def generate_mask_from_skin(face: Face) -> None:
from itertools import product
mask = np.zeros((IMG_SIZE, IMG_SIZE), dtype=np.bool)
mark = np.zeros((IMG_SIZE, IMG_SIZE, 3), dtype=np.float)
for x, y in product(range(IMG_SIZE), range(IMG_SIZE)):
mark[x][y] = tools.rgb_skin_mark(*(face.rgb_img[x][y]))
probe = [
mark[x][y]
for x, y in product(range(2 * IMG_SIZE // 4, 3 * IMG_SIZE // 4, 8),
range(2 * IMG_SIZE // 4, 3 * IMG_SIZE // 4, 8))
]
probe.sort(key=(lambda x: x[0]**2 + x[1]**2 + x[2]**2))
# Mark of middle [probably] SKIN element
mid_y, mid_cr, mid_cy = probe[len(probe) // 2]
for x, y in product(range(IMG_SIZE), range(IMG_SIZE)):
y, cr, cy = mark[x][y]
l_bound = 0.918
u_bound = 1.092
mask[x][y] = (0.3 * mid_y <= y <= 4 * mid_y) and (
l_bound * mid_cr <= cr <=
u_bound * mid_cr) and (l_bound * mid_cy <= cy <= u_bound * mid_cy)
face.mask = mask
# Display the mask if you want
tools.show_image(tools.pic_with_applied_mask(face.rgb_img, mask))
def generate_mask(face: Face, points: list((float, float, float))) -> None:
mask = np.zeros((IMG_SIZE, IMG_SIZE), dtype=np.bool)
for (xs, ys, _) in points:
mask[int(xs), int(ys)] = True
starting_point = (IMG_SIZE // 2, IMG_SIZE // 2
) # TODO: maybe some specific landmark (like nose)
sys.setrecursionlimit(100000)
def _helper(px, py):
if min(px, py) < 0 or max(px, py) >= IMG_SIZE:
return
if mask[px, py]:
return
mask[px, py] = True
_helper(px - 1, py)
_helper(px + 1, py)
_helper(px, py - 1)
_helper(px, py + 1)
_helper(starting_point[0], starting_point[1])
face.mask = mask