Python 我正在用OpenCV制作蒙面人脸检测应用程序，用于检测戴面具的人脸，但我遇到了一个错误

是否有任何模块需要导入

还是全部正确导入

我不调试它

我重新格式化了一次文件

我已经得到了所有需要的xml和jpg文件

我已经导入了所有需要的模块。。。我想是的

下面是错误

你能帮我吗？我是OpenCV的新手，遇到了这样一个复杂的错误

感谢Stackoverflow社区的所有帮助：）

C:\Users\Toshiba\Desktop\python\u temelleri\venv\Scripts\python.exe C:/Users/Toshiba/Desktop/python\u temelleri/detect\u mask\u video.py
2020-08-28 16:47:05.729423:W tensorflow/stream_executor/platform/default/dso_loader.cc:59]无法加载动态库“cudart64_101.dll”；错误：找不到cudart64_101.dll
2020-08-28 16:47:05.730054:I tensorflow/stream_executor/cuda/cudart_stub.cc:29]如果您的计算机上没有设置GPU，请忽略上面的cudart数据错误。
回溯（最近一次呼叫最后一次）：
文件“C:/Users/Toshiba/Desktop/python_temelleri/detect_mask_video.py”，第60行，在
faceNet=cv2.dnn.readNet（prototxtPath，weightsPath）
cv2.error:OpenCV（4.4.0）C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-2b5g8ysb\OpenCV\modules\dnn\src\caffe\caffe\U io.cpp:1121:error:（-2：未指定的错误）失败：fs.is\U open（）。无法在函数“cv:：dnn:：ReadProtoFromTextFile”中打开“face\u detector\deploy.prototxt”
[信息]正在加载人脸检测器模型。。。
进程已完成，退出代码为1

您可能没有提供模型，或者模型的路径不正确。打印prototxtPath和weightsPath的值，以检查您是否提供了正确的模型路径。

您是否阅读了错误消息？否。即使我在函数“cv:：dnn:：ReadProtoFromTextFile”中“无法打开”face\u detector\deploy.prototxt”，我也不理解任何内容好的。谢谢：）：）：）：）：：）：）：：：）：：）：：）：：）：）：：）：：）：：）：：）：）：）：）：）：）：）：）：）：）：）：）：）：）：）：）：）谢谢你的回答：））））））（谢谢你的回答：）（谢谢你的回答：）（我不能投我的票，谢谢你！声誉低于15的人所投的票将被记录，但不会改变公开显示的帖子分数。”。

from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.models import load_model
from imutils.video import VideoStream
import numpy as np
import argparse
import imutils
import time
import cv2
import os


def detect_and_predict_mask(frame, faceNet, maskNet):
    (h, w) = frame.shape[:2]
    blob = cv2.dnn.blobFromImage(frame, 1.0, (300, 300),
                                 (104.0, 177.0, 123.0))
    faceNet.setInput(blob)
    detections = faceNet.forward()
    faces = []
    locs = []
    preds = []

    for i in range(0, detections.shape[2]):
        confidence = detections[0, 0, i, 2]
        if confidence > args["confidence"]:
            box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
            (startX, startY, endX, endY) = box.astype("int")
            (startX, startY) = (max(0, startX), max(0, startY))
            (endX, endY) = (min(w - 1, endX), min(h - 1, endY))
            face = frame[startY:endY, startX:endX]
            face = cv2.cvtColor(face, cv2.COLOR_BGR2RGB)
            face = cv2.resize(face, (224, 224))
            face = img_to_array(face)
            face = preprocess_input(face)
            face = np.expand_dims(face, axis=0)
            faces.append(face)
            locs.append((startX, startY, endX, endY))

    if len(faces) > 0:
        preds = maskNet.predict(faces)
    return (locs, preds)


ap = argparse.ArgumentParser()
ap.add_argument("-f", "--face", type=str,
                default="face_detector",
                help="path to face detector model directory")
ap.add_argument("-m", "--model", type=str,
                default="mask_detector.model",
                help="path to trained face mask detector model")
ap.add_argument("-c", "--confidence", type=float, default=0.5,
                help="minimum probability to filter weak detections")
args = vars(ap.parse_args())
print("[INFO] loading face detector model...")
prototxtPath = os.path.sep.join([args["face"], "deploy.prototxt"])
weightsPath = os.path.sep.join([args["face"],
                                "res10_300x300_ssd_iter_140000.caffemodel"])
faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)

print("[INFO] loading face mask detector model...")
maskNet = load_model(args["model"])

print("[INFO] starting video stream...")
vs = VideoStream(src=0).start()
time.sleep(2.0)

while True:
    frame = vs.read()
    frame = imutils.resize(frame, width=400)
    (locs, preds) = detect_and_predict_mask(frame, faceNet, maskNet)
    for (box, pred) in zip(locs, preds):
        (startX, startY, endX, endY) = box
        (mask, withoutMask) = pred
        label = "Mask" if mask > withoutMask else "No Mask"
        color = (0, 255, 0) if label == "Mask" else (0, 0, 255)
        label = "{}: {:.2f}%".format(label, max(mask, withoutMask) * 100)
        cv2.putText(frame, label, (startX, startY - 10),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2)
        cv2.rectangle(frame, (startX, startY), (endX, endY), color, 2)

    cv2.imshow("Frame", frame)
    key = cv2.waitKey(1) & 0xFF
    if key == ord("q"):
        break

cv2.destroyAllWindows()
vs.stop()

C:\Users\Toshiba\Desktop\python_temelleri\venv\Scripts\python.exe C:/Users/Toshiba/Desktop/python_temelleri/detect_mask_video.py
2020-08-28 16:47:05.729423: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2020-08-28 16:47:05.730054: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Traceback (most recent call last):
  File "C:/Users/Toshiba/Desktop/python_temelleri/detect_mask_video.py", line 60, in <module>
    faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)
cv2.error: OpenCV(4.4.0) C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-2b5g8ysb\opencv\modules\dnn\src\caffe\caffe_io.cpp:1121: error: (-2:Unspecified error) FAILED: fs.is_open(). Can't open "face_detector\deploy.prototxt" in function 'cv::dnn::ReadProtoFromTextFile'

[INFO] loading face detector model...

Process finished with exit code 1