2020年大三下学期第十五周学习心得

完成通过摄像头完成人脸的检测跟踪：

import argparse
import time
import imutils
import cv2

# 创建参数解析器并解析参数
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="C:\Users\hp\Desktop\test.mp4")
# 待检测目标的最小面积，该值需根据实际应用情况进行调整(原文为500)
ap.add_argument("-a", "--min-area", type=int, default=2000, help="minimum area size")
args = vars(ap.parse_args())    #@

# 如果video参数为空，则从自带摄像头获取数据
if args.get("video") == None:
    camera = cv2.VideoCapture(0)
# 否则读取指定的视频
else:
    camera = cv2.VideoCapture(args["video"])


# 开始之前先暂停一下,以便跑路(离开本本摄像头拍摄区域^_^)
print("Ready?")
time.sleep(1)
print("Action!")

# 初始化视频第一帧
firstRet, firstFrame = camera.read()
if not firstRet:
    print("Load video error!")
    exit(0)

# 对第一帧进行预处理
firstFrame = imutils.resize(firstFrame, width=500)  # 尺寸缩放，width=500
gray_firstFrame = cv2.cvtColor(firstFrame, cv2.COLOR_BGR2GRAY) # 灰度化
firstFrame = cv2.GaussianBlur(gray_firstFrame, (21, 21), 0) #高斯模糊，用于去噪

# 遍历视频的每一帧
while True:
    (ret, frame) = camera.read()

    # 如果没有获取到数据，则结束循环
    if not ret:
        break

    # 对获取到的数据进行预处理
    frame = imutils.resize(frame, width=500)
    gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray_frame = cv2.GaussianBlur(gray_frame, (21, 21), 0)

    # cv2.imshow('video', firstFrame)
    # 计算第一帧和其他帧的差别
    frameDiff = cv2.absdiff(firstFrame, gray_frame)
    # 忽略较小的差别
    retVal, thresh = cv2.threshold(frameDiff, 25, 255, cv2.THRESH_BINARY)

    # 对阈值图像进行填充补洞
    thresh = cv2.dilate(thresh, None, iterations=2)
    image, contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    text = "Unoccupied"
    # 遍历轮廓
    for contour in contours:
        # if contour is too small, just ignore it
        if cv2.contourArea(contour) < args["min_area"]:
            continue

        # 计算最小外接矩形（非旋转）
        (x, y, w, h) = cv2.boundingRect(contour)
        cv2.rectangle(frame, (x, y), (x+w, y+h), (0,255,0), 2)
        text = "Occupied!"

    cv2.putText(frame, "Room Status: {}".format(text), (10,20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,0,255), 2)

    cv2.imshow('frame', frame)
    cv2.imshow('thresh', thresh)
    cv2.imshow('frameDiff', frameDiff)

    # 处理按键效果
    key = cv2.waitKey(60) & 0xff
    if key == 27:   # 按下ESC时，退出
        break
    elif key == ord(' '):   # 按下空格键时，暂停
        cv2.waitKey(0)

# 释放资源并关闭所有窗口
camera.release()
cv2.destroyAllWindows()