def __call__(self, img, boxes, labels):
img = img.astype('float32')
if random.randint(2):
delta = random.uniform(-self.brightness_delta, self.brightness_delta)
img += delta
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
return img, boxes, labels
def _augm(img, brightness_delta, contrast_mode, contrast_alpha,
saturation_alpha, hue_delta, noise_sigma, color_scales):
def _clamp_image(_img):
_img[_img < 0.0] = 0.0
_img[_img > 255.0] = 255.0
return _img
img = img.astype(np.float32)
# random brightness
if brightness_delta is not None:
img += brightness_delta
img = _clamp_image(img)
# random contrast
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
if contrast_mode == 1:
if contrast_alpha is not None:
img *= contrast_alpha
img = _clamp_image(img)
# convert color from BGR to HSV
if saturation_alpha is not None or hue_delta is not None:
img = mmcv.bgr2hsv(img / 255.)
# random saturation
if saturation_alpha is not None:
img[:, :, 1] *= saturation_alpha
img[:, :, 1][img[:, :, 1] > 1.0] = 1.0
img[:, :, 1][img[:, :, 1] < 0.0] = 0.0
# random hue
if hue_delta is not None:
img[:, :, 0] += hue_delta
img[:, :, 0][img[:, :, 0] > 360.0] -= 360.0
img[:, :, 0][img[:, :, 0] < 0.0] += 360.0
# convert color from HSV to BGR
if saturation_alpha is not None or hue_delta is not None:
img = mmcv.hsv2bgr(img) * 255.
# random contrast
if contrast_mode == 0:
if contrast_alpha is not None:
img *= contrast_alpha
img = _clamp_image(img)
if color_scales is not None:
img *= color_scales.reshape((1, 1, -1))
# gaussian noise
if noise_sigma is not None:
img += np.random.normal(loc=0.0, scale=noise_sigma, size=img.shape)
# clamp
img = _clamp_image(img)
return img.astype(np.uint8)
def __call__(self, results):
img = results['img']
# random brightness
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
# img += delta
img = np.add(img, delta)
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
# img *= alpha
img = np.multiply(img, alpha)
# convert color from BGR to HSV
img = img.astype(np.uint8)
img = mmcv.bgr2hsv(img)
# random saturation
if random.randint(2):
# img[..., 1] *= random.uniform(self.saturation_lower,
# self.saturation_upper)
img[..., 1] = np.multiply(
img[..., 1],
random.uniform(self.saturation_lower, self.saturation_upper))
# random hue
if random.randint(2):
# img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[...,
0] = np.add(img[..., 0],
random.uniform(-self.hue_delta, self.hue_delta))
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
# img *= alpha
img = np.multiply(img, alpha)
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
results['img'] = img
# cv_showimg(**results)
return results
def photo_metric_distortion(self, results, params=None):
"""Call function to perform photometric distortion on images.
Args:
results (dict): Result dict from loading pipeline.
params (dict, optional): Pre-defined parameters. Default to None.
Returns:
dict: Result dict with images distorted.
"""
if params is None:
params = self.get_params()
results['img_info']['color_jitter'] = params
if 'img_fields' in results:
assert results['img_fields'] == ['img'], \
'Only single img_fields is allowed'
img = results['img']
assert img.dtype == np.float32, \
'PhotoMetricDistortion needs the input image of dtype np.float32,'\
' please set "to_float32=True" in "LoadImageFromFile" pipeline'
# random brightness
if params['delta'] is not None:
img += params['delta']
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
if params['contrast_first']:
if params['alpha'] is not None:
img *= params['alpha']
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if params['saturation'] is not None:
img[..., 1] *= params['saturation']
# random hue
if params['hue'] is not None:
img[..., 0] += params['hue']
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if not params['contrast_first']:
if params['alpha'] is not None:
img *= params['alpha']
# randomly swap channels
if params['permutation'] is not None:
img = img[..., params['permutation']]
results['img'] = img
return results
def hue(self, img):
"""Hue distortion."""
if random.randint(2):
img = mmcv.bgr2hsv(img)
img[:, :,
0] = (img[:, :, 0].astype(int) +
random.randint(-self.hue_delta, self.hue_delta)) % 180
img = mmcv.hsv2bgr(img)
return img
def saturation(self, img):
"""Saturation distortion."""
if random.randint(2):
img = mmcv.bgr2hsv(img)
img[:, :, 1] = self.convert(
img[:, :, 1],
alpha=random.uniform(self.saturation_lower,
self.saturation_upper))
img = mmcv.hsv2bgr(img)
return img
def __call__(self, results):
img = results['img']
assert img.dtype == np.float32, \
'PhotoMetricDistortion needs the input image of dtype np.float32,' \
' please set "to_float32=True" in "LoadImageFromFile" pipeline'
# random brightness
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
img += delta
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
# random exposure
if random.randint(2):
img[..., 2] *= random.uniform(self.exposure_lower,
self.exposure_upper)
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
results['img'] = img
return results
def __call__(self, img, boxes, gt_masks, gt_segs, labels):
"""
apply transform when calling
:param img: numpy.ndarray,(h,w,c)
:param boxes: numpy.ndarray,(n,4), x1,y1,x2,y2
:param segments: list(list),(n)(x),x is variant
:param labels: numpy.ndarray,(n)
:return:
"""
# random brightness
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
img += delta
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
return img, boxes, gt_masks, gt_segs, labels
def __call__(self, img, boxes, labels):
print('photo metric distortion, extra_aug.py')
i += 1
# random brightness
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
img += delta
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
return img, boxes, labels
def __call__(self, results):
img = results['img']
# random brightness
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
img += delta
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
results['img'] = img
return results
def __call__(self, img, boxes, labels):
# random brightness 随机亮度
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
img += delta
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation 随机饱和度
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
# random hue 随机色度
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast 随机对比度
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# randomly swap channels 随机交换channel
if random.randint(2):
img = img[..., random.permutation(3)]
return img, boxes, labels
def __call__(self, results):
"""Call function.
Args:
results (dict): A dict containing the necessary information and
data for augmentation.
Returns:
dict: A dict containing the processed data and information.
"""
fg, alpha = results['fg'], results['alpha']
# convert to HSV space;
# convert to float32 image to keep precision during space conversion.
fg = mmcv.bgr2hsv(fg.astype(np.float32) / 255)
# Hue noise
hue_jitter = np.random.randint(self.hue_range[0], self.hue_range[1])
fg[:, :, 0] = np.remainder(fg[:, :, 0] + hue_jitter, 360)
# Saturation noise
sat_mean = fg[:, :, 1][alpha > 0].mean()
# jitter saturation within range (1.1 - sat_mean) * [-0.1, 0.1]
sat_jitter = (1.1 - sat_mean) * (np.random.rand() * 0.2 - 0.1)
sat = fg[:, :, 1]
sat = np.abs(sat + sat_jitter)
sat[sat > 1] = 2 - sat[sat > 1]
fg[:, :, 1] = sat
# Value noise
val_mean = fg[:, :, 2][alpha > 0].mean()
# jitter value within range (1.1 - val_mean) * [-0.1, 0.1]
val_jitter = (1.1 - val_mean) * (np.random.rand() * 0.2 - 0.1)
val = fg[:, :, 2]
val = np.abs(val + val_jitter)
val[val > 1] = 2 - val[val > 1]
fg[:, :, 2] = val
# convert back to BGR space
fg = mmcv.hsv2bgr(fg)
results['fg'] = fg * 255
return results
def __call__(self, results):
"""Call function to perform photometric distortion on images.
Args:
results (dict): Result dict from loading pipeline.
Returns:
dict: Result dict with images distorted.
"""
img = results['img']
# random brightness
img = self.brightness(img)
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
img = self.contrast(img)
hsv_mode = random.randint(4)
if hsv_mode:
# random saturation/hue distortion
img = mmcv.bgr2hsv(img)
if hsv_mode == 1 or hsv_mode == 3:
img = self.saturation(img)
if hsv_mode == 2 or hsv_mode == 3:
img = self.hue(img)
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
img = self.contrast(img)
# randomly swap channels
self.swap_channels(img)
results['img'] = img
return results
def __call__(self, results):
print('start')
import copy
img = copy.deepcopy(results['img'])
print(img.shape)
img[0,0,0]+=1
print('loaded')
# random brightness
if random.randint(2):
print('a')
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
print(delta)
print(img.shape)
print('success')
print(delta.shape)
img += delta
print('exit')
print('first')
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
print('exit1')
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
print(img.shape)
# convert color from BGR to HSV
print('bgr')
img = mmcv.bgr2hsv(img)
print('mid')
# random saturation
if random.randint(2):
img[..., 1] *= 2#random.uniform(self.saturation_lower,
#self.saturation_upper)
print('exit2')
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
print(img.shape)
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
print(img.shape)
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
results['img'] = img
print('end')
return results
def __call__(self, results):
"""Call function to perform photometric distortion on images.
Args:
results (dict): Result dict from loading pipeline.
Returns:
dict: Result dict with images distorted.
"""
if 'img_fields' in results:
assert results['img_fields'] == ['img'], \
'Only single img_fields is allowed'
img = results['img']
assert img.dtype == np.float32, \
'PhotoMetricDistortion needs the input image of dtype np.float32,'\
' please set "to_float32=True" in "LoadImageFromFile" pipeline'
# random brightness
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
img += delta
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
results['img'] = img
return results
def __call__(self, results, state=None):
if state is None:
delta_randint = random.randint(2)
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
mode = random.randint(2)
mode_randint = random.randint(2)
alpha = random.uniform(self.contrast_lower, self.contrast_upper)
sat_randint = random.randint(2)
sat_multiplier = random.uniform(self.saturation_lower,
self.saturation_upper)
hue_randint = random.randint(2)
hue_multiplier = random.uniform(-self.hue_delta, self.hue_delta)
contrast_randint = random.randint(2)
contrast_alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
perm_randint = random.randint(2)
perm = random.permutation(3)
state = dict(delta_randint=delta_randint,
delta=delta,
mode=mode,
mode_randint=mode_randint,
alpha=alpha,
sat_randint=sat_randint,
sat_multiplier=sat_multiplier,
hue_randint=hue_randint,
hue_multiplier=hue_multiplier,
contrast_randint=contrast_randint,
contrast_alpha=contrast_alpha,
perm_randint=perm_randint,
perm=perm)
else:
delta_randint = state['delta_randint']
delta = state['delta']
mode = state['mode']
mode_randint = state['mode_randint']
alpha = state['alpha']
sat_randint = state['sat_randint']
sat_multiplier = state['sat_multiplier']
hue_randint = state['hue_randint']
hue_multiplier = state['hue_multiplier']
contrast_randint = state['contrast_randint']
contrast_alpha = state['contrast_alpha']
perm_randint = state['perm_randint']
perm = state['perm']
img = results['img']
# random brightness
if delta_randint:
delta = delta
img += delta
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = mode
if mode == 1:
if mode_randint:
alpha = alpha
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if sat_randint:
img[..., 1] *= sat_multiplier
# random hue
if hue_randint:
img[..., 0] += hue_multiplier
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if contrast_randint:
alpha = contrast_alpha
img *= alpha
# randomly swap channels
if perm_randint:
img = img[..., perm]
results['img'] = img
return results, state
def __call__(self, img, boxes, labels, masks=None):
if self.color_choose == 0:
if random.uniform() < self.gray_p:
gray = mmcv.bgr2gray(img)
img = mmcv.gray2bgr(gray)
return img, boxes, labels, masks
# random brightness
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
img += delta
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = random.randint(2)
if mode == 1:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta, self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
# randomly swap channels
if random.randint(2):
img = img[..., random.permutation(3)]
else:
if self.color_choose == 1:
# random brightness
if random.randint(2):
delta = random.uniform(-self.brightness_delta,
self.brightness_delta)
img += delta
elif self.color_choose == 2:
# random contrast first
if random.randint(2):
alpha = random.uniform(self.contrast_lower,
self.contrast_upper)
img *= alpha
else:
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
if self.color_choose == 3:
# random saturation
if random.randint(2):
img[..., 1] *= random.uniform(self.saturation_lower,
self.saturation_upper)
if self.color_choose == 4:
# random hue
if random.randint(2):
img[..., 0] += random.uniform(-self.hue_delta,
self.hue_delta)
img[..., 0][img[..., 0] > 360] -= 360
img[..., 0][img[..., 0] < 0] += 360
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
return img, boxes, labels, masks
def random_photo_metric_distortion(self, img):
# https://github.com/open-mmlab/mmdetection/blob/a054aef422d650a644459bdc232248eefa8ae8b7/mmdet/datasets/extra_aug.py#L8
# brightness_delta=32
# contrast_range=(0.5, 1.5),
# saturation_range=(0.5, 1.5),
# hue_delta=18)
# brightness_delta = photo_metric_distortion['brightness_delta']
# contrast_lower, contrast_upper = photo_metric_distortion['contrast_range']
# saturation_lower, saturation_upper = photo_metric_distortion['saturation_range']
# hue_delta = self.photo_metric_distortion['hue_delta']
brightness_delta = 32
contrast_lower, contrast_upper = (0.5, 1.5)
saturation_lower, saturation_upper = (0.5, 1.5)
hue_delta = 18
# change datatype before do photo metric distortion
img = img.astype(np.float32)
# random brightness
if np.random.randint(2):
delta = np.random.uniform(-brightness_delta, brightness_delta)
img += delta
img = img.clip(min=0, max=255)
# mode == 0 --> do random contrast first
# mode == 1 --> do random contrast last
mode = np.random.randint(2)
if mode == 1:
if np.random.randint(2):
alpha = np.random.uniform(contrast_lower, contrast_upper)
img *= alpha
img = img.clip(min=0, max=255)
# convert color from BGR to HSV
img = mmcv.bgr2hsv(img)
# random saturation
if np.random.randint(2):
img[..., 1] *= np.random.uniform(saturation_lower,
saturation_upper)
img[..., 1] = img[..., 1].clip(min=0, max=1)
# random hue
if np.random.randint(2):
img[..., 0] += np.random.uniform(-hue_delta, hue_delta)
# img[..., 0][img[..., 0] > 360] -= 360
# img[..., 0][img[..., 0] < 0] += 360
img[..., 0] = img[..., 0].clip(min=0, max=360)
# convert color from HSV to BGR
img = mmcv.hsv2bgr(img)
# random contrast
if mode == 0:
if np.random.randint(2):
alpha = np.random.uniform(contrast_lower, contrast_upper)
img *= alpha
img = img.clip(min=0, max=255)
# randomly swap channels
# if np.random.randint(2):
# img = img[..., np.random.permutation(3)]
return img.astype(np.uint8)