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generate_main_repo_readme_images.py
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generate_main_repo_readme_images.py
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from __future__ import print_function, division
import imgaug as ia
from imgaug import augmenters as iaa
import numpy as np
import imageio
from skimage import data
import matplotlib.pyplot as plt
import tempfile
import six.moves as sm
import re
import os
from collections import defaultdict
import PIL.Image
try:
from cStringIO import StringIO as BytesIO
except ImportError:
from io import BytesIO
np.random.seed(44)
ia.seed(44)
#IMAGES_DIR = "docs/readme_images"
IMAGES_DIR = "readme_images"
def main():
draw_small_overview()
#draw_single_sequential_images()
#draw_per_augmenter_videos()
def draw_small_overview():
ia.seed(44)
image = ia.quokka(size=0.2)
heatmap = ia.quokka_heatmap(size=0.2)
segmap = ia.quokka_segmentation_map(size=0.2)
kps = ia.quokka_keypoints(size=0.2)
bbs = ia.quokka_bounding_boxes(size=0.2)
polys = ia.quokka_polygons(size=0.2)
batch = ia.Batch(
images=[image],
heatmaps=[heatmap.invert()],
segmentation_maps=[segmap],
keypoints=[kps],
bounding_boxes=[bbs],
polygons=[polys]
)
augs = []
augs.append(("noop", iaa.Noop()))
augs.append(("non_geometric", iaa.Sequential([
iaa.AdditiveGaussianNoise(scale=(0, 20)),
iaa.ContrastNormalization(1.2),
iaa.Sharpen(alpha=1.0, lightness=1.5)
])))
augs.append(("affine", iaa.Affine(rotate=0, translate_percent={"x": 0.1}, scale=1.3, mode="constant", cval=25)))
augs.append(("cropandpad", iaa.CropAndPad(percent=(-0.05, 0.2, -0.05, -0.2), pad_mode="maximum")))
augs.append(("fliplr_perspective", iaa.Sequential([
iaa.Fliplr(1.0),
iaa.PerspectiveTransform(scale=0.15)
])))
for name, aug in augs:
result = list(aug.augment_batches([batch]))[0]
image_aug = result.images_aug[0]
image_aug_heatmap = result.heatmaps_aug[0].draw(cmap=None)[0]
image_aug_segmap = result.segmentation_maps_aug[0].draw_on_image(image_aug, alpha=0.8)
image_aug_kps = result.keypoints_aug[0].draw_on_image(image_aug, color=[0, 255, 0], size=7)
image_aug_bbs = result.bounding_boxes_aug[0].clip_out_of_image().draw_on_image(image_aug, size=3)
# add polys for now to BBs image to save (screen) space
image_aug_bbs = result.polygons_aug[0].clip_out_of_image().draw_on_image(
image_aug_bbs, color=[0, 128, 0], color_points=[0, 128, 0], alpha=0.0,
alpha_points=1.0, alpha_lines=0.5)
imageio.imwrite(os.path.join(IMAGES_DIR, "small_overview", "%s_image.jpg" % (name,)), image_aug, quality=90)
imageio.imwrite(os.path.join(IMAGES_DIR, "small_overview", "%s_heatmap.jpg" % (name,)), image_aug_heatmap, quality=90)
imageio.imwrite(os.path.join(IMAGES_DIR, "small_overview", "%s_segmap.jpg" % (name,)), image_aug_segmap, quality=90)
imageio.imwrite(os.path.join(IMAGES_DIR, "small_overview", "%s_kps.jpg" % (name,)), image_aug_kps, quality=90)
imageio.imwrite(os.path.join(IMAGES_DIR, "small_overview", "%s_bbs.jpg" % (name,)), image_aug_bbs, quality=90)
def draw_single_sequential_images():
ia.seed(44)
#image = ia.imresize_single_image(imageio.imread("quokka.jpg", pilmode="RGB")[0:643, 0:643], (128, 128))
image = ia.quokka_square(size=(128, 128))
sometimes = lambda aug: iaa.Sometimes(0.5, aug)
seq = iaa.Sequential(
[
# apply the following augmenters to most images
iaa.Fliplr(0.5), # horizontally flip 50% of all images
iaa.Flipud(0.2), # vertically flip 20% of all images
# crop images by -5% to 10% of their height/width
sometimes(iaa.CropAndPad(
percent=(-0.05, 0.1),
pad_mode=ia.ALL,
pad_cval=(0, 255)
)),
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": (-0.2, 0.2), "y": (-0.2, 0.2)}, # translate by -20 to +20 percent (per axis)
rotate=(-45, 45), # rotate by -45 to +45 degrees
shear=(-16, 16), # 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)
)),
# execute 0 to 5 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, 5),
[
sometimes(iaa.Superpixels(p_replace=(0, 1.0), n_segments=(20, 200))), # convert images into their superpixel representation
iaa.OneOf([
iaa.GaussianBlur((0, 3.0)), # blur images with a sigma between 0 and 3.0
iaa.AverageBlur(k=(2, 7)), # blur image using local means with kernel sizes between 2 and 7
iaa.MedianBlur(k=(3, 11)), # blur image using local medians with kernel sizes between 2 and 7
]),
iaa.Sharpen(alpha=(0, 1.0), lightness=(0.75, 1.5)), # sharpen images
iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0)), # emboss images
# search either for all edges or for directed edges,
# blend the result with the original image using a blobby mask
iaa.SimplexNoiseAlpha(iaa.OneOf([
iaa.EdgeDetect(alpha=(0.5, 1.0)),
iaa.DirectedEdgeDetect(alpha=(0.5, 1.0), direction=(0.0, 1.0)),
])),
iaa.AdditiveGaussianNoise(loc=0, scale=(0.0, 0.05*255), per_channel=0.5), # add gaussian noise to images
iaa.OneOf([
iaa.Dropout((0.01, 0.1), per_channel=0.5), # randomly remove up to 10% of the pixels
iaa.CoarseDropout((0.03, 0.15), size_percent=(0.02, 0.05), per_channel=0.2),
]),
iaa.Invert(0.05, per_channel=True), # invert color channels
iaa.Add((-10, 10), per_channel=0.5), # change brightness of images (by -10 to 10 of original value)
iaa.AddToHueAndSaturation((-20, 20)), # change hue and saturation
# either change the brightness of the whole image (sometimes
# per channel) or change the brightness of subareas
iaa.OneOf([
iaa.Multiply((0.5, 1.5), per_channel=0.5),
iaa.FrequencyNoiseAlpha(
exponent=(-4, 0),
first=iaa.Multiply((0.5, 1.5), per_channel=True),
second=iaa.ContrastNormalization((0.5, 2.0))
)
]),
iaa.ContrastNormalization((0.5, 2.0), per_channel=0.5), # improve or worsen the contrast
iaa.Grayscale(alpha=(0.0, 1.0)),
sometimes(iaa.ElasticTransformation(alpha=(0.5, 3.5), sigma=0.25)), # move pixels locally around (with random strengths)
sometimes(iaa.PiecewiseAffine(scale=(0.01, 0.05))), # sometimes move parts of the image around
sometimes(iaa.PerspectiveTransform(scale=(0.01, 0.1)))
],
random_order=True
)
],
random_order=True
)
grid = seq.draw_grid(image, cols=8, rows=8)
imageio.imwrite(os.path.join(IMAGES_DIR, "examples_grid.jpg"), grid)
def draw_per_augmenter_images():
print("[draw_per_augmenter_images] Loading image...")
#image = ia.imresize_single_image(imageio.imread("quokka.jpg", pilmode="RGB")[0:643, 0:643], (128, 128))
image = ia.quokka_square(size=(128, 128))
keypoints = [ia.Keypoint(x=34, y=15), ia.Keypoint(x=85, y=13), ia.Keypoint(x=63, y=73)] # left ear, right ear, mouth
keypoints = [ia.KeypointsOnImage(keypoints, shape=image.shape)]
print("[draw_per_augmenter_images] Initializing...")
rows_augmenters = [
(0, "Noop", [("", iaa.Noop()) for _ in sm.xrange(5)]),
(0, "Crop\n(top, right,\nbottom, left)", [(str(vals), iaa.Crop(px=vals)) for vals in [(2, 0, 0, 0), (0, 8, 8, 0), (4, 0, 16, 4), (8, 0, 0, 32), (32, 64, 0, 0)]]),
(0, "Pad\n(top, right,\nbottom, left)", [(str(vals), iaa.Pad(px=vals)) for vals in [(2, 0, 0, 0), (0, 8, 8, 0), (4, 0, 16, 4), (8, 0, 0, 32), (32, 64, 0, 0)]]),
(0, "Fliplr", [(str(p), iaa.Fliplr(p)) for p in [0, 0, 1, 1, 1]]),
(0, "Flipud", [(str(p), iaa.Flipud(p)) for p in [0, 0, 1, 1, 1]]),
(0, "Superpixels\np_replace=1", [("n_segments=%d" % (n_segments,), iaa.Superpixels(p_replace=1.0, n_segments=n_segments)) for n_segments in [25, 50, 75, 100, 125]]),
(0, "Superpixels\nn_segments=100", [("p_replace=%.2f" % (p_replace,), iaa.Superpixels(p_replace=p_replace, n_segments=100)) for p_replace in [0, 0.25, 0.5, 0.75, 1.0]]),
(0, "Invert", [("p=%d" % (p,), iaa.Invert(p=p)) for p in [0, 0, 1, 1, 1]]),
(0, "Invert\n(per_channel)", [("p=%.2f" % (p,), iaa.Invert(p=p, per_channel=True)) for p in [0.5, 0.5, 0.5, 0.5, 0.5]]),
(0, "Add", [("value=%d" % (val,), iaa.Add(val)) for val in [-45, -25, 0, 25, 45]]),
(0, "Add\n(per channel)", [("value=(%d, %d)" % (vals[0], vals[1],), iaa.Add(vals, per_channel=True)) for vals in [(-55, -35), (-35, -15), (-10, 10), (15, 35), (35, 55)]]),
(0, "AddToHueAndSaturation", [("value=%d" % (val,), iaa.AddToHueAndSaturation(val)) for val in [-45, -25, 0, 25, 45]]),
(0, "Multiply", [("value=%.2f" % (val,), iaa.Multiply(val)) for val in [0.25, 0.5, 1.0, 1.25, 1.5]]),
(1, "Multiply\n(per channel)", [("value=(%.2f, %.2f)" % (vals[0], vals[1],), iaa.Multiply(vals, per_channel=True)) for vals in [(0.15, 0.35), (0.4, 0.6), (0.9, 1.1), (1.15, 1.35), (1.4, 1.6)]]),
(0, "GaussianBlur", [("sigma=%.2f" % (sigma,), iaa.GaussianBlur(sigma=sigma)) for sigma in [0.25, 0.50, 1.0, 2.0, 4.0]]),
(0, "AverageBlur", [("k=%d" % (k,), iaa.AverageBlur(k=k)) for k in [1, 3, 5, 7, 9]]),
(0, "MedianBlur", [("k=%d" % (k,), iaa.MedianBlur(k=k)) for k in [1, 3, 5, 7, 9]]),
(0, "BilateralBlur\nsigma_color=250,\nsigma_space=250", [("d=%d" % (d,), iaa.BilateralBlur(d=d, sigma_color=250, sigma_space=250)) for d in [1, 3, 5, 7, 9]]),
(0, "Sharpen\n(alpha=1)", [("lightness=%.2f" % (lightness,), iaa.Sharpen(alpha=1, lightness=lightness)) for lightness in [0, 0.5, 1.0, 1.5, 2.0]]),
(0, "Emboss\n(alpha=1)", [("strength=%.2f" % (strength,), iaa.Emboss(alpha=1, strength=strength)) for strength in [0, 0.5, 1.0, 1.5, 2.0]]),
(0, "EdgeDetect", [("alpha=%.2f" % (alpha,), iaa.EdgeDetect(alpha=alpha)) for alpha in [0.0, 0.25, 0.5, 0.75, 1.0]]),
(0, "DirectedEdgeDetect\n(alpha=1)", [("direction=%.2f" % (direction,), iaa.DirectedEdgeDetect(alpha=1, direction=direction)) for direction in [0.0, 1*(360/5)/360, 2*(360/5)/360, 3*(360/5)/360, 4*(360/5)/360]]),
(0, "AdditiveGaussianNoise", [("scale=%.2f*255" % (scale,), iaa.AdditiveGaussianNoise(scale=scale * 255)) for scale in [0.025, 0.05, 0.1, 0.2, 0.3]]),
(0, "AdditiveGaussianNoise\n(per channel)", [("scale=%.2f*255" % (scale,), iaa.AdditiveGaussianNoise(scale=scale * 255, per_channel=True)) for scale in [0.025, 0.05, 0.1, 0.2, 0.3]]),
(0, "Dropout", [("p=%.2f" % (p,), iaa.Dropout(p=p)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]),
(0, "Dropout\n(per channel)", [("p=%.2f" % (p,), iaa.Dropout(p=p, per_channel=True)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]),
(3, "CoarseDropout\n(p=0.2)", [("size_percent=%.2f" % (size_percent,), iaa.CoarseDropout(p=0.2, size_percent=size_percent, min_size=2)) for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]),
(0, "CoarseDropout\n(p=0.2, per channel)", [("size_percent=%.2f" % (size_percent,), iaa.CoarseDropout(p=0.2, size_percent=size_percent, per_channel=True, min_size=2)) for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]),
(0, "SaltAndPepper", [("p=%.2f" % (p,), iaa.SaltAndPepper(p=p)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]),
(0, "Salt", [("p=%.2f" % (p,), iaa.Salt(p=p)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]),
(0, "Pepper", [("p=%.2f" % (p,), iaa.Pepper(p=p)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]),
(0, "CoarseSaltAndPepper\n(p=0.2)", [("size_percent=%.2f" % (size_percent,), iaa.CoarseSaltAndPepper(p=0.2, size_percent=size_percent, min_size=2)) for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]),
(0, "CoarseSalt\n(p=0.2)", [("size_percent=%.2f" % (size_percent,), iaa.CoarseSalt(p=0.2, size_percent=size_percent, min_size=2)) for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]),
(0, "CoarsePepper\n(p=0.2)", [("size_percent=%.2f" % (size_percent,), iaa.CoarsePepper(p=0.2, size_percent=size_percent, min_size=2)) for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]),
(0, "ContrastNormalization", [("alpha=%.1f" % (alpha,), iaa.ContrastNormalization(alpha=alpha)) for alpha in [0.5, 0.75, 1.0, 1.25, 1.50]]),
(0, "ContrastNormalization\n(per channel)", [("alpha=(%.2f, %.2f)" % (alphas[0], alphas[1],), iaa.ContrastNormalization(alpha=alphas, per_channel=True)) for alphas in [(0.4, 0.6), (0.65, 0.85), (0.9, 1.1), (1.15, 1.35), (1.4, 1.6)]]),
(0, "Grayscale", [("alpha=%.1f" % (alpha,), iaa.Grayscale(alpha=alpha)) for alpha in [0.0, 0.25, 0.5, 0.75, 1.0]]),
(6, "PerspectiveTransform", [("scale=%.3f" % (scale,), iaa.PerspectiveTransform(scale=scale)) for scale in [0.025, 0.05, 0.075, 0.10, 0.125]]),
(0, "PiecewiseAffine", [("scale=%.3f" % (scale,), iaa.PiecewiseAffine(scale=scale)) for scale in [0.015, 0.03, 0.045, 0.06, 0.075]]),
(0, "Affine: Scale", [("%.1fx" % (scale,), iaa.Affine(scale=scale)) for scale in [0.1, 0.5, 1.0, 1.5, 1.9]]),
(0, "Affine: Translate", [("x=%d y=%d" % (x, y), iaa.Affine(translate_px={"x": x, "y": y})) for x, y in [(-32, -16), (-16, -32), (-16, -8), (16, 8), (16, 32)]]),
(0, "Affine: Rotate", [("%d deg" % (rotate,), iaa.Affine(rotate=rotate)) for rotate in [-90, -45, 0, 45, 90]]),
(0, "Affine: Shear", [("%d deg" % (shear,), iaa.Affine(shear=shear)) for shear in [-45, -25, 0, 25, 45]]),
(0, "Affine: Modes", [(mode, iaa.Affine(translate_px=-32, mode=mode)) for mode in ["constant", "edge", "symmetric", "reflect", "wrap"]]),
(0, "Affine: cval", [("%d" % (int(cval*255),), iaa.Affine(translate_px=-32, cval=int(cval*255), mode="constant")) for cval in [0.0, 0.25, 0.5, 0.75, 1.0]]),
(
2, "Affine: all", [
(
"",
iaa.Affine(
scale={"x": (0.5, 1.5), "y": (0.5, 1.5)},
translate_px={"x": (-32, 32), "y": (-32, 32)},
rotate=(-45, 45),
shear=(-32, 32),
mode=ia.ALL,
cval=(0.0, 1.0)
)
)
for _ in sm.xrange(5)
]
),
(1, "ElasticTransformation\n(sigma=0.2)", [("alpha=%.1f" % (alpha,), iaa.ElasticTransformation(alpha=alpha, sigma=0.2)) for alpha in [0.1, 0.5, 1.0, 3.0, 9.0]]),
(0, "Alpha\nwith EdgeDetect(1.0)", [("factor=%.1f" % (factor,), iaa.Alpha(factor=factor, first=iaa.EdgeDetect(1.0))) for factor in [0.0, 0.25, 0.5, 0.75, 1.0]]),
(4, "Alpha\nwith EdgeDetect(1.0)\n(per channel)", [("factor=(%.2f, %.2f)" % (factor[0], factor[1]), iaa.Alpha(factor=factor, first=iaa.EdgeDetect(1.0), per_channel=0.5)) for factor in [(0.0, 0.2), (0.15, 0.35), (0.4, 0.6), (0.65, 0.85), (0.8, 1.0)]]),
(15, "SimplexNoiseAlpha\nwith EdgeDetect(1.0)", [("", iaa.SimplexNoiseAlpha(first=iaa.EdgeDetect(1.0))) for alpha in [0.0, 0.25, 0.5, 0.75, 1.0]]),
(9, "FrequencyNoiseAlpha\nwith EdgeDetect(1.0)", [("exponent=%.1f" % (exponent,), iaa.FrequencyNoiseAlpha(exponent=exponent, first=iaa.EdgeDetect(1.0), size_px_max=16, upscale_method="linear", sigmoid=False)) for exponent in [-4, -2, 0, 2, 4]])
]
print("[draw_per_augmenter_images] Augmenting...")
rows = []
for (row_seed, row_name, augmenters) in rows_augmenters:
ia.seed(row_seed)
#for img_title, augmenter in augmenters:
# #aug.reseed(1000)
# pass
row_images = []
row_keypoints = []
row_titles = []
for img_title, augmenter in augmenters:
aug_det = augmenter.to_deterministic()
row_images.append(aug_det.augment_image(image))
row_keypoints.append(aug_det.augment_keypoints(keypoints)[0])
row_titles.append(img_title)
rows.append((row_name, row_images, row_keypoints, row_titles))
# matplotlib drawin routine
"""
print("[draw_per_augmenter_images] Plotting...")
width = 8
height = int(1.5 * len(rows_augmenters))
fig = plt.figure(figsize=(width, height))
grid_rows = len(rows)
grid_cols = 1 + 5
gs = gridspec.GridSpec(grid_rows, grid_cols, width_ratios=[2, 1, 1, 1, 1, 1])
axes = []
for i in sm.xrange(grid_rows):
axes.append([plt.subplot(gs[i, col_idx]) for col_idx in sm.xrange(grid_cols)])
fig.tight_layout()
#fig.subplots_adjust(bottom=0.2 / grid_rows, hspace=0.22)
#fig.subplots_adjust(wspace=0.005, hspace=0.425, bottom=0.02)
fig.subplots_adjust(wspace=0.005, hspace=0.005, bottom=0.02)
for row_idx, (row_name, row_images, row_keypoints, row_titles) in enumerate(rows):
axes_row = axes[row_idx]
for col_idx in sm.xrange(grid_cols):
ax = axes_row[col_idx]
ax.cla()
ax.axis("off")
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
if col_idx == 0:
ax.text(0, 0.5, row_name, color="black")
else:
cell_image = row_images[col_idx-1]
cell_keypoints = row_keypoints[col_idx-1]
cell_image_kp = cell_keypoints.draw_on_image(cell_image, size=5)
ax.imshow(cell_image_kp)
x = 0
y = 145
#ax.text(x, y, row_titles[col_idx-1], color="black", backgroundcolor="white", fontsize=6)
ax.text(x, y, row_titles[col_idx-1], color="black", fontsize=7)
fig.savefig("examples.jpg", bbox_inches="tight")
#plt.show()
"""
# simpler and faster drawing routine
"""
output_image = ExamplesImage(128, 128, 128+64, 32)
for (row_name, row_images, row_keypoints, row_titles) in rows:
row_images_kps = []
for image, keypoints in zip(row_images, row_keypoints):
row_images_kps.append(keypoints.draw_on_image(image, size=5))
output_image.add_row(row_name, row_images_kps, row_titles)
imageio.imwrite("examples.jpg", output_image.draw())
"""
# routine to draw many single files
seen = defaultdict(lambda: 0)
markups = []
for (row_name, row_images, row_keypoints, row_titles) in rows:
output_image = ExamplesImage(128, 128, 128+64, 32)
row_images_kps = []
for image, keypoints in zip(row_images, row_keypoints):
row_images_kps.append(keypoints.draw_on_image(image, size=5))
output_image.add_row(row_name, row_images_kps, row_titles)
if "\n" in row_name:
row_name_clean = row_name[0:row_name.find("\n")+1]
else:
row_name_clean = row_name
row_name_clean = re.sub(r"[^a-z0-9]+", "_", row_name_clean.lower())
row_name_clean = row_name_clean.strip("_")
if seen[row_name_clean] > 0:
row_name_clean = "%s_%d" % (row_name_clean, seen[row_name_clean] + 1)
fp = os.path.join(IMAGES_DIR, "examples_%s.jpg" % (row_name_clean,))
#imageio.imwrite(fp, output_image.draw())
save(fp, output_image.draw())
seen[row_name_clean] += 1
markup_descr = row_name.replace('"', '') \
.replace("\n", " ") \
.replace("(", "") \
.replace(")", "")
markup = '' % (markup_descr, fp, markup_descr)
markups.append(markup)
for markup in markups:
print(markup)
class ExamplesImage(object):
def __init__(self, image_height, image_width, title_cell_width, subtitle_height):
self.rows = []
self.image_height = image_height
self.image_width = image_width
self.title_cell_width = title_cell_width
self.cell_height = image_height + subtitle_height
self.cell_width = image_width
def add_row(self, title, images, subtitles):
assert len(images) == len(subtitles)
images_rs = []
for image in images:
images_rs.append(ia.imresize_single_image(image, (self.image_height, self.image_width)))
self.rows.append((title, images_rs, subtitles))
def draw(self):
rows_drawn = [self.draw_row(title, images, subtitles) for title, images, subtitles in self.rows]
grid = np.vstack(rows_drawn)
return grid
def draw_row(self, title, images, subtitles):
title_cell = np.zeros((self.cell_height, self.title_cell_width, 3), dtype=np.uint8) + 255
title_cell = ia.draw_text(title_cell, x=2, y=12, text=title, color=[0, 0, 0], size=16)
image_cells = []
for image, subtitle in zip(images, subtitles):
image_cell = np.zeros((self.cell_height, self.cell_width, 3), dtype=np.uint8) + 255
image_cell[0:image.shape[0], 0:image.shape[1], :] = image
image_cell = ia.draw_text(image_cell, x=2, y=image.shape[0]+2, text=subtitle, color=[0, 0, 0], size=11)
image_cells.append(image_cell)
row = np.hstack([title_cell] + image_cells)
return row
def slugify(s):
return re.sub(r"[^a-z0-9]+", "_", s.lower()).strip("_")
def draw_per_augmenter_videos():
class _Descriptor(object):
def __init__(self, module, title, augmenters, subtitles, seed=0, affects_geometry=False, comment=None):
self.module = module
self.title = title
self.augmenters = augmenters
self.subtitles = subtitles
self.seed = seed
self.affects_geometry = affects_geometry
self.comment = comment
@property
def title_markup(self):
return self.title.replace('"', '') \
.replace("\n", " ") \
.replace("(", "") \
.replace(")", "")
@classmethod
def from_augsubs(cls, module, title, augsubs, seed=0, affects_geometry=False, comment=None):
return _Descriptor(module=module, title=title,
augmenters=[el[1] for el in augsubs],
subtitles=[el[0] for el in augsubs],
seed=seed, affects_geometry=affects_geometry, comment=comment)
def generate_frames(self, image, keypoints, bounding_boxes, polygons, heatmap, segmap, subtitle_height):
frames_images = []
frames_kps = []
frames_bbs = []
frames_heatmap = []
frames_segmap = []
any_subtitle = any([len(subtitle) > 0 for subtitle in self.subtitles])
for i, (augmenter, subtitle) in enumerate(zip(self.augmenters, self.subtitles)):
# print("seeding", augmenter.name, self.seed+i)
augmenter.localize_random_state_(recursive=True)
augmenter.reseed(random_state=self.seed+i)
def _subt(img, toptitle):
if self.affects_geometry:
#return self._draw_cell(img, subtitle, subtitle_height if any_subtitle else 0, toptitle, 16)
return self._draw_cell(img, subtitle, subtitle_height, toptitle, 16)
else:
#return self._draw_cell(img, subtitle, subtitle_height if any_subtitle else 0, "", 0)
return self._draw_cell(img, subtitle, subtitle_height, "", 16)
aug_det = augmenter.to_deterministic()
image_aug = aug_det.augment_image(image)
kps_aug = aug_det.augment_keypoints([keypoints])[0]
bbs_aug = aug_det.augment_bounding_boxes([bounding_boxes])[0]
polys_aug = aug_det.augment_polygons([polygons])[0]
heatmap_aug = aug_det.augment_heatmaps([heatmap])[0]
segmap_aug = aug_det.augment_segmentation_maps([segmap])[0]
if self.affects_geometry:
image_with_coordsaug = _subt(
polys_aug.draw_on_image(
bbs_aug.draw_on_image(
kps_aug.draw_on_image(image_aug, size=5)
),
color_lines=(0, 128, 0),
color_points=(0, 128, 0),
alpha=0,
alpha_lines=0.5,
alpha_points=1.0
),
"IMG, KPs, BBs, Polys"
)
frames_images.append(image_with_coordsaug)
#frames_kps.append(_subt(kps_aug.draw_on_image(image_aug, size=5), "keypoints"))
#frames_bbs.append(_subt(bbs_aug.draw_on_image(image_aug), "bounding boxes"))
#frames_kps.append(_subt(
# bbs_aug.draw_on_image(kps_aug.draw_on_image(image_aug, size=5)),
# "Keypoints + BBs"
#))
frames_heatmap.append(_subt(heatmap_aug.draw_on_image(image_aug)[0], "Heatmaps"))
frames_segmap.append(_subt(segmap_aug.draw_on_image(image_aug), "Segmentation Maps"))
else:
frames_images.append(_subt(image_aug, "Images"))
return frames_images, frames_kps, frames_bbs, frames_heatmap, frames_segmap
@classmethod
def _draw_cell(cls, image, subtitle, subtitle_height, toptitle, toptitle_height):
cell_height, cell_width = image.shape[0:2]
image_cell = np.zeros((toptitle_height + cell_height + subtitle_height, cell_width, 3), dtype=np.uint8) + 255
image_cell[toptitle_height:toptitle_height+image.shape[0], 0:image.shape[1], :] = image
image_cell = ia.draw_text(image_cell, x=2, y=toptitle_height + image.shape[0]+2, text=subtitle, color=[0, 0, 0], size=9)
if toptitle != "":
image_cell = ia.draw_text(image_cell, x=2, y=2, text=toptitle, color=[0, 0, 0], size=9)
return image_cell
class _MarkdownTableCell(object):
def __init__(self, descriptor, markup_images, markup_kps, markup_bbs, markup_hm, markup_segmap):
self.descriptor = descriptor
self.markup_images = markup_images
self.markup_kps = markup_kps
self.markup_bbs = markup_bbs
self.markup_hm = markup_hm
self.markup_segmap = markup_segmap
@property
def colspan(self):
#only_images = len(self.markup_kps) == 0 and len(self.markup_bbs) == 0 and len(self.markup_hm) == 0 and len(self.markup_segmap) == 0
only_images = not self.descriptor.affects_geometry
return 1 if only_images else 2
def render_title(self):
#return '<td colspan="%d">\n<small>\n%s\n</small>\n</td>' % (self.colspan, self.descriptor.title.replace("\n", "<br/>"))
return '<td colspan="%d"><sub>%s</sub></td>' % (self.colspan, self.descriptor.title.replace("\n", "<br/>"))
def render_main(self):
#return '<td colspan="%d">\n\n%s%s%s%s%s\n\n</td>' % (self.colspan, self.markup_images, self.markup_kps, self.markup_bbs, self.markup_hm, self.markup_segmap)
return '<td colspan="%d">%s%s%s%s%s</td>' % (self.colspan, self.markup_images, self.markup_kps, self.markup_bbs, self.markup_hm, self.markup_segmap)
def render_comment(self):
if self.descriptor.comment is not None:
#return '<td colspan="%d">\n<small>\n\n%s\n\n</small>\n</td>' % (self.colspan, self.descriptor.comment,)
return '<td colspan="%d"><sub>%s</sub></td>' % (self.colspan, self.descriptor.comment,)
else:
return '<td colspan="%d"> </td>' % (self.colspan,)
class _MarkdownTable(object):
ROW_SIZE = 5 # in columns
def __init__(self):
self.cells = []
def render(self):
current_module = None
first_row_in_module = True
markup = []
cells = self.cells
while len(cells) > 0:
current_row_size = 0
row_title = []
row_main = []
row_comment = []
any_comment = False
while current_row_size < self.ROW_SIZE and len(cells) > 0:
cell = cells[0]
if current_module is None:
current_module = cell.descriptor.module
elif current_module != cell.descriptor.module:
if current_row_size == 0:
current_module = cell.descriptor.module
first_row_in_module = True
else:
break
if cell.colspan > (self.ROW_SIZE - current_row_size):
break
row_title.append(cell.render_title())
row_main.append(cell.render_main())
row_comment.append(cell.render_comment())
if cell.descriptor.comment is not None and len(cell.descriptor.comment) > 0:
any_comment = True
current_row_size += cell.colspan
cells = cells[1:]
while current_row_size < self.ROW_SIZE:
row_title.append("<td> </td>")
row_main.append("<td> </td>")
row_comment.append("<td> </td>")
current_row_size += 1
if first_row_in_module:
#markup.append('<tr>\n<td colspan="3">\n\n**%s**\n\n</td>\n</tr>' % (current_module,))
markup.append('<tr><td colspan="%d"><strong>%s</strong></td></tr>' % (self.ROW_SIZE, current_module,))
first_row_in_module = False
markup.append("<tr>\n%s\n</tr>\n<tr>\n%s\n</tr>%s" % (
"\n".join(row_title),
"\n".join(row_main),
"" if not any_comment else "\n<tr>\n%s\n</tr>" % ("\n".join(row_comment),)
))
return "<table>\n\n%s\n\n</table>" % ("\n".join(markup),)
def append(self, descriptor, markup_images, markup_kps, markup_bbs, markup_hm, markup_segmap):
self.cells.append(_MarkdownTableCell(descriptor, markup_images, markup_kps, markup_bbs, markup_hm, markup_segmap))
print("[draw_per_augmenter_videos] Loading image...")
# image = ia.imresize_single_image(imageio.imread("quokka.jpg", pilmode="RGB")[0:643, 0:643], (128, 128))
h, w = 100, 100
h_subtitle = 32
image = ia.quokka_square(size=(h, w))
keypoints = ia.quokka_keypoints(size=(h, w), extract="square")
bbs = ia.quokka_bounding_boxes(size=(h, w), extract="square")
polygons = ia.quokka_polygons(size=(h, w), extract="square")
heatmap = ia.quokka_heatmap(size=(h, w), extract="square")
segmap = ia.quokka_segmentation_map(size=(h, w), extract="square")
image_landscape = imageio.imread("https://upload.wikimedia.org/wikipedia/commons/8/89/Kukle%2CCzech_Republic..jpg", format="jpg")
# os.path.join(os.path.dirname(os.path.abspath(__file__)), "landscape.jpg")
image_landscape = ia.imresize_single_image(image_landscape, (96, 128))
print("[draw_per_augmenter_videos] Initializing...")
descriptors = []
# ###
# meta
# ###
descriptors.extend([
# Augmenter (base class for all augmenters)
# Sequential
# SomeOf
# OneOf
# Sometimes
# WithChannels
_Descriptor.from_augsubs(
"meta",
"Noop",
[("", iaa.Noop()) for _ in sm.xrange(1)]),
# Lambda
# AssertLambda
# AssertShape
_Descriptor.from_augsubs(
"meta",
"ChannelShuffle",
[("p=1.0", iaa.ChannelShuffle(p=1.0)) for _ in sm.xrange(5)]
)
])
# ###
# arithmetic
# ###
descriptors.extend([
_Descriptor.from_augsubs(
"arithmetic",
"Add",
[("value=%d" % (val,), iaa.Add(val)) for val in [-45, -25, 0, 25, 45]]
),
_Descriptor.from_augsubs(
"arithmetic",
"Add\n(per_channel=True)",
[("value=(%d, %d)" % (vals[0], vals[1],), iaa.Add(vals, per_channel=True))
for vals in [(-55, -35), (-35, -15), (-10, 10), (15, 35), (35, 55)]]
),
# AddElementwise
_Descriptor.from_augsubs(
"arithmetic",
"AdditiveGaussianNoise",
[("scale=%.2f*255" % (scale,), iaa.AdditiveGaussianNoise(scale=scale * 255))
for scale in [0.025, 0.05, 0.1, 0.2, 0.3]]
),
_Descriptor.from_augsubs(
"arithmetic",
"AdditiveGaussianNoise\n(per_channel=True)",
[("scale=%.2f*255" % (scale,), iaa.AdditiveGaussianNoise(scale=scale * 255, per_channel=True))
for scale in [0.025, 0.05, 0.1, 0.2, 0.3]]
),
_Descriptor.from_augsubs(
"arithmetic",
"AdditiveLaplaceNoise",
[("scale=%.2f*255" % (scale,), iaa.AdditiveLaplaceNoise(scale=scale * 255))
for scale in [0.025, 0.05, 0.1, 0.2, 0.3]]
),
_Descriptor.from_augsubs(
"arithmetic",
"AdditiveLaplaceNoise\n(per_channel=True)",
[("scale=%.2f*255" % (scale,), iaa.AdditiveLaplaceNoise(scale=scale * 255, per_channel=True))
for scale in [0.025, 0.05, 0.1, 0.2, 0.3]]
),
_Descriptor.from_augsubs(
"arithmetic",
"AdditivePoissonNoise",
[("lam=%.2f" % (lam,), iaa.AdditivePoissonNoise(lam=lam))
for lam in [4.0, 8.0, 16.0, 32.0, 64.0]]
),
_Descriptor.from_augsubs(
"arithmetic",
"AdditivePoissonNoise\n(per_channel=True)",
[("lam=%.2f" % (lam,), iaa.AdditivePoissonNoise(lam=lam, per_channel=True))
for lam in [4.0, 8.0, 16.0, 32.0, 64.0]]
),
_Descriptor.from_augsubs(
"arithmetic",
"Multiply",
[("value=%.2f" % (val,), iaa.Multiply(val))
for val in [0.25, 0.5, 1.0, 1.25, 1.5]]
),
_Descriptor.from_augsubs(
"arithmetic",
"Multiply\n(per_channel=True)",
[("value=(%.2f, %.2f)" % (vals[0], vals[1],), iaa.Multiply(vals, per_channel=True))
for vals in [(0.15, 0.35), (0.4, 0.6), (0.9, 1.1), (1.15, 1.35), (1.4, 1.6)]]
),
# MultiplyElementwise
_Descriptor.from_augsubs(
"arithmetic",
"Dropout",
[("p=%.2f" % (p,), iaa.Dropout(p=p))
for p in [0.025, 0.05, 0.1, 0.2, 0.4]]
),
_Descriptor.from_augsubs(
"arithmetic",
"Dropout\n(per_channel=True)",
[("p=%.2f" % (p,), iaa.Dropout(p=p, per_channel=True))
for p in [0.025, 0.05, 0.1, 0.2, 0.4]]
),
_Descriptor.from_augsubs(
"arithmetic",
"CoarseDropout\n(p=0.2)",
[("size_percent=%.2f" % (size_percent,), iaa.CoarseDropout(p=0.2, size_percent=size_percent, min_size=2))
for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]
),
_Descriptor.from_augsubs(
"arithmetic",
"CoarseDropout\n(p=0.2, per_channel=True)",
[("size_percent=%.2f" % (size_percent,), iaa.CoarseDropout(p=0.2, size_percent=size_percent, per_channel=True, min_size=2))
for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]
),
# ReplaceElementwise
_Descriptor.from_augsubs(
"arithmetic",
"ImpulseNoise",
[("p=%.2f" % (p,), iaa.ImpulseNoise(p=p)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]
),
_Descriptor.from_augsubs(
"arithmetic",
"SaltAndPepper",
[("p=%.2f" % (p,), iaa.SaltAndPepper(p=p)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]
),
_Descriptor.from_augsubs(
"arithmetic",
"Salt",
[("p=%.2f" % (p,), iaa.Salt(p=p)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]
),
_Descriptor.from_augsubs(
"arithmetic",
"Pepper",
[("p=%.2f" % (p,), iaa.Pepper(p=p)) for p in [0.025, 0.05, 0.1, 0.2, 0.4]]
),
_Descriptor.from_augsubs(
"arithmetic",
"CoarseSaltAndPepper\n(p=0.2)",
[("size_percent=%.2f" % (size_percent,), iaa.CoarseSaltAndPepper(p=0.2, size_percent=size_percent, min_size=2))
for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]
),
_Descriptor.from_augsubs(
"arithmetic",
"CoarseSalt\n(p=0.2)",
[("size_percent=%.2f" % (size_percent,), iaa.CoarseSalt(p=0.2, size_percent=size_percent, min_size=2))
for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]
),
_Descriptor.from_augsubs(
"arithmetic",
"CoarsePepper\n(p=0.2)",
[("size_percent=%.2f" % (size_percent,), iaa.CoarsePepper(p=0.2, size_percent=size_percent, min_size=2))
for size_percent in [0.3, 0.2, 0.1, 0.05, 0.02]]
),
_Descriptor.from_augsubs(
"arithmetic",
"Invert",
[("p=%d" % (p,), iaa.Invert(p=p)) for p in [0, 1]]
),
_Descriptor.from_augsubs(
"arithmetic",
"Invert\n(per_channel=True)",
[("p=%.2f" % (p,), iaa.Invert(p=p, per_channel=True)) for p in [0.5, 0.5, 0.5, 0.5, 0.5]]
),
#_Descriptor.from_augsubs(
# "arithmetic",
# "ContrastNormalization",
# [("alpha=%.1f" % (alpha,), iaa.ContrastNormalization(alpha=alpha)) for alpha in [0.5, 0.75, 1.0, 1.25, 1.50]]
#),
#_Descriptor.from_augsubs(
# "arithmetic",
# "ContrastNormalization\n(per channel)",
# [("alpha=(%.2f, %.2f)" % (alphas[0], alphas[1],), iaa.ContrastNormalization(alpha=alphas, per_channel=True))
# for alphas in [(0.4, 0.6), (0.65, 0.85), (0.9, 1.1), (1.15, 1.35), (1.4, 1.6)]]
#),
_Descriptor.from_augsubs(
"arithmetic",
"JpegCompression",
[("compression=%d" % (compression,), iaa.JpegCompression(compression=compression))
for compression in np.linspace(50, 100, num=5)]
)
])
# ###
# blur
# ###
descriptors.extend([
_Descriptor.from_augsubs(
"blur",
"GaussianBlur",
[("sigma=%.2f" % (sigma,), iaa.GaussianBlur(sigma=sigma))
for sigma in [0.25, 0.50, 1.0, 2.0, 4.0]]
),
_Descriptor.from_augsubs(
"blur",
"AverageBlur",
[("k=%d" % (k,), iaa.AverageBlur(k=k))
for k in [1, 3, 5, 7, 9]]
),
_Descriptor.from_augsubs(
"blur",
"MedianBlur",
[("k=%d" % (k,), iaa.MedianBlur(k=k))
for k in [1, 3, 5, 7, 9]]
),
_Descriptor.from_augsubs(
"blur",
"BilateralBlur\n(sigma_color=250,\nsigma_space=250)",
[("d=%d" % (d,), iaa.BilateralBlur(d=d, sigma_color=250, sigma_space=250))
for d in [1, 3, 5, 7, 9]]
),
_Descriptor.from_augsubs(
"blur",
"MotionBlur\n(angle=0)",
[("k=%d" % (k,), iaa.MotionBlur(k=k, angle=0)) for k in [3, 5, 7, 11, 13]]
),
_Descriptor.from_augsubs(
"blur",
"MotionBlur\n(k=5)",
[("angle=%d" % (angle,), iaa.MotionBlur(k=5, angle=angle))
for angle in np.linspace(0, 360-360/5, num=5)]
)
])
# ####
# color
# ####
descriptors.extend([
# WithColorspace
_Descriptor.from_augsubs(
"color",
"AddToHueAndSaturation",
[("value=%d" % (val,), iaa.AddToHueAndSaturation(val)) for val in [-45, -25, 0, 25, 45]]
),
_Descriptor.from_augsubs(
"color",
"Grayscale",
[("alpha=%.1f" % (alpha,), iaa.Grayscale(alpha=alpha)) for alpha in [0.0, 0.25, 0.5, 0.75, 1.0]]
)
# ChangeColorspace
])
# ####
# contrast
# ####
descriptors.extend([
_Descriptor.from_augsubs(
"contrast",
"GammaContrast",
[("gamma=%.2f" % (gamma,), iaa.GammaContrast(gamma=gamma)) for gamma in np.linspace(0.5, 1.75, num=5)]
),
_Descriptor.from_augsubs(
"contrast",
"GammaContrast\n(per_channel=True)",
[("gamma=(0.5, 1.75)", iaa.GammaContrast(gamma=(0.5, 1.75), per_channel=True)) for _ in range(5)]
),
_Descriptor.from_augsubs(
"contrast",
"SigmoidContrast\n(cutoff=0.5)",
[("gain=%.1f" % (gain,), iaa.SigmoidContrast(gain=gain, cutoff=0.5))
for gain in np.linspace(5, 17.5, num=5)]
),
_Descriptor.from_augsubs(
"contrast",
"SigmoidContrast\n(gain=10)",
[("cutoff=%.2f" % (cutoff,), iaa.SigmoidContrast(gain=10, cutoff=cutoff))
for cutoff in np.linspace(0.0, 1.0, num=5)]
),
_Descriptor.from_augsubs(
"contrast",
"SigmoidContrast\n(per_channel=True)",
[("gain=(5, 15),\ncutoff=(0.0, 1.0)", iaa.SigmoidContrast(gain=(5, 15), cutoff=(0.0, 1.0), per_channel=True))
for _ in range(5)]
),
_Descriptor.from_augsubs(
"contrast",
"LogContrast",
[("gain=%.2f" % (gain,), iaa.LogContrast(gain=gain)) for gain in np.linspace(0.5, 1.0, num=5)]
),
_Descriptor.from_augsubs(
"contrast",
"LogContrast\n(per_channel=True)",
[("gain=(0.5, 1.0)", iaa.LogContrast(gain=(0.5, 1.0), per_channel=True)) for _ in range(5)]
),
_Descriptor.from_augsubs(
"contrast",
"LinearContrast",
[("alpha=%.2f" % (alpha,), iaa.LinearContrast(alpha=alpha)) for alpha in np.linspace(0.25, 1.75, num=5)]
),
_Descriptor.from_augsubs(
"contrast",
"LinearContrast\n(per_channel=True)",
[("alpha=(0.25, 1.75)", iaa.LinearContrast(alpha=(0.25, 1.75), per_channel=True)) for _ in range(5)]
),
_Descriptor.from_augsubs(
"contrast",
"AllChannels-\nHistogramEqualization",
[("", iaa.AllChannelsHistogramEqualization()) for _ in range(1)]
),
_Descriptor.from_augsubs(
"contrast",
"HistogramEqualization",
[("to_colorspace=%s" % (to_colorspace,), iaa.HistogramEqualization(to_colorspace=to_colorspace))
for to_colorspace
in [iaa.HistogramEqualization.Lab, iaa.HistogramEqualization.HSV, iaa.HistogramEqualization.HLS]]
),
_Descriptor.from_augsubs(
"contrast",
"AllChannelsCLAHE",
[("clip_limit=%d" % (int(clip_limit),), iaa.AllChannelsCLAHE(clip_limit=int(clip_limit)))
for clip_limit
in np.linspace(1, 20, num=5)]
),
_Descriptor.from_augsubs(
"contrast",
"AllChannelsCLAHE\n(per_channel=True)",
[("clip_limit=(1, 20)", iaa.AllChannelsCLAHE(clip_limit=(1, 20), per_channel=True)) for _ in range(5)],
seed=4
),
_Descriptor.from_augsubs(
"contrast",
"CLAHE",
[("clip_limit=%d,\nto_colorspace=%s" % (int(clip_limit), to_colorspace),
iaa.CLAHE(clip_limit=int(clip_limit), to_colorspace=to_colorspace))
for to_colorspace, clip_limit
in zip([iaa.CLAHE.Lab] * 5, np.linspace(1, 20, num=5))]
),
])
# ###
# convolutional
# ###
descriptors.extend([
# Convolve
_Descriptor.from_augsubs(
"convolutional",
"Sharpen\n(alpha=1)",
[("lightness=%.2f" % (lightness,), iaa.Sharpen(alpha=1, lightness=lightness))
for lightness in [0, 0.5, 1.0, 1.5, 2.0]]),
_Descriptor.from_augsubs(
"convolutional",
"Emboss\n(alpha=1)",
[("strength=%.2f" % (strength,), iaa.Emboss(alpha=1, strength=strength))
for strength in [0, 0.5, 1.0, 1.5, 2.0]]),
_Descriptor.from_augsubs(
"convolutional",
"EdgeDetect",
[("alpha=%.2f" % (alpha,), iaa.EdgeDetect(alpha=alpha))
for alpha in [0.0, 0.25, 0.5, 0.75, 1.0]]),
_Descriptor.from_augsubs(
"convolutional",
"DirectedEdgeDetect\n(alpha=1)",
[("direction=%.2f" % (direction,), iaa.DirectedEdgeDetect(alpha=1, direction=direction))
for direction in [0.0, 1*(360/5)/360, 2*(360/5)/360, 3*(360/5)/360, 4*(360/5)/360]])
])
# ###
# flip
# ###
descriptors.extend([
_Descriptor.from_augsubs(
"flip",
"Fliplr",
[("p=%.1f" % (p,), iaa.Fliplr(p)) for p in [0, 1]],
affects_geometry=True),
_Descriptor.from_augsubs(
"flip",
"Flipud",
[("p=%.1f" % (p,), iaa.Flipud(p)) for p in [0, 1]],
affects_geometry=True)
])
# ###
# geometric
# ###
descriptors.extend([
_Descriptor.from_augsubs(
"geometric",
"Affine",
[("", iaa.Affine(scale={"x": (0.5, 1.5), "y": (0.5, 1.5)}, translate_px={"x": (-32, 32), "y": (-32, 32)}, rotate=(-45, 45), shear=(-32, 32), mode=["constant", "edge"], cval=(0.0, 1.0)))
for _ in sm.xrange(5)],
affects_geometry=True
),
#_Descriptor.from_augsubs(
# "geometric",
# "Affine: Scale",
# [("%.1fx" % (scale,), iaa.Affine(scale=scale)) for scale in [0.1, 0.5, 1.0, 1.5, 1.9]],
# affects_geometry=True),
#_Descriptor.from_augsubs(
# "geometric",
# "Affine: Translate",
# [("x=%d y=%d" % (x, y), iaa.Affine(translate_px={"x": x, "y": y}))
# for x, y in [(-32, -16), (-16, -32), (-16, -8), (16, 8), (16, 32)]],
# affects_geometry=True),
#_Descriptor.from_augsubs(
# "geometric",
# "Affine: Rotate",
# [("%d deg" % (rotate,), iaa.Affine(rotate=rotate)) for rotate in [-90, -45, 0, 45, 90]],
# affects_geometry=True),
#_Descriptor.from_augsubs(
# "geometric",
# "Affine: Shear",
# [("%d deg" % (shear,), iaa.Affine(shear=shear)) for shear in [-45, -25, 0, 25, 45]],
# affects_geometry=True),
_Descriptor.from_augsubs(
"geometric",
"Affine: Modes",
[("mode=%s" % (mode,), iaa.Affine(translate_px=-32, mode=mode)) for mode in ["constant", "edge", "symmetric", "reflect", "wrap"]],
affects_geometry=True
#comment='Augmentation of heatmaps and segmentation maps is currently always done with mode="constant" '
# + 'for consistency with keypoint and bounding box augmentation. It may be resonable to use '
# + 'mode="constant" for images too when augmenting heatmaps or segmentation maps.'
),
_Descriptor.from_augsubs(
"geometric",
"Affine: cval",
[("cval=%d" % (int(cval*255),), iaa.Affine(translate_px=-32, cval=int(cval*255), mode="constant"))
for cval in [0.0, 0.25, 0.5, 0.75, 1.0]],
affects_geometry=True),
# AffineCv2
_Descriptor.from_augsubs(
"geometric",