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Gender_Detection.py
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Gender_Detection.py
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import cv2
import math
import argparse
def highlightFace(net, frame, conf_threshold=0.7):
frameOpencvDnn=frame.copy()
frameHeight=frameOpencvDnn.shape[0]
frameWidth=frameOpencvDnn.shape[1]
blob=cv2.dnn.blobFromImage(frameOpencvDnn, 1.0, (300, 300), [104, 117, 123], True, False)
net.setInput(blob)
detections=net.forward()
faceBoxes=[]
for i in range(detections.shape[2]):
confidence=detections[0,0,i,2]
if confidence>conf_threshold:
x1=int(detections[0,0,i,3]*frameWidth)
y1=int(detections[0,0,i,4]*frameHeight)
x2=int(detections[0,0,i,5]*frameWidth)
y2=int(detections[0,0,i,6]*frameHeight)
faceBoxes.append([x1,y1,x2,y2])
cv2.rectangle(frameOpencvDnn, (x1,y1), (x2,y2), (0,255,0), int(round(frameHeight/150)), 8)
return frameOpencvDnn,faceBoxes
parser=argparse.ArgumentParser()
parser.add_argument('--image')
args=parser.parse_args()
faceProto="opencv_face_detector.pbtxt"
faceModel="opencv_face_detector_uint8.pb"
genderProto="gender_deploy.prototxt"
genderModel="gender_net.caffemodel"
MODEL_MEAN_VALUES=(78.4263377603, 87.7689143744, 114.895847746)
genderList=['Male','Female']
faceNet=cv2.dnn.readNet(faceModel,faceProto)
genderNet=cv2.dnn.readNet(genderModel,genderProto)
video=cv2.VideoCapture(args.image if args.image else 0)
padding=20
while cv2.waitKey(1)<0:
hasFrame,frame=video.read()
if not hasFrame:
cv2.waitKey()
break
resultImg,faceBoxes=highlightFace(faceNet,frame)
if not faceBoxes:
print("No face detected")
for faceBox in faceBoxes:
face=frame[max(0,faceBox[1]-padding):
min(faceBox[3]+padding,frame.shape[0]-1),max(0,faceBox[0]-padding)
:min(faceBox[2]+padding, frame.shape[1]-1)]
blob=cv2.dnn.blobFromImage(face, 1.0, (227,227), MODEL_MEAN_VALUES, swapRB=False)
genderNet.setInput(blob)
genderPreds=genderNet.forward()
gender=genderList[genderPreds[0].argmax()]
print(f'Gender: {gender}')
cv2.putText(resultImg, f'{gender}', (faceBox[0], faceBox[1]-10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (251,78,40), 2, cv2.LINE_AA)
cv2.imshow("Detecting Gender......", resultImg)
video.release()
cv2.destroyAllWindows()