wandaxiao 2020-05-01
我使用的语言为python,识别率不高,只是简单实现了人脸识别的步骤,参考<OpenCV3 计算机视觉>,部分的opencv库接口有所改变.
import cv2
import os
def generate(dirname):
face_cascade = cv2.CascadeClassifier(‘/home/yuanqi/opencv-3.4.6/yuanqi opencv/cascades/haarcascade_frontalface_default.xml‘)
eye_cascade = cv2.CascadeClassifier(‘/home/yuanqi/opencv-3.4.6/yuanqi opencv/cascades/haarcascade_eye_tree_eyeglasses.xml‘)
if(not os.path.isdir(dirname)):
os.makedirs(dirname)
camera = cv2.VideoCapture(0)
count = 0
while (True):
ret, frame = camera.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
img = cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
f = cv2.resize(gray[y:y+h, x:x+w], (200, 200))
cv2.imwrite(dirname+‘/%s.pgm‘ % str(count), f)
print(count)
count += 1
cv2.imshow("camera", frame)
if cv2.waitKey(100) & 0xff == ord("q"):
break
elif count > 20:
break
camera.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
generate("/home/yuanqi/opencvname/jm")
import sys
import os.path
if __name__ == "__main__":
BASE_PATH="/home/yuanqi/opencvname"
SEPARATOR=";"
fh = open("/home/yuanqi/opencvname/jm/at.text",‘w‘)
label = 0
for dirname, dirnames, filenames in os.walk(BASE_PATH):
for subdirname in dirnames:
subject_path = os.path.join(dirname, subdirname)
for filename in os.listdir(subject_path):
abs_path = "%s/%s" % (subject_path, filename)
print ("%s%s%d" % (abs_path, SEPARATOR, label))
fh.write(abs_path)
fh.write(SEPARATOR)
fh.write(str(label))
fh.write("\n")
label = label + 1
fh.close()
import cv2,os,sys
import numpy as np
def read_images(path, sz = None):
c = 0
X, y = [], []
for dirname, dirnames, filenames in os.walk(path):
for subdirname in dirnames:
subject_path = os.path.join(dirname, subdirname)
for filename in os.listdir(subject_path):
try:
if not filename.endswith(‘.pgm‘):
continue
filepath = os.path.join(subject_path, filename)
im = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
if sz is not None:
im = cv2.resize(im,(200,200))
X.append(np.asarray(im, dtype=np.uint8))
y.append(c)
except:
print("Unexpected error:",sys.exc_info()[0])
c = c + 1
return [X, y]
def face_rec(img_path):
names = [‘rabbit‘]
[X,y] = read_images(img_path)
y = np.asarray(y, dtype=np.int32)
model = cv2.face.EigenFaceRecognizer_create()
model.train(np.asarray(X), np.asarray(y))
camera = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier(
r‘/home/yuanqi/opencv-3.4.6/yuanqi opencv/cascades/haarcascade_frontalface_default.xml‘)
while (True):
read, img = camera.read()
faces = face_cascade.detectMultiScale(img, 1.3, 5)
for (x, y, w, h) in faces:
img = cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
roi = gray[x: x+w, y: y+h]
try:
roi = cv2.resize(roi, (200, 200), interpolation=cv2.INTER_LINEAR)
params = model.predict(roi)
print("Label: %s, Confidence: %.2f" % (params[0], params[1]))
cv2.putText(img, names[params[0]], (x, y - 20), cv2.FONT_HERSHEY_SIMPLEX, 1, 255, 2)
except:
continue
cv2.imshow("camera", img)
if cv2.waitKey(1000 // 12) & 0xff == ord(‘q‘):
break
cv2.destroyAllWindows()
if __name__ == "__main__":
face_rec(r‘/home/yuanqi/opencvname‘)