def transform(self, in_data):
augmenter = iaa.AffineCv2(
translate_percent=(-0.25, 0.25),
rotate=(-180, 180),
shear=(-15, 15),
)
augmenter = augmenter.to_deterministic()
shape = None
for index in self._rgb_indices:
if shape is None:
shape = in_data[index].shape[:2]
assert shape == in_data[index].shape[:2]
in_data[index] = augmenter.augment_image(in_data[index])
for index in self._mask_indices:
masks = in_data[index].astype(np.uint8)
masks = np.array([augmenter.augment_image(m) for m in masks])
in_data[index] = masks.astype(bool)
for index in self._bbox_indices:
bbox_on_img = imgaug.BoundingBoxesOnImage(
[
imgaug.BoundingBox(x1, y1, x2, y2)
for y1, x1, y2, x2 in in_data[index]
],
shape,
)
bbox_on_img = augmenter.augment_bounding_boxes(bbox_on_img)
bboxes = []
for bbox in bbox_on_img.bounding_boxes:
bboxes.append([bbox.y1, bbox.x1, bbox.y2, bbox.x2])
bboxes = np.array(bboxes, dtype=in_data[index].dtype)
in_data[index] = bboxes
def main():
image = data.astronaut()
image = ia.imresize_single_image(image, (HEIGHT, WIDTH))
kps = []
for y in range(NB_ROWS):
ycoord = BB_Y1 + int(y * (BB_Y2 - BB_Y1) / (NB_COLS - 1))
for x in range(NB_COLS):
xcoord = BB_X1 + int(x * (BB_X2 - BB_X1) / (NB_ROWS - 1))
kp = (xcoord, ycoord)
kps.append(kp)
kps = set(kps)
kps = [ia.Keypoint(x=xcoord, y=ycoord) for (xcoord, ycoord) in kps]
kps = ia.KeypointsOnImage(kps, shape=image.shape)
bb = ia.BoundingBox(x1=BB_X1, x2=BB_X2, y1=BB_Y1, y2=BB_Y2)
bbs = ia.BoundingBoxesOnImage([bb], shape=image.shape)
pairs = []
seqs = [
iaa.AffineCv2(rotate=45),
iaa.AffineCv2(translate_px=20),
iaa.AffineCv2(translate_percent=0.1),
iaa.AffineCv2(scale=1.2),
iaa.AffineCv2(scale=0.8),
iaa.AffineCv2(shear=45),
iaa.AffineCv2(rotate=45, cval=256),
iaa.AffineCv2(translate_px=20, mode=cv2.BORDER_CONSTANT),
iaa.AffineCv2(translate_px=20, mode=cv2.BORDER_REPLICATE),
iaa.AffineCv2(translate_px=20, mode=cv2.BORDER_REFLECT),
iaa.AffineCv2(translate_px=20, mode=cv2.BORDER_REFLECT_101),
iaa.AffineCv2(translate_px=20, mode=cv2.BORDER_WRAP),
iaa.AffineCv2(translate_px=20, mode="constant"),
iaa.AffineCv2(translate_px=20, mode="replicate"),
iaa.AffineCv2(translate_px=20, mode="reflect"),
iaa.AffineCv2(translate_px=20, mode="reflect_101"),
iaa.AffineCv2(translate_px=20, mode="wrap"),
iaa.AffineCv2(scale=0.5, order=cv2.INTER_NEAREST),
iaa.AffineCv2(scale=0.5, order=cv2.INTER_LINEAR),
iaa.AffineCv2(scale=0.5, order=cv2.INTER_CUBIC),
iaa.AffineCv2(scale=0.5, order=cv2.INTER_LANCZOS4),
iaa.AffineCv2(scale=0.5, order="nearest"),
iaa.AffineCv2(scale=0.5, order="linear"),
iaa.AffineCv2(scale=0.5, order="cubic"),
iaa.AffineCv2(scale=0.5, order="lanczos4"),
iaa.AffineCv2(rotate=45, translate_px=20, scale=1.2),
iaa.AffineCv2(rotate=45, translate_px=20, scale=0.8),
iaa.AffineCv2(rotate=(-45, 45),
translate_px=(-20, 20),
scale=(0.8, 1.2),
order=ia.ALL,
mode=ia.ALL,
cval=ia.ALL),
iaa.AffineCv2(rotate=(-45, 45),
translate_px=(-20, 20),
scale=(0.8, 1.2),
order=ia.ALL,
mode=ia.ALL,
cval=ia.ALL),
iaa.AffineCv2(rotate=(-45, 45),
translate_px=(-20, 20),
scale=(0.8, 1.2),
order=ia.ALL,
mode=ia.ALL,
cval=ia.ALL),
iaa.AffineCv2(rotate=(-45, 45),
translate_px=(-20, 20),
scale=(0.8, 1.2),
order=ia.ALL,
mode=ia.ALL,
cval=ia.ALL)
]
for seq in seqs:
seq_det = seq.to_deterministic()
image_aug = seq_det.augment_image(image)
#print(image_aug.dtype, np.min(image_aug), np.max(image_aug))
kps_aug = seq_det.augment_keypoints([kps])[0]
bbs_aug = seq_det.augment_bounding_boxes([bbs])[0]
image_before = np.copy(image)
image_before = kps.draw_on_image(image_before)
image_before = bbs.draw_on_image(image_before)
image_after = np.copy(image_aug)
image_after = kps_aug.draw_on_image(image_after)
image_after = bbs_aug.draw_on_image(image_after)
pairs.append(np.hstack((image_before, image_after)))
misc.imshow(np.vstack(pairs))
misc.imsave("affinecv2.jpg", np.vstack(pairs))
import os
import glob
import shutil
from csv import reader, writer
import cv2
folders = glob.glob('D:\\tsr\\train\\*')
images = []
counter = 0
counter2 = 0
counter3 = 0
aug = iaa.SomeOf(2, [
iaa.Affine(rotate=(-5, 5)),
iaa.AffineCv2(translate_px=8, mode=["replicate"]),
iaa.Affine(shear=(-8, 8), cval=(0, 255)),
iaa.AffineCv2(scale=(0.5, 1.5), order=[0, 1]),
iaa.Multiply((0.5, 1.5)),
iaa.AverageBlur(k=(2, 5)),
iaa.MedianBlur(k=(3, 7)),
iaa.GaussianBlur(sigma=(1.0, 3.0)),
iaa.Sharpen(alpha=(0, 0.6), lightness=(0.75, 1.5)),
iaa.Emboss(alpha=(0, 0.85), strength=(0, 1.5)),
iaa.LinearContrast((0.5, 2.0), per_channel=0.5),
iaa.AdditiveGaussianNoise(scale=(0.03 * 255, 0.05 * 255))
])
def searchImagesFolder(list, str):
for folder in folders: