import os
import cv2
import math
import matplotlib.pyplot as pl
import pandas as pd
from PIL import Image
import numpy as np
def face_detection(img):
faces = face_detector.detectMultiScale(img, 1.1, 4)
if (len(faces) <= 0):
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
return img, img_gray
else:
X, Y, W, H = faces[0]
img = img[int(Y):int(Y+H), int(X):int(X+W)]
return img, cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
def trignometry_for_distance(a, b):
return math.sqrt(((b[0] - a[0]) * (b[0] - a[0])) +
((b[1] - a[1]) * (b[1] - a[1])))
def Face_Alignement(img_path):
pl.imshow(cv2.imread(img_path)[:, :, ::-1])
pl.show()
img_raw = cv2.imread(img_path).copy()
img, gray_img = face_detection(cv2.imread(img_path))
eyes = eye_detector.detectMultiScale(gray_img)
if len(eyes) >= 2:
eye = eyes[:, 2]
container1 = []
for i in range(0, len(eye)):
container = (eye[i], i)
container1.append(container)
df = pd.DataFrame(container1, columns=[
"length", "idx"]).sort_values(by=['length'])
eyes = eyes[df.idx.values[0:2]]
eye_1 = eyes[0]
eye_2 = eyes[1]
if eye_1[0] > eye_2[0]:
left_eye = eye_2
right_eye = eye_1
else:
left_eye = eye_1
right_eye = eye_2
right_eye_center = (
int(right_eye[0] + (right_eye[2]/2)),
int(right_eye[1] + (right_eye[3]/2)))
right_eye_x = right_eye_center[0]
right_eye_y = right_eye_center[1]
cv2.circle(img, right_eye_center, 2, (255, 0, 0), 3)
left_eye_center = (
int(left_eye[0] + (left_eye[2] / 2)),
int(left_eye[1] + (left_eye[3] / 2)))
left_eye_x = left_eye_center[0]
left_eye_y = left_eye_center[1]
cv2.circle(img, left_eye_center, 2, (255, 0, 0), 3)
if left_eye_y > right_eye_y:
print("Rotate image to clock direction")
point_3rd = (right_eye_x, left_eye_y)
direction = -1
else:
print("Rotate to inverse clock direction")
point_3rd = (left_eye_x, right_eye_y)
direction = 1
cv2.circle(img, point_3rd, 2, (255, 0, 0), 2)
a = trignometry_for_distance(left_eye_center,
point_3rd)
b = trignometry_for_distance(right_eye_center,
point_3rd)
c = trignometry_for_distance(right_eye_center,
left_eye_center)
cos_a = (b*b + c*c - a*a)/(2*b*c)
angle = (np.arccos(cos_a) * 180) / math.pi
if direction == -1:
angle = 90 - angle
else:
angle = -(90-angle)
new_img = Image.fromarray(img_raw)
new_img = np.array(new_img.rotate(direction * angle))
return new_img
opencv_home = cv2.__file__
folders = opencv_home.split(os.path.sep)[0:-1]
path = folders[0]
for folder in folders[1:]:
path = path + "/" + folder
path_for_face = path+"/data/haarcascade_frontalface_default.xml"
path_for_eyes = path+"/data/haarcascade_eye.xml"
path_for_nose = path+"/data/haarcascade_mcs_nose.xml"
if os.path.isfile(path_for_face) != True:
raise ValueError(
"opencv is not installed pls install using pip install opencv ",
detector_path, " violated.")
face_detector = cv2.CascadeClassifier(path_for_face)
eye_detector = cv2.CascadeClassifier(path_for_eyes)
nose_detector = cv2.CascadeClassifier(path_for_nose)
test_set = ["pic.png"]
for i in test_set:
alignedFace = Face_Alignement(i)
pl.imshow(alignedFace[:, :, ::-1])
pl.show()
img, gray_img = face_detection(alignedFace)
pl.imshow(img[:, :, ::-1])
pl.show()