女生比较避讳别人问年龄,于是我偷偷写了一款年龄检测器!

912 阅读4分钟

导语

图片

一入Python深似海,不会还要继续坚持学!

哈喽!大家好,我是木子,今天又到了一周周末,到了看剧刷抖音的好时间,可怜的我还在公司加班赶稿子。

想着今天都周末了,给大家送一波福利!不清楚大家刷抖音的时候是不是经常看到这个画面,检测人脸识别的小程序,一打开程序,现场拍一张图片就可以识别你适合的发型、颜值打分、识别年龄.......等等~

周末公司上班的话比较放松除了工作也会聊点儿额外的话题,某某多大、毕业多久。大概是这些话题。

很多小姐姐问到年龄这个问题都比较“害羞”,咳咳咳.......

所以我想着你们不好意思说自己多大了,肯定是想作为技术员的我给你们做一款年龄检测机器!

好心的我给公司的一大批小姐姐偷偷做了年龄检测!

嘘嘘嘘!这话我只告诉你们不要往外说~

正文

原理简介:

(1)预先加载三个网络模型
(2)打开摄像头视频流/加载图像;

(3)对每一帧进行人脸检测;对检测到的人脸进行性别与年龄预测;解析预测结果;显示结果。

代码实现详解

加载模型:

MODEL_MEAN_VALUES = (78.4263377603, 87.7689143744, 114.895847746)
ageList = ['(0-2)', '(4-6)', '(8-12)', '(15-20)', '(25-32)', '(38-43)', '(48-53)', '(60-100)']
genderList = ['Male', 'Female']

# Load network
ageNet = cv.dnn.readNet(ageModel, ageProto)
genderNet = cv.dnn.readNet(genderModel, genderProto)
faceNet = cv.dnn.readNet(faceModel, faceProto)

人脸检测:

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)

性别与年龄预测:

for bbox in bboxes:
        # print(bbox)
        face = frame[max(0,bbox[1]-padding):min(bbox[3]+padding,frame.shape[0]-1),max(0,bbox[0]-padding):min(bbox[2]+padding, frame.shape[1]-1)]

        blob = cv.dnn.blobFromImage(face, 1.0, (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 : {}, conf = {:.3f}".format(gender, genderPreds[0].max()))

        ageNet.setInput(blob)
        agePreds = ageNet.forward()
        age = ageList[agePreds[0].argmax()]
        print("Age Output : {}".format(agePreds))
        print("Age : {}, conf = {:.3f}".format(age, agePreds[0].max()))

        label = "{},{}".format(gender, age)
        cv.putText(frameFace, label, (bbox[0], bbox[1]-10), cv.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 255), 2, cv.LINE_AA)
        cv.imshow("Age Gender Demo", frameFace)
    print("time : {:.3f} ms".format(time.time() - t))

效果图:

​​

​​

​附:

import cv2 as cv
import time


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


faceProto = "D:/projects/opencv_tutorial/data/models/face_detector/opencv_face_detector.pbtxt"
faceModel = "D:/projects/opencv_tutorial/data/models/face_detector/opencv_face_detector_uint8.pb"

ageProto = "D:/projects/opencv_tutorial/data/models/cnn_age_gender_models/age_deploy.prototxt"
ageModel = "D:/projects/opencv_tutorial/data/models/cnn_age_gender_models/age_net.caffemodel"

genderProto = "D:/projects/opencv_tutorial/data/models/cnn_age_gender_models/gender_deploy.prototxt"
genderModel = "D:/projects/opencv_tutorial/data/models/cnn_age_gender_models/gender_net.caffemodel"

MODEL_MEAN_VALUES = (78.4263377603, 87.7689143744, 114.895847746)
ageList = ['(0-2)', '(4-6)', '(8-12)', '(15-20)', '(25-32)', '(38-43)', '(48-53)', '(60-100)']
genderList = ['Male', 'Female']

# Load network
ageNet = cv.dnn.readNet(ageModel, ageProto)
genderNet = cv.dnn.readNet(genderModel, genderProto)
faceNet = cv.dnn.readNet(faceModel, faceProto)

# Open a video file or an image file or a camera stream
cap = cv.VideoCapture(0)
padding = 20
while cv.waitKey(1) < 0:
    # Read frame
    t = time.time()
    hasFrame, frame = cap.read()
    frame = cv.flip(frame, 1)
    if not hasFrame:
        cv.waitKey()
        break

    frameFace, bboxes = getFaceBox(faceNet, frame)
    if not bboxes:
        print("No face Detected, Checking next frame")
        continue

    for bbox in bboxes:
        # print(bbox)
        face = frame[max(0,bbox[1]-padding):min(bbox[3]+padding,frame.shape[0]-1),max(0,bbox[0]-padding):min(bbox[2]+padding, frame.shape[1]-1)]

        blob = cv.dnn.blobFromImage(face, 1.0, (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 : {}, conf = {:.3f}".format(gender, genderPreds[0].max()))

        ageNet.setInput(blob)
        agePreds = ageNet.forward()
        age = ageList[agePreds[0].argmax()]
        print("Age Output : {}".format(agePreds))
        print("Age : {}, conf = {:.3f}".format(age, agePreds[0].max()))

        label = "{},{}".format(gender, age)
        cv.putText(frameFace, label, (bbox[0], bbox[1]-10), cv.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 255), 2, cv.LINE_AA)
        cv.imshow("Age Gender Demo", frameFace)
    print("time : {:.3f} ms".format(time.time() - t))

总结

公司小姐姐听说我给她们偷偷做了检测年龄的机器,过来扣了我奶茶!

需要完整的项目源码:#源码基地:959755565# 免费领取!

记得三连哈~​下面这个是我希望的亚子:指望你们了~~~~