f4334277
 Hu Chunming
提交3rdparty
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#!/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()
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