def main(in_img_path):
rgb_img = cv2.imread(in_img_path)
overlay_img = cv2.imread(OVERLAY_IMG_PATH, -1)
cascade = cv2.CascadeClassifier(CASCADE_PATH)
faces = cascade.detectMultiScale(cv2.cvtColor(rgb_img,
cv2.COLOR_BGR2GRAY),
scaleFactor=1.1,
minNeighbors=1,
minSize=(1, 1))
if len(faces) <= 0:
check_img(rgb_img, 'total', True, OUT_IMG_PATH)
return
for (x, y, w, h) in faces:
face_img = rgb_img[y:y + h, x:x + w]
if not is_skin(face_img):
continue
# color = hsv_to_bgr(get_hair_color_hsv(face_img))
name, hsv = detect_aikatsu_charactors['anime_based']['bgr_diff'](
get_hair_color_hsv(face_img))
color = hsv_to_bgr(hsv)
cv2.rectangle(rgb_img, (x, y), (x + w, y + h), color, thickness=7)
check_img(rgb_img, 'total', True, OUT_IMG_PATH)
def main(in_img_path):
rgb_img = cv2.imread(in_img_path)
overlay_img = cv2.imread(OVERLAY_IMG_PATH, -1)
cascade = cv2.CascadeClassifier(CASCADE_PATH)
faces = cascade.detectMultiScale(cv2.cvtColor(rgb_img, cv2.COLOR_BGR2GRAY),
scaleFactor=1.1, minNeighbors=1, minSize=(1, 1))
if len(faces) <= 0:
check_img(rgb_img, 'total', True, OUT_IMG_PATH)
return
for (x, y, w, h) in faces:
face_img = rgb_img[y:y + h, x:x + w]
if not is_skin(face_img):
continue
# color = hsv_to_bgr(get_hair_color_hsv(face_img))
name, hsv = detect_aikatsu_charactors['anime_based']['bgr_diff'](get_hair_color_hsv(face_img))
color = hsv_to_bgr(hsv)
cv2.rectangle(rgb_img, (x, y), (x + w, y + h), color, thickness=7)
check_img(rgb_img, 'total', True, OUT_IMG_PATH)
import cv2
from functions import get_hair_color_hsv, hsv_to_bgr
# カスケード分類器の特徴量を取得する
cascade_path = "../cascade/lbpcascade_animeface.xml"
cascade = cv2.CascadeClassifier(cascade_path)
overlay_img_path = "../test_imgs/face_up3.jpg"
in_img_path = "../test_imgs/hirari-hitori-kirari/face_detecting5.png"
out_img_path = "../test_imgs/hirari-hitori-kirari/face_detecting_out.png"
img = cv2.imread(in_img_path)
overlay_img = cv2.imread(overlay_img_path)
color = (0, 187, 254)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=1, minSize=(1, 1))
if len(faces) > 0:
# 検出した顔を囲む矩形の作成
for (x, y, w, h) in faces:
face_img = img[y:y + h, x:x + w]
color = hsv_to_bgr(get_hair_color_hsv(face_img))
cv2.rectangle(img, (x, y), (x + w, y + h), color, thickness=7)
# cv2.rectangle(img, (x, y), (x + w, y + h), color, thickness=7)
# resized_overlay_img = cv2.resize(overlay_img, tuple((w, h)))
# img[y:y + h, x:x + w] = resized_overlay_img[:, :]
cv2.imwrite(out_img_path, img)
