项目场景：人脸识别

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:/PythonFlask/opencv_face_detector.pbtxt"
faceModel = "D:/PythonFlask/opencv_face_detector_uint8.pb"
 
ageProto = "D:/PythonFlask/age_deploy.prototxt"
ageModel = "D:/PythonFlask/age_net.caffemodel"
 
genderProto = "D:/PythonFlask/gender_deploy.prototxt"
genderModel = "D:/PythonFlask/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))
 

报错信息：

Traceback (most recent call last):
  File "D:\PythonFlask\test.py", line 42, in <module>
    faceNet = cv.dnn.readNet(faceModel, faceProto)
cv2.error: OpenCV(4.5.5) D:\a\opencv-python\opencv-python\opencv\modules\dnn\src\tensorflow\tf_importer.cpp:2984: error: (-215:Assertion failed) netBinSize || netTxtSize in function 'cv::dnn::dnn4_v20211220::`anonymous-namespace'::TFImporter::populateNet'
 

哪位大佬帮忙解答一下，有偿作答