用 OpenCV 进行年龄和性别检测
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2020-12-24 07:25
def getFaceBox(net, frame, conf_threshold=0.7):
frameOpencvDnn = frame.copy()
frameHeight = frameOpencvDnn.shape[0]
frameWidth = frameOpencvDnn.shape[1]
blob = cv.dnn.blobFromImage(frameOpencvDnn, 1.0, (300, 300), [104, 117, 123], True, False)
net.setInput(blob)
detections = net.forward()
bboxes = []
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)
bboxes.append([x1, y1, x2, y2])
cv.rectangle(frameOpencvDnn, (x1, y1), (x2, y2), (0, 255, 0), int(round(frameHeight/150)), 8)
return frameOpencvDnn, bboxes
genderProto = "gender_deploy.prototxt"
genderModel = "gender_net.caffemodel"
ageNet = cv.dnn.readNet(ageModel, ageProto)
genderList = ['Male', 'Female']
blob = cv.dnn.blobFromImage(face, 1, (227, 227), MODEL_MEAN_VALUES, swapRB=False)
genderNet.setInput(blob)
genderPreds = genderNet.forward()
gender = genderList[genderPreds[0].argmax()]
print("Gender Output : {}".format(genderPreds))
print("Gender : {}".format(gender))
ageProto = "age_deploy.prototxt"
ageModel = "age_net.caffemodel"
ageNet = cv.dnn.readNet(ageModel, ageProto)
ageList = ['(0 - 2)', '(4 - 6)', '(8 - 12)', '(15 - 20)', '(25 - 32)', '(38 - 43)', '(48 - 53)', '(60 - 100)']
ageNet.setInput(blob)
agePreds = ageNet.forward()
age = ageList[agePreds[0].argmax()]
print("Gender Output : {}".format(agePreds))
print("Gender : {}".format(age))
label = "{}, {}".format(gender, age)
cv.putText(frameFace, label, (bbox[0], bbox[1]-20), cv.FONT_HERSHEY_SIMPLEX, 0.8, (255, 0, 0), 3, cv.LINE_AA)
cv.imshow("Age Gender Demo", frameFace)
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