As we can see we need to give two parameters that are the pre-trained model and de caffe deploy.
Explaining the code.
First we need to import the packages that we are going to use
# import the necessary packages
from imutils.video import VideoStream
from imutils.video import FPS
import numpy as np
import argparse
import imutils
import time
import cv2
Initialice the parameters that we are going to use
Caffe deploy
Caffe pre-trained model
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--prototxt", required=True,
help="path to Caffe 'deploy' prototxt file")
ap.add_argument("-m", "--model", required=True,
help="path to Caffe pre-trained model")
ap.add_argument("-c", "--confidence", type=float, default=0.2,
help="minimum probability to filter weak detections")
args = vars(ap.parse_args())
Give the list of object that our MobileNet SSD was trained, and create rectangles to introduce to the frame when a object is detected.