                              foreground=iaa.Multiply(0.0))
        transformed_image = transform(image=image)