mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
92 lines
2.7 KiB
92 lines
2.7 KiB
#!/usr/bin/env python |
|
|
|
''' |
|
face detection using haar cascades |
|
''' |
|
|
|
# Python 2/3 compatibility |
|
from __future__ import print_function |
|
|
|
import numpy as np |
|
import cv2 as cv |
|
|
|
def detect(img, cascade): |
|
rects = cascade.detectMultiScale(img, scaleFactor=1.275, minNeighbors=4, minSize=(30, 30), |
|
flags=cv.CASCADE_SCALE_IMAGE) |
|
if len(rects) == 0: |
|
return [] |
|
rects[:,2:] += rects[:,:2] |
|
return rects |
|
|
|
from tests_common import NewOpenCVTests, intersectionRate |
|
|
|
class facedetect_test(NewOpenCVTests): |
|
|
|
def test_facedetect(self): |
|
cascade_fn = self.repoPath + '/data/haarcascades/haarcascade_frontalface_alt.xml' |
|
nested_fn = self.repoPath + '/data/haarcascades/haarcascade_eye.xml' |
|
|
|
cascade = cv.CascadeClassifier(cascade_fn) |
|
nested = cv.CascadeClassifier(nested_fn) |
|
|
|
samples = ['samples/data/lena.jpg', 'cv/cascadeandhog/images/mona-lisa.png'] |
|
|
|
faces = [] |
|
eyes = [] |
|
|
|
testFaces = [ |
|
#lena |
|
[[218, 200, 389, 371], |
|
[ 244, 240, 294, 290], |
|
[ 309, 246, 352, 289]], |
|
|
|
#lisa |
|
[[167, 119, 307, 259], |
|
[188, 153, 229, 194], |
|
[236, 153, 277, 194]] |
|
] |
|
|
|
for sample in samples: |
|
|
|
img = self.get_sample( sample) |
|
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) |
|
gray = cv.GaussianBlur(gray, (5, 5), 0) |
|
|
|
rects = detect(gray, cascade) |
|
faces.append(rects) |
|
|
|
if not nested.empty(): |
|
for x1, y1, x2, y2 in rects: |
|
roi = gray[y1:y2, x1:x2] |
|
subrects = detect(roi.copy(), nested) |
|
|
|
for rect in subrects: |
|
rect[0] += x1 |
|
rect[2] += x1 |
|
rect[1] += y1 |
|
rect[3] += y1 |
|
|
|
eyes.append(subrects) |
|
|
|
faces_matches = 0 |
|
eyes_matches = 0 |
|
|
|
eps = 0.8 |
|
|
|
for i in range(len(faces)): |
|
for j in range(len(testFaces)): |
|
if intersectionRate(faces[i][0], testFaces[j][0]) > eps: |
|
faces_matches += 1 |
|
#check eyes |
|
if len(eyes[i]) == 2: |
|
if intersectionRate(eyes[i][0], testFaces[j][1]) > eps and intersectionRate(eyes[i][1] , testFaces[j][2]) > eps: |
|
eyes_matches += 1 |
|
elif intersectionRate(eyes[i][1], testFaces[j][1]) > eps and intersectionRate(eyes[i][0], testFaces[j][2]) > eps: |
|
eyes_matches += 1 |
|
|
|
self.assertEqual(faces_matches, 2) |
|
self.assertEqual(eyes_matches, 2) |
|
|
|
|
|
if __name__ == '__main__': |
|
NewOpenCVTests.bootstrap()
|
|
|