问如何使用cv2.dnn_detectionModel方法定制目标检测

EN

import cv2
import numpy as np

#Threshold setup
thres = 0.3 # Threshold to detect object
nms_threshold = 0.2

#camera setup
cap = cv2.VideoCapture(0)
#cap.set(3,1080)
#cap.set(4,1920)
#cap.set(10,300)

#standard configuration setting up
classFile = "coco.names"
classNames = []
with open(classFile,"rt") as f:
        classNames = f.read().rstrip("\n").split("\n")

#print(classNames)
configPath = "/home/pi/darknet/ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt"
weightPath = "/home/pi/darknet/frozen_inference_graph.pb"

net = cv2.dnn_DetectionModel(configPath,weightPath)
net.setInputSize(320,320)
net.setInputScale(1.0/ 120)
net.setInputMean((120, 120, 120))
net.setInputSwapRB(True)

while True:
    success,img = cap.read()

    img = cv2.flip(img, 0)

    classIds, confs, bbox = net.detect(img,confThreshold=thres)
    bbox = list(bbox)
    confs = list(np.array(confs).reshape(1,-1)[0])
    confs = list(map(float,confs))
    #print(type(confs[0]))
    #print(confs)

    indices = cv2.dnn.NMSBoxes(bbox,confs,thres,nms_threshold)
    #print(indices)

    for i in indices:
        i = i[0]
        box = bbox[i]
        x,y,w,h = box[0], box[1], box[2], box[3]
        cv2.rectangle(img, (x,y),(x+w,h+y), color=(0,255,0),thickness=1)
        cv2.putText(img,classNames[classIds[i][0]-1].upper(),(box[0]+10,box[1]+30),
            cv2.FONT_HERSHEY_COMPLEX,1,(0,255,0),1)

    cv2.imshow("Output",img)
    cv2.waitKey(1)