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import math
from typing import Union, Tuple
from numpy import ndarray
import numpy as np
def cal_start_end_point(big: float, small: float, center: float = None):
if center is None:
center = big / 2
if center < small / 2:
center = small / 2
if center > (big - small / 2):
center = big - small / 2
start = center - small / 2
end = center + small / 2
return (start, end)
def cal_small_bbox_coord_of_big_bbox(
bigbbox_width,
bigbbox_height,
smallbbox_width,
smallbbox_height,
center_width: float = None,
center_height: float = None,
need_round2even=False,
):
"""只有宽高信息，按中心crop计算小矩形在大矩形的剪辑坐标
Args:
bigbbox_width (float): _description_
bigbbox_height (float): _description_
smallbbox_width (float): _description_
smallbbox_height (float): _description_
Returns:
(float, float, float, float): (x1, y1, x2, y2) 在大矩形中的剪辑位置
"""
x1, x2 = cal_start_end_point(bigbbox_width, smallbbox_width, center=center_width)
y1, y2 = cal_start_end_point(bigbbox_height, smallbbox_height, center=center_height)
# x1 = (bigbbox_width - smallbbox_width) / 2
# y1 = (bigbbox_height - smallbbox_height) / 2
# x2 = (bigbbox_width + smallbbox_width) / 2
# y2 = (bigbbox_height + smallbbox_height) / 2
if need_round2even:
x1, y1, x2, y2 = round_up_coord_to_even(x1, y1, x2, y2)
return (x1, y1, x2, y2)
def round_up_to_even(num):
return math.floor(num / 2.0) * 2
def round_up_coord_to_even(x1, y1, x2, y2):
x2 = x1 + round_up_to_even(x2 - x1)
y2 = y1 + round_up_to_even(y2 - y1)
return (x1, y1, x2, y2)
def cal_crop_coord(
width,
height,
target_width_height_ratio,
restricted_bbox=None,
need_round2even=False,
):
"""
(TODO): 当前只考虑crop，不考虑补全；
(TODO): 当前只考虑视频尺寸比目标尺寸大
Args:
width (float): 原视频的宽
height (float): 原视频的高
target_width (float): 目标视频的宽
target_height (float): 目标视频的高
restricted_bbox ((float, float, float, float), optional): (x1, y1, x2, y2). Defaults to None.
Returns:
(float, float, float, float): (x1, y1, x2, y2) 在原视频中的剪辑位置
"""
if restricted_bbox is None:
target_width, target_height = cal_target_width_height_by_ratio(
width=width,
height=height,
target_width_height_ratio=target_width_height_ratio,
)
crop_bbox = cal_small_bbox_coord_of_big_bbox(
width, height, target_width, target_height
)
else:
r_width = restricted_bbox[2] - restricted_bbox[0]
r_height = restricted_bbox[3] - restricted_bbox[1]
target_width, target_height = cal_target_width_height_by_ratio(
width=r_width,
height=r_height,
target_width_height_ratio=target_width_height_ratio,
)
crop_bbox = cal_small_bbox_coord_of_big_bbox(
r_width, r_height, target_width, target_height
)
crop_bbox = (
crop_bbox[0] + restricted_bbox[0],
crop_bbox[1] + restricted_bbox[1],
crop_bbox[2] + restricted_bbox[0],
crop_bbox[3] + restricted_bbox[1],
)
if need_round2even:
crop_bbox = round_up_coord_to_even(*crop_bbox)
return crop_bbox
def cal_target_width_height_by_ratio(
width, height, target_width_height_ratio, need_round2even=False
):
"""针对原视频的宽、高和目标视频宽高比，计算合适的宽、高
Args:
width (float): 原视频的宽
height (float): 原视频的高
target_width_height_ratio (float): 目标视频宽高比
Returns:
target_width (float)): 目标宽
target_height (float): 目标高
"""
width_height_ratio = width / height
if width_height_ratio >= target_width_height_ratio:
target_width = height * target_width_height_ratio
target_height = height
else:
target_width = width
target_height = width / target_width_height_ratio
if need_round2even:
target_height = round_up_to_even(target_height)
target_width = round_up_to_even(target_width)
return target_width, target_height
def cal_target_width_height(
target_width=None,
target_height=None,
target_width_height_ratio=None,
need_even=True,
):
if target_width and not target_height and target_width_height_ratio:
target_height = int(target_width / target_width_height_ratio)
if need_even:
target_height = round_up_to_even(target_height)
if target_height and not target_width and target_width_height_ratio:
target_width = int(target_height * target_width_height_ratio)
if need_even:
target_width = round_up_to_even(target_width)
if target_height and target_width:
target_width_height_ratio = target_width / target_height
return target_width, target_height, target_width_height_ratio
def find_outlier(grid: ndarray) -> ndarray:
"""find outlier coordinary out of grid
Args:
grid (ndarray): 2xHxW
Returns:
mask: ndarray, HxW, 1 for coordinary in grid, 0 for outlier
"""
c, h, w = grid.shape
mask = np.zeros((h, w))
for i, j in zip(range(h), range(w)):
x = int(grid[0, i, j])
y = int(grid[1, i, j])
if x < h and y < w:
mask[x, y] = 1
return mask
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