def random_neg_with_rotate(img, label):
if lucky(0.5):
##50% of samples set to negative samples
label = label - 1
# rotate by 180 debgress
img_rotate = np.rot90(img)
img = np.rot90(img_rotate)
return img, np.array(label).astype(np.int32)
def transform(self, im, cval=255, **kw):
"""According to the parameters initialized by the class, deform the incoming image"""
severity = self.severity
prob = self.prob
cval = self.convert_color(im, cval)
if lucky(prob):
# affine transform
im = rgeometry(im, severity=severity, cval=cval)
if lucky(prob):
im = rdistort(im, severity=severity, cval=cval)
if lucky(prob):
im = warp_perspective(im, severity=severity, cval=cval)
if lucky(prob):
im = resize(im,
fx=kw.get('fx'),
fy=kw.get('fy'),
severity=severity)
if lucky(prob):
im = rotate_about_center(im, severity=severity, cval=cval)
if lucky(prob):
# the overall distortion of the image.
im = whole_rdistort(im, severity=severity)
if lucky(prob) and self.enable_crop:
# random crop
im = randcrop(im, severity=severity)
return im
def add_noise(self, im):
"""randomly add noise to image"""
severity = self.severity
prob = self.prob
if lucky(prob):
im = noise_gamma(im, severity=severity)
if lucky(prob):
im = noise_blur(im, severity=severity)
if lucky(prob):
im = noise_gaussian(im, severity=severity)
if lucky(prob):
im = noise_salt_pepper(im, severity=severity)
if lucky(prob):
im = shift_color(im, severity=severity)
if lucky(prob):
im = gaussian_blur(im, severity=severity)
if lucky(prob):
im = noise_speckle(im, severity=severity)
if lucky(prob):
im = enhance_sharpness(im, severity=severity)
if lucky(prob):
im = enhance_contrast(im, severity=severity)
if lucky(prob):
im = enhance_brightness(im, severity=severity)
if lucky(prob):
im = enhance_color(im, severity=severity)
if lucky(prob):
im = random_contrast(im)
return im