def __rotate(self, arr, angle=0):
if angle == 0:
return arr
elif angle == 90:
arr = arr.transpose((0, 2, 1))
return arr
elif angle == 180:
arr = nd.flip(arr, axis=1)
return arr
elif angle == 270:
arr = arr.transpose((0, 2, 1))
arr = nd.flip(arr, axis=1)
return arr
def image_preprocess2(img, crop_sz, expandid, blockid, cornerid, flipid):
nd_img = nd.array(img)
if len(args.rgb_mean) > 0:
rgb_mean = [float(x) for x in args.rgb_mean.split(',')]
rgb_mean = np.array(rgb_mean, dtype=np.float32).reshape(1, 1, 3)
rgb_mean = nd.array(rgb_mean)
nd_img -= rgb_mean
nd_img *= 0.0078125
#expand = 32
#if crop_sz<300:
# expand = 16
img_sz = crop_sz + args.expand * (expandid + 1)
#img_sz = crop_sz+int(crop_sz/7)*(expandid+1)
nd_img = mx.image.resize_short(nd_img, img_sz)
if flipid == 1:
nd_img = nd.flip(nd_img, axis=1)
img = nd_img.asnumpy()
h = img.shape[0]
w = img.shape[1]
block_size = min(h, w)
blockh = 0
blockw = 0
if h > w:
if blockid == 1:
_half = int((h - w) / 2)
blockh = _half
elif blockid == 2:
blockh = h - w
else:
if blockid == 1:
_half = int((w - h) / 2)
blockw = _half
elif blockid == 2:
blockw = w - h
block = img[blockh:(blockh + block_size), blockw:(blockw + block_size), :]
if cornerid == 5:
img = cv2.resize(block, (crop_sz, crop_sz))
else:
if cornerid == 0:
cornerh = int((block_size - crop_sz) / 2)
cornerw = int((block_size - crop_sz) / 2)
elif cornerid == 1:
cornerh = 0
cornerw = 0
elif cornerid == 2:
cornerh = 0
cornerw = block_size - crop_sz
elif cornerid == 3:
cornerh = block_size - crop_sz
cornerw = 0
elif cornerid == 4:
cornerh = block_size - crop_sz
cornerw = block_size - crop_sz
img = block[cornerh:(cornerh + crop_sz),
cornerw:(cornerw + crop_sz), :]
img = np.swapaxes(img, 0, 2)
img = np.swapaxes(img, 1, 2) # change to CHW
#print(img.shape)
return img
def image_preprocess2(img, crop_sz, blockid, cornerid, flipid):
nd_img = nd.array(img)
expand = 32
#if crop_sz<300:
# expand = 16
img_sz = crop_sz + expand
nd_img = mx.image.resize_short(nd_img, img_sz)
if flipid == 1:
nd_img = nd.flip(nd_img, axis=1)
img = nd_img.asnumpy()
h = img.shape[0]
w = img.shape[1]
block_size = min(h, w)
blockh = 0
blockw = 0
if h > w:
if blockid == 1:
_half = int((h - w) / 2)
blockh = _half
elif blockid == 2:
blockh = h - w
else:
if blockid == 1:
_half = int((w - h) / 2)
blockw = _half
elif blockid == 2:
blockw = w - h
block = img[blockh:(blockh + block_size), blockw:(blockw + block_size), :]
if cornerid == 0:
cornerh = int((block_size - crop_sz) / 2)
cornerw = int((block_size - crop_sz) / 2)
elif cornerid == 1:
cornerh = 0
cornerw = 0
elif cornerid == 2:
cornerh = 0
cornerw = block_size - crop_sz
elif cornerid == 3:
cornerh = block_size - crop_sz
cornerw = 0
elif cornerid == 4:
cornerh = block_size - crop_sz
cornerw = block_size - crop_sz
img = block[cornerh:(cornerh + crop_sz), cornerw:(cornerw + crop_sz), :]
img = np.swapaxes(img, 0, 2)
img = np.swapaxes(img, 1, 2) # change to CHW
#print(img.shape)
return img
def image_preprocess2(img, crop_sz):
nd_img = nd.array(img)
img_sz = crop_sz + random.randint(8, 32)
if args.step == 0:
img_sz = crop_sz + 32
if img_sz > 0:
nd_img = mx.image.resize_short(nd_img, img_sz)
#nd_img = mx.image.random_size_crop(nd_img, (crop_sz, crop_sz), 0.08, (3.0/4, 4.0/3))[0]
if args.step == 0:
nd_img = mx.image.center_crop(nd_img, (crop_sz, crop_sz))[0]
else:
nd_img = mx.image.random_crop(nd_img, (int(
(img_sz + crop_sz) / 2), int((img_sz + crop_sz) / 2)))[0]
nd_img = mx.image.center_crop(nd_img, (crop_sz, crop_sz))[0]
if random.random() < 0.5:
nd_img = nd.flip(nd_img, axis=1)
img = nd_img.asnumpy()
img = np.swapaxes(img, 0, 2)
img = np.swapaxes(img, 1, 2) # change to CHW
#print(img.shape)
return img
def forward(self, inpt):
fwd = self._lstm_fwd(inpt)
bwd_inpt = nd.flip(inpt, 0)
bwd = self._lstm_bwd(bwd_inpt)
bwd = nd.flip(bwd, 0)
return nd.concat(fwd, bwd, dim=2)
def horizon_flip(image):
return nd.flip(image, axis=1)
def random_horizon_flip(image, p=0.5):
if random.random() <= p:
image = nd.flip(image, axis=1)
return image
