def pose_rotation(meta):
deg = random.uniform(-15.0, 15.0)
img = meta.img
center = (img.shape[1] * 0.5, img.shape[0] * 0.5) # x, y
rot_m = cv2.getRotationMatrix2D((int(center[0]), int(center[1])), deg, 1)
ret = cv2.warpAffine(img, rot_m, img.shape[1::-1], flags=cv2.INTER_AREA, borderMode=cv2.BORDER_CONSTANT)
if img.ndim == 3 and ret.ndim == 2:
ret = ret[:, :, np.newaxis]
neww, newh = RotationAndCropValid.largest_rotated_rect(ret.shape[1], ret.shape[0], deg)
neww = min(neww, ret.shape[1])
newh = min(newh, ret.shape[0])
newx = int(center[0] - neww * 0.5)
newy = int(center[1] - newh * 0.5)
# print(ret.shape, deg, newx, newy, neww, newh)
img = ret[newy:newy + newh, newx:newx + neww]
# adjust meta data
adjust_joint_list = []
for point in meta.joint_list:
if point[0] < -100 or point[1] < -100:
adjust_joint_list.append((-1000, -1000))
continue
# if point[0] <= 0 or point[1] <= 0:
# adjust_joint_list.append((-1, -1))
# continue
x, y = _rotate_coord((meta.width, meta.height), (newx, newy), point, deg)
adjust_joint_list.append((x, y))
meta.joint_list = adjust_joint_list
meta.width, meta.height = neww, newh
meta.img = img
return meta
def pose_rotation(meta):
deg = random.uniform(-15.0, 15.0)
img = meta.img
center = (img.shape[1] * 0.5, img.shape[0] * 0.5) # x, y
rot_m = cv2.getRotationMatrix2D((int(center[0]), int(center[1])), deg, 1)
ret = cv2.warpAffine(img, rot_m, img.shape[1::-1], flags=cv2.INTER_AREA, borderMode=cv2.BORDER_CONSTANT)
if img.ndim == 3 and ret.ndim == 2:
ret = ret[:, :, np.newaxis]
neww, newh = RotationAndCropValid.largest_rotated_rect(ret.shape[1], ret.shape[0], deg)
neww = min(neww, ret.shape[1])
newh = min(newh, ret.shape[0])
newx = int(center[0] - neww * 0.5)
newy = int(center[1] - newh * 0.5)
# print(ret.shape, deg, newx, newy, neww, newh)
img = ret[newy:newy + newh, newx:newx + neww]
# adjust meta data
adjust_joint_list = []
for joint in meta.joint_list:
adjust_joint = []
for point in joint:
if point[0] < -100 or point[1] < -100:
adjust_joint.append((-1000, -1000))
continue
# if point[0] <= 0 or point[1] <= 0:
# adjust_joint.append((-1, -1))
# continue
x, y = _rotate_coord((meta.width, meta.height), (newx, newy), point, deg)
adjust_joint.append((x, y))
adjust_joint_list.append(adjust_joint)
meta.joint_list = adjust_joint_list
meta.width, meta.height = neww, newh
meta.img = img
return meta
def pose_rotation(meta):
if meta.hyperparams is None:
max_rotate_degree = 40 #random.uniform(-15.0, 15.0)
else:
max_rotate_degree = meta.hyperparams['max_rotate_degree']
deg = random.uniform(-40.0, 40.0)
img = meta.img
center = (img.shape[1] * 0.5, img.shape[0] * 0.5) # x, y
rot_m = cv2.getRotationMatrix2D(center, deg, 1)
if not isinstance(meta, pose_dataset.MPIMetadata):
ret = cv2.warpAffine(img,
rot_m,
img.shape[1::-1],
flags=cv2.INTER_CUBIC,
borderMode=cv2.BORDER_CONSTANT,
borderValue=(128, 128, 128))
if img.ndim == 3 and ret.ndim == 2:
ret = ret[:, :, np.newaxis]
neww, newh = RotationAndCropValid.largest_rotated_rect(
ret.shape[1], ret.shape[0], deg)
neww = min(neww, ret.shape[1])
newh = min(newh, ret.shape[0])
newx = int(center[0] - neww * 0.5)
newy = int(center[1] - newh * 0.5)
img = ret[newy:newy + newh, newx:newx + neww]
else:
# rotation calculates the cos and sin, taking absolutes of those.
abs_cos = abs(rot_m[0, 0])
abs_sin = abs(rot_m[0, 1])
# find the new width and height bounds
bound_w = int(img.shape[0] * abs_sin + img.shape[1] * abs_cos)
bound_h = int(img.shape[0] * abs_cos + img.shape[1] * abs_sin)
# subtract old image center (bringing image back to orin) and adding
# the new image center coordinates
rot_m[0, 2] += bound_w / 2 - center[0]
rot_m[1, 2] += bound_h / 2 - center[1]
ret = cv2.warpAffine(img,
rot_m, (bound_w, bound_h),
flags=cv2.INTER_CUBIC,
borderMode=cv2.BORDER_CONSTANT,
borderValue=(128, 128, 128))
if img.ndim == 3 and ret.ndim == 2:
ret = ret[:, :, np.newaxis]
img = ret
neww, newh = ret.shape[1], ret.shape[0]
newx = int(center[0] - neww * 0.5)
newy = int(center[1] - newh * 0.5)
#adjust mask
if isinstance(meta, pose_dataset.MPIMetadata):
msk = cv2.warpAffine(meta.mask,
rot_m, (bound_w, bound_h),
flags=cv2.INTER_AREA,
borderMode=cv2.BORDER_CONSTANT,
borderValue=255) #borderMode=cv2.BORDER_CONSTANT)
meta.mask = msk
# adjust meta data
adjust_joint_list = []
for joint in meta.joint_list:
adjust_joint = []
for point in joint:
if np.abs(point[0]) == np.inf or np.abs(point[1]) == np.inf:
x = np.inf
y = np.inf
else:
x, y = _rotate_coord((meta.width, meta.height), (newx, newy),
point, deg)
adjust_joint.append((x, y))
adjust_joint_list.append(adjust_joint)
adjust_objPos = []
future_randpers = meta.randpers
for c, pos in enumerate(meta.objpos):
x, y = _rotate_coord((meta.width, meta.height), (newx, newy), pos, deg)
if not (x > img.shape[1] or y > img.shape[0] or x < 0 or y < 0):
adjust_objPos.append([x, y])
elif c <= meta.randpers:
future_randpers -= 1
logger.warning('lost person during rotate')
meta.randpers = future_randpers
meta.objpos = adjust_objPos
meta.joint_list = adjust_joint_list
meta.width, meta.height = neww, newh
meta.img = img
return meta
def pose_rotation(image, annos, mask):
img_shape = np.shape(image)
height = img_shape[0]
width = img_shape[1]
deg = random.uniform(-15.0, 15.0)
img = image
center = (img.shape[1] * 0.5, img.shape[0] * 0.5) # x, y
rot_m = cv2.getRotationMatrix2D((int(center[0]), int(center[1])), deg, 1)
ret = cv2.warpAffine(img,
rot_m,
img.shape[1::-1],
flags=cv2.INTER_AREA,
borderMode=cv2.BORDER_CONSTANT)
if img.ndim == 3 and ret.ndim == 2:
ret = ret[:, :, np.newaxis]
neww, newh = RotationAndCropValid.largest_rotated_rect(
ret.shape[1], ret.shape[0], deg)
neww = min(neww, ret.shape[1])
newh = min(newh, ret.shape[0])
newx = int(center[0] - neww * 0.5)
newy = int(center[1] - newh * 0.5)
# print(ret.shape, deg, newx, newy, neww, newh)
img = ret[newy:newy + newh, newx:newx + neww]
# adjust meta data
adjust_joint_list = []
for joint in annos:
adjust_joint = []
for point in joint:
if point[0] < -100 or point[1] < -100:
adjust_joint.append((-1000, -1000))
continue
# if point[0] <= 0 or point[1] <= 0:
# adjust_joint.append((-1, -1))
# continue
x, y = _rotate_coord((width, height), (newx, newy), point, deg)
# if x > neww or y > newh:
# adjust_joint.append((-1000, -1000))
# continue
if x > neww - 1 or y > newh - 1:
adjust_joint.append((-1000, -1000))
continue
if x < 0 or y < 0:
adjust_joint.append((-1000, -1000))
continue
adjust_joint.append((x, y))
adjust_joint_list.append(adjust_joint)
joint_list = adjust_joint_list
msk = mask
center = (msk.shape[1] * 0.5, msk.shape[0] * 0.5) # x, y
rot_m = cv2.getRotationMatrix2D((int(center[0]), int(center[1])), deg, 1)
ret = cv2.warpAffine(msk,
rot_m,
msk.shape[1::-1],
flags=cv2.INTER_AREA,
borderMode=cv2.BORDER_CONSTANT)
if msk.ndim == 3 and msk.ndim == 2:
ret = ret[:, :, np.newaxis]
neww, newh = RotationAndCropValid.largest_rotated_rect(
ret.shape[1], ret.shape[0], deg)
neww = min(neww, ret.shape[1])
newh = min(newh, ret.shape[0])
newx = int(center[0] - neww * 0.5)
newy = int(center[1] - newh * 0.5)
# print(ret.shape, deg, newx, newy, neww, newh)
msk = ret[newy:newy + newh, newx:newx + neww]
return img, joint_list, msk
