def find_color(img, lower, upper):
color_mask = cv2.inRange(img, lower, upper)
contours, _ = cv2.findContours(color_mask, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
found = False
for cnt in contours:
if len(cnt) > 5:
found = True
ellipse = cv2.fitEllipse(cnt)
x = ellipse[0][0] # center x
y = ellipse[0][1] # center y
angle = ellipse[2] # angle
a_min = ellipse[1][0] # asse minore
a_max = ellipse[1][1] # asse maggiore
if angle == 0:
h = a_max
w = a_min
else:
h = a_min
w = a_max
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(
h, w, x, y)
if not found:
return False
return [ymin, ymax, xmin, xmax, x, y, a_min, a_max, angle, contours]
def infer_nip(aur_list):
"""
Infer nipples.
:param aur_list: <BodyPart[]> aur list)
:return: <BodyPart[]> nip list
"""
nip_list = []
for aur in aur_list:
# Nip rules:
# - circle (w == h)
# - min dim: 5
# - bigger if aur is bigger
nip_dim = int(5 + aur.w * random.uniform(0.03, 0.09))
# center:
x = aur.x
y = aur.y
# Calculate Bounding Box:
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(
nip_dim, nip_dim, x, y)
BodyPart.add_body_part_to_list("nip",
BoundingBox(xmin, ymin, xmax, ymax),
Center(x, y),
Dimension(nip_dim, nip_dim), nip_list)
return nip_list
def infer_hair(vag_list, enable):
"""
Infer vaginal hair.
:param vag_list: <BodyPart[]> vag list
:param enable: <Boolean> Enable or disable hair generation
:return: <BodyPart[]> hair list
"""
hair_list = []
if enable:
for vag in vag_list:
# Hair rules:
hair_w = vag.w * random.uniform(0.4, 1.5)
hair_h = vag.h * random.uniform(0.4, 1.5)
# center:
x = vag.x
y = vag.y - (hair_h / 2) - (vag.h / 2)
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(
hair_h, hair_w, x, y)
BodyPart.add_body_part_to_list("hair",
BoundingBox(xmin, ymin, xmax, ymax),
Center(x, y),
Dimension(hair_w, hair_h),
hair_list)
return hair_list
def resolve_problem_6():
# Find width aur is full:
new_x, new_y = find_l2_width_is_full(tits_list, aur_list)
new_w = tits_list[0].w / 2
# Calculate Bounding Box:
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(new_w, new_w, new_x, new_y)
BodyPart.add_body_part_to_list("tit", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y),
Dimension(tits_list[0].w, tits_list[0].w), tits_list)
def resolve_problem_7():
# Add the first aur:
new_w = tits_list[0].w * random.uniform(0.03, 0.1) # TOTEST
new_x = tits_list[0].x
new_y = tits_list[0].y
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(new_w, new_w, new_x, new_y)
BodyPart.add_body_part_to_list("aur", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y),
Dimension(new_w, new_w), aur_list)
# Add the second aur:
new_w = tits_list[1].w * random.uniform(0.03, 0.1) # TOTEST
new_x = tits_list[1].x
new_y = tits_list[1].y
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(new_w, new_w, new_x, new_y)
BodyPart.add_body_part_to_list("aur", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y),
Dimension(new_w, new_w), aur_list)
def resolve_problem_3():
random_tit_factor = random.randint(2, 5) # TOTEST
# Add the first tit:
new_w = aur_list[0].w * random_tit_factor # TOTEST
new_x = aur_list[0].x
new_y = aur_list[0].y
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(new_w, new_w, new_x, new_y)
BodyPart.add_body_part_to_list("tit", BoundingBox(xmin, ymin, xmax, ymax), Center(new_x, new_y),
Dimension(new_w, new_w), tits_list)
# Add the second tit:
new_w = aur_list[1].w * random_tit_factor # TOTEST
new_x = aur_list[1].x
new_y = aur_list[1].y
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(new_w, new_w, new_x, new_y)
BodyPart.add_body_part_to_list("tit", BoundingBox(xmax, xmin, ymax, ymin), Center(new_x, new_y),
Dimension(new_w, new_w), tits_list)
def find_body_part(image, part_name):
"""
Find body part.
:param image: <RGB> image
:param part_name: <string> part_name
:return: <BodyPart[]>list
"""
bodypart_list = [] # empty BodyPart list
color_mask = get_correct_filter_color(image, part_name)
# find contours:
contours, _ = cv2.findContours(color_mask, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
# for every contour:
for cnt in contours:
if len(cnt) > 5: # at least 5 points to fit ellipse
# (x, y), (MA, ma), angle = cv2.fitEllipse(cnt)
ellipse = cv2.fitEllipse(cnt)
# Fit Result:
x = ellipse[0][0] # center x
y = ellipse[0][1] # center y
angle = ellipse[2] # angle
a_min = ellipse[1][0] # asse minore
a_max = ellipse[1][1] # asse maggiore
h, w = detect_direction(a_max, a_min, angle)
h, w = normalize_belly_vag(h, part_name, w)
xmax, xmin, ymax, ymin = BoundingBox.calculate_bounding_box(
h, w, x, y)
BodyPart.add_body_part_to_list(part_name,
BoundingBox(xmin, ymin, xmax, ymax),
Center(x, y), Dimension(w, h),
bodypart_list)
return bodypart_list