def chapter_augmenters_randaugment():
fn_start = "collections/randaugment"
aug = iaa.RandAugment(n=2, m=9)
run_and_save_augseq(fn_start + "_standard_case.jpg",
aug,
[ia.quokka(size=(128, 128)) for _ in range(4 * 3)],
cols=4,
rows=3)
aug = iaa.RandAugment(m=30)
run_and_save_augseq(fn_start + "_strong_magnitude.jpg",
aug,
[ia.quokka(size=(128, 128)) for _ in range(4 * 3)],
cols=4,
rows=3)
aug = iaa.RandAugment(m=(0, 9))
run_and_save_augseq(fn_start + "_random_magnitude.jpg",
aug,
[ia.quokka(size=(128, 128)) for _ in range(4 * 3)],
cols=4,
rows=3)
aug = iaa.RandAugment(n=(0, 3))
run_and_save_augseq(fn_start + "_random_iterations.jpg",
aug,
[ia.quokka(size=(128, 128)) for _ in range(4 * 3)],
cols=4,
rows=3)
def generate_randaugment():
ia.seed(1)
image = ia.quokka((128, 128))
images_aug = [image]
images_aug.extend(iaa.RandAugment(m=20)(images=[image] * (2 * 8 - 1)))
_save("randaugment.jpg", ia.draw_grid(images_aug, cols=8, rows=2))
def run(files, number):
folder = 0
zip_object = io.BytesIO()
with zipfile.ZipFile(zip_object, "w", zipfile.ZIP_DEFLATED) as zf:
for file in files:
folder = folder + 1
image = Image.open(file).convert('RGB')
result = list()
images = asarray(image)
for _ in range(number):
temp = deepcopy(
iaa.Sometimes(1, iaa.RandAugment(n=2, m=9))(image=images))
temp = Image.fromarray(temp, 'RGB')
result.append(temp)
i = 0
for img in result:
buf = io.BytesIO()
img.save(buf, 'jpeg')
img_name = str(folder) + "/aug_{:02d}.jpeg".format(i)
i = i + 1
print("Writing image {:s} in the archive".format(img_name))
zf.writestr(img_name, buf.getvalue())
zip_object.seek(0)
# img = base64.b64encode(img_io.getvalue())
return zip_object.getvalue()
def main():
image = ia.quokka(0.25)
for N in [1, 2]:
print("N=%d" % (N, ))
images_aug = []
for M in [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]:
images_aug.extend(
iaa.RandAugment(n=N, m=M, random_state=1)(images=[image] * 10))
ia.imshow(ia.draw_grid(images_aug, cols=10))
for M in [0, 1, 2, 4, 8, 10]:
print("M=%d" % (M, ))
aug = iaa.RandAugment(m=M, random_state=1)
images_aug = []
for _ in np.arange(6):
images_aug.extend(aug(images=[image] * 16))
ia.imshow(ia.draw_grid(images_aug, cols=16, rows=6))
def texture_augmented_augmentor(x, y):
def config_and_generate(depth_i, cls_i):
rand_idx = randint(0, n_rnd_bkgs - 1)
depth_seq = iaa.Sequential(
[iaa.Affine(scale=(0.5, 1.5), rotate=(-45, 45))])
depth_i += depth_seq(images=np.array([rnd_bkgs[rand_idx]]))[0] * 0.1
return simulation2014_approach.generate(depth_i)
sim = np.array([config_and_generate(x[i], y[i]) for i in range(len(x))])
seq = iaa.Sequential([iaa.RandAugment(n=2, m=9)])
return seq(images=sim), y
def __init__(self):
self.aug = iaa.Sequential(
[
# iaa.Resize((224, 224)),
# iaa.Sometimes(0.25, iaa.GaussianBlur(sigma=(0, 3.0))),
iaa.Fliplr(0.5),
# iaa.Flipud(0.1), # vertically flip 20% of all images
iaa.Affine(
rotate=(-5, 5),
shear=(-3, 3),
translate_percent={
"x": (-0.1, 0.1),
"y": (-0.1, 0.1)
},
mode="symmetric",
),
# iaa.SaltAndPepper(p=(0, 0.03)),
# iaa.Sometimes(0.1,
# iaa.OneOf([iaa.Dropout(p=(0, 0.1)),
# iaa.CoarseDropout(0.1, size_percent=0.5)])),
# iaa.LinearContrast((0.5, 2.0), per_channel=0.5),
# sometimes(
# iaa.ElasticTransformation(alpha=(0.5, 3.5), sigma=0.25)
# ),
# iaa.Grayscale(alpha=(0.0, 1.0)),
# sometimes(iaa.PiecewiseAffine(scale=(0.01, 0.05))),
# iaa.Multiply((0.8, 1.2), per_channel=0.2),
# iaa.ContrastNormalization((0.75, 1.5)),
# iaa.AddToHueAndSaturation(value=(-10, 10), per_channel=True)
],
random_order=True,
)
self.aug2 = iaa.Sequential([
# iaa.Scale((224, 224)),
iaa.Sometimes(0.25, iaa.GaussianBlur(sigma=(0, 3.0))),
iaa.Fliplr(0.5),
iaa.Affine(rotate=(-20, 20), mode="symmetric"),
iaa.Sometimes(
0.25,
iaa.OneOf([
iaa.Dropout(p=(0, 0.1)),
iaa.CoarseDropout(0.1, size_percent=0.5),
]),
),
iaa.AddToHueAndSaturation(value=(-10, 10), per_channel=True),
])
self.aug3 = iaa.Sequential([
# iaa.Scale((224, 224)),
iaa.RandAugment(n=2, m=9)
])
def test_m(self, mock_main, mock_initial):
def _create_main_list(m, _cval):
return [iaa.Add(m)]
mock_main.side_effect = _create_main_list
mock_initial.return_value = []
img = np.zeros((1, 1, 3), dtype=np.uint8)
for m in [0, 1, 2]:
with self.subTest(m=m):
aug = iaa.RandAugment(m=m)
img_aug = aug(image=img)
assert img_aug[0, 0, 0] == m
def test_n(self, mock_main, mock_initial):
mock_main.return_value = [iaa.Add(1), iaa.Add(2), iaa.Add(4)]
mock_initial.return_value = []
img = np.zeros((1, 1, 3), dtype=np.uint8)
expected = {
0: [0],
1: [1, 2, 4],
2: [1 + 1, 1 + 2, 1 + 4, 2 + 2, 2 + 4, 4 + 4]
}
for n in [0, 1, 2]:
with self.subTest(n=n):
aug = iaa.RandAugment(n=n)
img_aug = aug(image=img)
assert img_aug[0, 0, 0] in expected[n]
def test_cval(self):
cval = 200
aug = iaa.RandAugment(n=1, m=30, cval=cval)
img = np.zeros((20, 20, 3), dtype=np.uint8)
x_cval = False
y_cval = False
# lots of iterations here, because only in some iterations an affine
# translation is actually applied
for _ in np.arange(500):
img_aug = aug(image=img)
x_cval = x_cval or np.all(img_aug[:, :1] == cval)
x_cval = x_cval or np.all(img_aug[:, -1:] == cval)
y_cval = y_cval or np.all(img_aug[:1, :] == cval)
y_cval = y_cval or np.all(img_aug[-1:, :] == cval)
if np.all([x_cval, y_cval]):
break
assert np.all([x_cval, y_cval])
def data_aug(images):
seq = iaa.Sometimes(
0.5, iaa.Identity(),
iaa.Sometimes(
0.5,
iaa.Sequential([
iaa.Fliplr(0.5),
iaa.Sometimes(
0.5,
iaa.OneOf([
iaa.Add((-40, 40)),
iaa.AddElementwise((-40, 40)),
iaa.AdditiveGaussianNoise(scale=(0, 0.2 * 255)),
iaa.AdditiveLaplaceNoise(scale=(0, 0.2 * 255)),
iaa.AdditivePoissonNoise((0, 40)),
iaa.MultiplyElementwise((0.5, 1.5)),
iaa.ReplaceElementwise(0.1, [0, 255]),
iaa.SaltAndPepper(0.1)
])),
iaa.OneOf([
iaa.Cutout(nb_iterations=2,
size=0.15,
cval=0,
squared=False),
iaa.CoarseDropout((0.0, 0.05), size_percent=(0.02, 0.25)),
iaa.Dropout(p=(0, 0.2)),
iaa.CoarseSaltAndPepper(0.05, size_percent=(0.01, 0.1)),
iaa.Cartoon(),
iaa.BlendAlphaVerticalLinearGradient(iaa.TotalDropout(1.0),
min_value=0.2,
max_value=0.8),
iaa.GaussianBlur(sigma=(0.0, 3.0)),
iaa.AverageBlur(k=(2, 11)),
iaa.MedianBlur(k=(3, 11)),
iaa.BilateralBlur(d=(3, 10),
sigma_color=(10, 250),
sigma_space=(10, 250)),
iaa.MotionBlur(k=20),
iaa.AllChannelsCLAHE(),
iaa.Sharpen(alpha=(0.0, 1.0), lightness=(0.75, 2.0)),
iaa.Emboss(alpha=(0.0, 1.0), strength=(0.5, 1.5)),
iaa.Affine(scale=(0.5, 1.5)),
iaa.Affine(translate_px={
"x": (-20, 20),
"y": (-20, 20)
}),
iaa.Affine(shear=(-16, 16)),
iaa.pillike.EnhanceSharpness()
]),
iaa.OneOf([
iaa.GammaContrast((0.5, 2.0)),
iaa.SigmoidContrast(gain=(3, 10), cutoff=(0.4, 0.6)),
iaa.LogContrast(gain=(0.6, 1.4)),
iaa.LinearContrast((0.4, 1.6)),
iaa.pillike.EnhanceBrightness()
])
]),
iaa.Sometimes(0.5, iaa.RandAugment(n=2, m=9),
iaa.RandAugment(n=(0, 3), m=(0, 9)))))
images = seq(images=images)
return images
def augmentor(x, y):
seq = iaa.Sequential([iaa.RandAugment(n=2, m=9)])
return seq(images=x), y
def test_pickleable(self):
aug = iaa.RandAugment(m=(0, 10), n=(1, 2))
runtest_pickleable_uint8_img(aug, iterations=50)
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
def __init__(self, number_of_affine, magnitude_of_affine):
self.aug = iaa.RandAugment(n=number_of_affine, m=magnitude_of_affine)
for d in dirs:
img_path = path+str(d)+"/"+str(d)+".jpg"
image = imageio.imread(img_path)
images = [image, image, image, image, image, image, image, image, image, image,
image, image, image, image, image, image, image, image, image, image,
image, image, image, image, image, image, image, image, image, image,
image, image, image, image, image, image, image, image, image, image,
image, image, image, image, image, image, image, image, image]
sometimes = lambda aug: iaa.Sometimes(0.5, aug)
seq = iaa.Sequential(
[
iaa.RandAugment(m=10),
iaa.RandAugment(m=(2, 9)),
iaa.RandAugment(n=(1, 3)),
iaa.SomeOf((5, 10),
[
iaa.RelativeRegularGridVoronoi(0.1, 0.25),
iaa.Superpixels(p_replace=(0.1, 1.0), n_segments=(16, 128)),
iaa.Add((-40, 40), per_channel=0.5),
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)),
def test_get_parameters(self):
aug = iaa.RandAugment(n=1, m=30, cval=100)
params = aug.get_parameters()
assert params[0] is aug[1].n
assert params[1] is aug._m
assert params[2] is aug._cval
def __init__(self, n=2, m=9, determint=False):
self.n = n
self.m = m
self.determint = determint
self.func = iaa.RandAugment(n=n, m=m)
"""
## Define hyperparameters
"""
AUTO = tf.data.AUTOTUNE
BATCH_SIZE = 128
EPOCHS = 1
IMAGE_SIZE = 72
"""
## Initialize `RandAugment` object
Now, we will initialize a `RandAugment` object from the `imgaug.augmenters` module with
the parameters suggested by the RandAugment authors.
"""
rand_aug = iaa.RandAugment(n=3, m=7)
def augment(images):
# Input to `augment()` is a TensorFlow tensor which
# is not supported by `imgaug`. This is why we first
# convert it to its `numpy` variant.
images = tf.cast(images, tf.uint8)
return rand_aug(images=images.numpy())
"""
## Create TensorFlow `Dataset` objects
Because `RandAugment` can only process NumPy arrays, it
cannot be applied directly as part of the `Dataset` object (which expects TensorFlow
