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