def preprocess(image, mode='plain', d_theta=0): """ Combine all preprocess functions into one """ if mode == 'random_rotate_and_shift': angle = 30 dx = 32 dy = 16 d_theta = round(np.random.random() * angle * 2 - angle) d_x = np.random.random() * dx * 2 - dx d_y = np.random.random() * dy * 2 - dy y, x = image.shape[:2] translation_matrix = np.float32([[1, 0, d_x], [0, 1, d_y]]) from PIL import Image image = Image.fromarray(image) image = image.rotate(d_theta) image = np.array(image) image = cv2.warpAffine(image, translation_matrix, (x, y)) elif mode == 'exact_rotate': from PIL import Image image = Image.fromarray(image) image = image.rotate(d_theta) image = np.array(image) elif mode == 'rainy_foggy_automold': import Automold as am import Helpers as hp if np.random.random() > 0.5: image = am.add_rain(image, rain_type='heavy') else: image = am.add_fog(image) elif mode == 'rainy_foggy_iaa': from imgaug import augmenters as iaa seq = iaa.Rain() if np.random.random() > 0.5: seq = iaa.Rain() else: seq = iaa.Fog() image = seq(images=image) # for i in range(len(image)): # image[i] = crop(image[i]) # image[i] = resize(image[i]) # image[i] = rgb2yuv(image[i]) # image[i] = image[i][np.newaxis, :, :, :] # image = np.concatenate(image, axis=0) image = crop(image) image = resize(image) image = rgb2yuv(image) return image
def get_seq(flag_normal, flag_affine, flag_noise, flag_snow, flag_cloud, flag_fog, flag_snowflakes, flag_rain, flag_dropout): if flag_normal: seq_list = [ iaa.SomeOf((1, 2), [ iaa.LinearContrast((0.5, 2.0), per_channel=0.5), iaa.Grayscale(alpha=(0.0, 1.0)), iaa.Sharpen(alpha=(0, 1.0), lightness=(0.75, 1.5)), ]) ] else: seq_list = [] if flag_affine: seq_list.append( iaa.Sometimes( 0.7, iaa.Affine(scale={ "x": (0.8, 1.2), "y": (0.8, 1.2) }, translate_percent={ "x": (-0.2, 0.2), "y": (-0.2, 0.2) }, rotate=(-25, 25), shear=(-8, 8)))) if flag_noise: seq_list.append( iaa.OneOf([ iaa.GaussianBlur((0, 3.0)), iaa.AverageBlur(k=(2, 7)), iaa.MedianBlur(k=(3, 11)), ])) if flag_snow: seq_list.append( iaa.FastSnowyLandscape(lightness_threshold=(100, 255), lightness_multiplier=(1.0, 4.0))) elif flag_cloud: seq_list.append(iaa.Clouds()) elif flag_fog: seq_list.append(iaa.Fog()) elif flag_snowflakes: seq_list.append( iaa.Snowflakes(flake_size=(0.2, 0.7), speed=(0.007, 0.03))) elif flag_rain: seq_list.append(iaa.Rain()) if flag_dropout: seq_list.append( iaa.OneOf([ iaa.Dropout((0.01, 0.1), per_channel=0.5), iaa.CoarseDropout((0.03, 0.15), size_percent=(0.02, 0.05), per_channel=0.2), ])) return iaa.Sequential(seq_list, random_order=True)
def chapter_augmenters_rain(): fn_start = "weather/rain" image = LANDSCAPE_IMAGE aug = iaa.Rain(speed=(0.1, 0.3)) run_and_save_augseq( fn_start + ".jpg", aug, [image for _ in range(4*2)], cols=4, rows=2)
def main(): augs = [ iaa.Rain(speed=(0.1, 0.3)), iaa.Rain(), iaa.Rain(drop_size=(0.1, 0.2)) ] image = imageio.imread( ("https://upload.wikimedia.org/wikipedia/commons/8/89/" "Kukle%2CCzech_Republic..jpg"), format="jpg") for aug, size in zip(augs, [0.1, 0.2, 1.0]): image_rs = ia.imresize_single_image(image, size, "cubic") print(image_rs.shape) images_aug = aug.augment_images([image_rs] * 64) ia.imshow(ia.draw_grid(images_aug))
def get_preview(images, augmentationList): """ Accepts a list of images and augmentationList as input. Provides a list of augmented images in that order as ouptut. """ augmented = [] for image in images: for augmentation in augmentationList: aug_id = augmentation['id'] params = augmentation['params'] if (aug_id == 1): image = iaa.SaltAndPepper(p=params[0], per_channel=params[1])(image=image) elif (aug_id == 2): image = iaa.imgcorruptlike.GaussianNoise( severity=(params[0], params[1]))(image=image) elif (aug_id == 3): image = iaa.Rain(speed=(params[0], params[1]), drop_size=(params[2], params[3]))(image=image) elif (aug_id == 4): image = iaa.imgcorruptlike.Fog( severity=(params[0], params[1]))(image=image) elif (aug_id == 5): image = iaa.imgcorruptlike.Snow( severity=(params[0], params[1]))(image=image) elif (aug_id == 6): image = iaa.imgcorruptlike.Spatter( severity=(params[0], params[1]))(image=image) elif (aug_id == 7): image = iaa.BlendAlphaSimplexNoise( iaa.EdgeDetect(1))(image=image) elif (aug_id == 8): image = iaa.Rotate(rotate=(params[0], params[1]))(image=image) elif (aug_id == 9): image = iaa.Affine()(image=image) #to be implemented elif (aug_id == 10): image = iaa.MotionBlur(k=params[0], angle=(params[1], params[2]))(image=image) elif (aug_id == 11): image = iaa.imgcorruptlike.ZoomBlur( severity=(params[0], params[1]))(image=image) elif (aug_id == 12): image = iaa.AddToBrightness()(image=image) #to be implemented elif (aug_id == 13): image = iaa.ChangeColorTemperature( kelvin=(params[0], params[1]))(image=image) elif (aug_id == 14): image = iaa.SigmoidContrast()(image=image) #to be implemented elif (aug_id == 15): image = iaa.Cutout(nb_iterations=(params[0], params[1]), size=params[2], squared=params[3])(image=image) else: print("Not implemented") augmented.append(image) return augmented
def test_zero_sized_axes(self): shapes = [(0, 0, 3), (0, 1, 3), (1, 0, 3)] for shape in shapes: with self.subTest(shape=shape): image = np.zeros(shape, dtype=np.uint8) aug = iaa.Rain() image_aug = aug(image=image) assert image_aug.dtype.name == "uint8" assert image_aug.shape == shape
def generate_rain(): ia.seed(2) image = imageio.imread( os.path.join(INPUT_IMAGES_DIR, "Pahalgam_Valley.jpg")) image = iaa.Resize({ "width": 256, "height": "keep-aspect-ratio" })(image=image) images_aug = [image] images_aug.extend(iaa.Rain()(images=[image] * (2 * 8 - 1))) _save("rain.jpg", ia.draw_grid(images_aug, cols=4, rows=4))
def train(model): """Train the model.""" # Training dataset. dataset_train = CharacterDataset() dataset_train.load_characters("train") dataset_train.prepare() # Validation dataset dataset_val = CharacterDataset() dataset_val.load_characters("val") dataset_val.prepare() #Augmentation aug = iaa.SomeOf(2, [ iaa.AdditiveGaussianNoise(scale=(0, 0.10 * 255)), iaa.MotionBlur(), iaa.GaussianBlur(sigma=(0.0, 2.0)), iaa.RemoveSaturation(mul=(0, 0.5)), iaa.GammaContrast(), iaa.Rotate(rotate=(-45, 45)), iaa.PerspectiveTransform(scale=(0.01, 0.15)), iaa.JpegCompression(compression=(0, 75)), iaa.imgcorruptlike.Spatter(severity=(1, 4)), iaa.Rain(speed=(0.1, 0.3)), iaa.Fog() ]) custom_callbacks = [ ReduceLROnPlateau(monitor='val_loss', factor=0.1, patience=5, verbose=1), EarlyStopping(monitor='val_loss', min_delta=0, patience=10, verbose=1) ] # *** This training schedule is an example. Update to your needs *** # Since we're using a very small dataset, and starting from # COCO trained weights, we don't need to train too long. Also, # no need to train all layers, just the heads should do it. print("Training network heads") model.train(dataset_train, dataset_val, learning_rate=config.LEARNING_RATE, epochs=100, layers='heads', augmentation=aug, custom_callbacks=custom_callbacks)
def _test_very_roughly(cls, nb_channels): if nb_channels is None: img = np.zeros((100, 100), dtype=np.uint8) else: img = np.zeros((100, 100, nb_channels), dtype=np.uint8) imgs_aug = iaa.Rain()(images=[img] * 5) assert 5 < np.average(imgs_aug) < 200 assert np.max(imgs_aug) > 70 for img_aug in imgs_aug: img_aug_f32 = img_aug.astype(np.float32) grad_x = img_aug_f32[:, 1:] - img_aug_f32[:, :-1] grad_y = img_aug_f32[1:, :] - img_aug_f32[:-1, :] assert np.sum(np.abs(grad_x)) > 10 * img.shape[1] assert np.sum(np.abs(grad_y)) > 10 * img.shape[0]
def do_all_aug(image): do_aug(image, iaa.Noop(name="origin")) do_aug(image, iaa.Crop((0, 10))) # 切边 do_aug(image, iaa.GaussianBlur((0, 3))) do_aug(image, iaa.AverageBlur(1, 7)) do_aug(image, iaa.MedianBlur(1, 7)) do_aug(image, iaa.Sharpen()) do_aug(image, iaa.BilateralBlur()) # 既噪音又模糊,叫双边 do_aug(image, iaa.MotionBlur()) do_aug(image, iaa.MeanShiftBlur()) do_aug(image, iaa.GammaContrast()) do_aug(image, iaa.SigmoidContrast()) do_aug(image, iaa.Affine(shear={ 'x': (-10, 10), 'y': (-10, 10) }, mode="edge")) # shear:x轴往左右偏离的像素书,(a,b)是a,b间随机值,[a,b]是二选一 do_aug(image, iaa.Affine(shear={ 'x': (-10, 10), 'y': (-10, 10) }, mode="edge")) # shear:x轴往左右偏离的像素书,(a,b)是a,b间随机值,[a,b]是二选一 do_aug(image, iaa.Rotate(rotate=(-10, 10), mode="edge")) do_aug(image, iaa.PiecewiseAffine()) # 局部点变形 do_aug(image, iaa.Fog()) do_aug(image, iaa.Clouds()) do_aug(image, iaa.Snowflakes(flake_size=(0.1, 0.2), density=(0.005, 0.025))) do_aug( image, iaa.Rain( nb_iterations=1, drop_size=(0.05, 0.1), speed=(0.04, 0.08), )) do_aug( image, iaa.ElasticTransformation(alpha=(0.0, 20.0), sigma=(3.0, 5.0), mode="nearest")) do_aug(image, iaa.AdditiveGaussianNoise(scale=(0, 10))) do_aug(image, iaa.AdditiveLaplaceNoise(scale=(0, 10))) do_aug(image, iaa.AdditivePoissonNoise(lam=(0, 10))) do_aug(image, iaa.Salt((0, 0.02))) do_aug(image, iaa.Pepper((0, 0.02)))
elif augmentation == 'relative_regular_grid_voronoi': transform = iaa.RelativeRegularGridVoronoi(0.1, 0.25) transformed_image = transform(image=image) ## Weather elif augmentation == 'fog': transform = iaa.imgcorruptlike.Fog(severity=2) transformed_image = transform(image=image) elif augmentation == 'random_rain': transform = RandomRain(always_apply=True) transformed_image = transform(image=image)['image'] elif augmentation == 'rain': transform = iaa.Rain(speed=(0.1, 0.3)) transformed_image = transform(image=image) elif augmentation == 'snow': transform = iaa.imgcorruptlike.Snow(severity=2) transformed_image = transform(image=image) elif augmentation == 'snow_flakes': transform = iaa.Snowflakes(flake_size=(0.1, 0.4), speed=(0.01, 0.05)) transformed_image = transform(image=image) elif augmentation == 'frost': transform = iaa.imgcorruptlike.Frost(severity=1) transformed_image = transform(image=image) elif augmentation == 'clouds':
def test_pickleable(self): aug = iaa.Rain(random_state=1) runtest_pickleable_uint8_img(aug, iterations=3, shape=(20, 20, 3))
iaa.AllChannelsHistogramEqualization(), iaa.GammaContrast((0.5, 1.5), per_channel=True), iaa.GammaContrast((0.5, 1.5)), iaa.SigmoidContrast(gain=(3, 10), cutoff=(0.4, 0.6), per_channel=True), iaa.SigmoidContrast(gain=(3, 10), cutoff=(0.4, 0.6)), iaa.HistogramEqualization(), iaa.Sharpen(alpha=0.5) ]), iaa.OneOf([ iaa.AveragePooling([2, 3]), iaa.MaxPooling(([2, 3], [2, 3])), ]), iaa.OneOf([ iaa.Clouds(), iaa.Snowflakes(flake_size=(0.1, 0.4), speed=(0.01, 0.05)), iaa.Rain(speed=(0.1, 0.3)) ]) ], random_order=True) def get_color_augmentation(augment_prob): return iaa.Sometimes(augment_prob, aug_transform).augment_image class SegCompose(object): def __init__(self, augmenters): super().__init__() self.augmenters = augmenters def __call__(self, image, label):
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 augument(self, image, bbox_list): seq = iaa.Sequential([ # 变形 iaa.Sometimes( 0.6, [ iaa.OneOf([ iaa.Affine(shear={ 'x': (-1.5, 1.5), 'y': (-1.5, 1.5) }, mode="edge"), # 仿射变化程度,单位像素 iaa.Rotate(rotate=(-1, 1), mode="edge"), # 旋转,单位度 ]) ]), # 扭曲 iaa.Sometimes( 0.5, [ iaa.OneOf([ iaa.PiecewiseAffine( scale=(0, 0.02), nb_rows=2, nb_cols=2), # 局部仿射 iaa.ElasticTransformation( # distort扭曲变形 alpha=(0, 3), # 扭曲程度 sigma=(0.8, 1), # 扭曲后的平滑程度 mode="nearest"), ]), ]), # 模糊 iaa.Sometimes( 0.5, [ iaa.OneOf([ iaa.GaussianBlur(sigma=(0, 0.7)), iaa.AverageBlur(k=(1, 3)), iaa.MedianBlur(k=(1, 3)), iaa.BilateralBlur( d=(1, 5), sigma_color=(10, 200), sigma_space=(10, 200)), # 既噪音又模糊,叫双边, iaa.MotionBlur(k=(3, 5)), iaa.Snowflakes(flake_size=(0.1, 0.2), density=(0.005, 0.025)), iaa.Rain(nb_iterations=1, drop_size=(0.05, 0.1), speed=(0.04, 0.08)), ]) ]), # 锐化 iaa.Sometimes(0.3, [ iaa.OneOf([ iaa.Sharpen(), iaa.GammaContrast(), iaa.SigmoidContrast() ]) ]), # 噪音 iaa.Sometimes(0.3, [ iaa.OneOf([ iaa.AdditiveGaussianNoise(scale=(1, 5)), iaa.AdditiveLaplaceNoise(scale=(1, 5)), iaa.AdditivePoissonNoise(lam=(1, 5)), iaa.Salt((0, 0.02)), iaa.Pepper((0, 0.02)) ]) ]), # 剪切 iaa.Sometimes( 0.8, [ iaa.OneOf([ iaa.Crop((0, 2)), # 切边, (0到10个像素采样) ]) ]), ]) assert bbox_list is None or type(bbox_list) == list if bbox_list is None or len(bbox_list) == 0: polys = None else: polys = [ia.Polygon(pos) for pos in bbox_list] polys = ia.PolygonsOnImage(polys, shape=image.shape) # 处理部分或者整体出了图像的范围的多边形,参考:https://imgaug.readthedocs.io/en/latest/source/examples_bounding_boxes.html polys = polys.remove_out_of_image().clip_out_of_image() images_aug, polygons_aug = seq(images=[image], polygons=polys) image = images_aug[0] if polygons_aug is None: polys = None else: polys = [] for p in polygons_aug.polygons: polys.append(p.coords) polys = np.array(polys, np.int32).tolist() # (N,2) return image, polys
def aug4(self, img): seq = iaa.Sequential([iaa.Rain(speed=(0))]) img_au = seq(image=img) return img_au
def do_random(image, pos_list): # 1.先任选5种影响位置的效果之一做位置变换 seq = iaa.Sequential([ iaa.Sometimes( 0.5, [ iaa.Crop((0, 10)), # 切边, (0到10个像素采样) ]), iaa.Sometimes( 0.5, [ iaa.Affine(shear={ 'x': (-10, 10), 'y': (-10, 10) }, mode="edge"), iaa.Rotate(rotate=(-10, 10), mode="edge"), # 旋转 ]), iaa.Sometimes( 0.5, [ iaa.PiecewiseAffine(), # 局部仿射 iaa.ElasticTransformation( # distort扭曲变形 alpha=(0.0, 20.0), sigma=(3.0, 5.0), mode="nearest"), ]), # 18种位置不变的效果 iaa.SomeOf( (1, 3), [ iaa.GaussianBlur(), iaa.AverageBlur(), iaa.MedianBlur(), iaa.Sharpen(), iaa.BilateralBlur(), # 既噪音又模糊,叫双边, iaa.MotionBlur(), iaa.MeanShiftBlur(), iaa.GammaContrast(), iaa.SigmoidContrast(), iaa.Fog(), iaa.Clouds(), iaa.Snowflakes(flake_size=(0.1, 0.2), density=(0.005, 0.025)), iaa.Rain(nb_iterations=1, drop_size=(0.05, 0.1), speed=(0.04, 0.08)), iaa.AdditiveGaussianNoise(scale=(0, 10)), iaa.AdditiveLaplaceNoise(scale=(0, 10)), iaa.AdditivePoissonNoise(lam=(0, 10)), iaa.Salt((0, 0.02)), iaa.Pepper((0, 0.02)) ]) ]) polys = [ia.Polygon(pos) for pos in pos_list] polygons = ia.PolygonsOnImage(polys, shape=image.shape) images_aug, polygons_aug = seq(images=[image], polygons=polygons) image = images_aug[0] image = polygons_aug.draw_on_image(image, size=2) new_polys = [] for p in polygons_aug.polygons: new_polys.append(p.coords) polys = np.array(new_polys, np.int32).tolist() return image, polys