from utils import *
import logging
import cv2
def detect_face(img_path, cc_path='../files/haarcascade_frontalface_default.xml'):
"""
Detect the face from the image, return colored face
"""
cc = cv2.CascadeClassifier(os.path.abspath(cc_path))
img_path = os.path.abspath(img_path)
img = cv2.imread(img_path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = cc.detectMultiScale(gray, 1.3, 5)
roi_color = None
if len(faces) == 0:
logging.exception(img_path + ': No face found')
else:
x,y,w,h = faces[0]
_h, _w = compute_size(h, w)
roi_color = img[y - _h:y + h + _h, x - _w:x + w + _w]
return roi_color
def generate_faces(src_path, dst_path):
"""
Generate faces from source directory and store cropped faces in destination directory
"""
for root, dirs, files in os.walk(src_path):
for name in dirs:
dir_name = os.path.join(root, name)
images = os.listdir(dir_name)
images = [image for image in images if image.endswith('jpg')]
_path = os.path.join(dst_path, name)
if not os.path.exists(_path):
os.makedirs(_path)
for image in images:
face = detect_face(os.path.join(dir_name, image))
if face is None: continue
cv2.imwrite(os.path.join(_path, image), face)
