OpenCV Python：cv2.cuda_CascadeClassifier().detectMultiScale() 无误地结束我的程序

Question

Python：Anaconda3 Python 3.8.5 OpenCV：4.5.1

我用 CMake 编译了 OpenCV 和 OpenCV-Contrib，所以我可以在 python 中使用

cuda

函数。 现在我正在尝试使用

cv2.cuda_CascadeClassifier().detectMultiScale()

功能检测人脸。 当我运行它时，一切正常，直到行：

gpu_result = model.classifier_cuda.detectMultiScale(gpu_frame)

也用

**code**

标记它。 一旦这条线被执行，程序就会停止。 我已将终端的输出从头到尾放在我的代码下方。

我的代码：

import time
start_time = time.time()
import cv2
import os
clear = lambda: os.system('cls')

def printMessageWithTime(message):
    print(f"[INFO] {message} - Time: {time.time() - start_time}s")
    
def most_frequent_element_in_list(list):
    counter = 0
    num = list[0]
    
    for i in list:
        curr_frequency = list.count(i)
        if(curr_frequency>counter):
            counter = curr_frequency
            num = i
    return num

printMessageWithTime("Programm started, packages loaded!")
print("OpenCV Version: " + cv2.__version__)

class Model():
    def __init__(self, modelNumber):
        self.trainers_path = "C:/Users/Student/Documents/models"
        self.trainer_main_name = "_percent_trainer"
        self.trainer_names = ["1","5","10"]
        self.model_number = modelNumber
        self.choosen_trainer = f"{self.trainers_path}/{self.trainer_names[self.model_number]}{self.trainer_main_name}.xml"
        self.cascadePath = "C:/Users/Student/Documents/repos/ai_face_recognition/ai_face_recognition/testing/haarcascade_frontalface_default.xml" #cv2.data.haarcascades +
        self.cudacascadePath = "C:/Users/Student/Desktop/new build/opencv-4.5.1/data/haarcascades_cuda/haarcascade_frontalface_default.xml"
        self.faceCascade = cv2.CascadeClassifier(self.cascadePath)
        self.classifier_cuda = cv2.cuda_CascadeClassifier(self.cudacascadePath)
        self.recognizer = cv2.face.LBPHFaceRecognizer_create()
        self.recognizer.read(self.choosen_trainer)

model = Model(0)
printMessageWithTime("Model data loaded!")

class Camera():
    def __init__(self, resolution):
        self.width = resolution[0]
        self.height = resolution[1]
        self.cam = cv2.VideoCapture(0)
        self.cam.set(3,self.width)
        self.cam.set(4,self.height)
        self.minW = 0.25*self.cam.get(3)
        self.minH = 0.25*self.cam.get(4)
Cam = Camera([640,480])
printMessageWithTime("Camera set up!")

detected_ids = []
font = cv2.FONT_HERSHEY_SCRIPT_SIMPLEX

while True:
    start_time = time.time()
    ret, img = Cam.cam.read()
    gray_frame = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gpu_frame = cv2.cuda_GpuMat(gray_frame)
    printMessageWithTime("Detecting")
**  gpu_result = model.classifier_cuda.detectMultiScale(gpu_frame)**
    printMessageWithTime("Detecting finished")
    result = gpu_result.download() # UMat

    id = 0
    confidence = 0
    for(x,y,w,h) in result:   
        cv2.rectangle(img, (x,y),(x+w,y+h), (0,255,0), 2)
        id, confidence = model.recognizer.predict(gray_frame[y:y+h,x:x+w])
        if confidence < 100:
            id = str(id)            
        else:
            id = "unknown"
        confidence = "  {0}%".format(round(100-confidence))
        cv2.putText(img, str(id), (x+5,y-5),font,1,(255,255,255),2)
        cv2.putText(img,str(confidence),(x+5,y+h-5),font,1,(255,255,0),1)
    detected_ids.insert(0,id)
    if len(detected_ids) > 40:
        del detected_ids[0]
    most_frequent_id = most_frequent_element_in_list(detected_ids)
    end_time = time.time()
    try:
        fps = 1 / (end_time - start_time)
    except:
        print("Can not calculate fps, due to division by 0!")
    print(f"[INFO] Time for detection: {end_time - start_time}, Detected Person: {most_frequent_id} - Confidence: {confidence}")
    cv2.imshow('camera',img)
    k = cv2.waitKey(10) & 0xff
    if k == 27:
        break

Cam.cam.release()
cv2.destroyAllWindows()
print("\n[INFO] Exiting program")

终端输出：

PS C:\Users\Student\Documents\repos\ai_face_recognition\ai_face_recognition> & C:/Users/Student/anaconda3/python.exe c:/Users/Student/Documents/repos/ai_face_recognition/ai_face_recognition/recognizer/recognizer_2.py
[INFO] Programm started, packages loaded! - Time: 0.4229726791381836s
OpenCV Version: 4.5.1
[INFO] Model data loaded! - Time: 11.675345182418823s
[INFO] Camera set up! - Time: 41.83551025390625s
[INFO] Detect - Time: 1.9768860340118408s
PS C:\Users\Student\Documents\repos\ai_face_recognition\ai_face_recognition> 

我尝试了为 detectMultiScale 函数创建框架的不同方法，如以下问题所述：“Cuda CascadeClassifier detectMultiScale output is unreadable。 以及这个问题：cv2.cuda_CascadeClassifier in python 但是他们的问题和我的问题不同，我根本没有收到任何错误，并且描述的所有解决方案都不起作用。