[硬件環境]

Win10 64位

[軟件環境]

Python版本：2.7.3

IDE：JetBrains PyCharm 2016.3.2

Python庫：

1.1) opencv-python(3.2.0.6)

[搭建過程]

OpenCV Python庫：

1. PyCharm的插件源中選擇opencv-python(3.2.0.6)庫安裝

[相關代碼]

# encoding=utf-8

# 導入必要的軟件包
import argparse
import datetime
import imutils
import time
import cv2

# 創建參數解析器並解析參數
ap = argparse.ArgumentParser()
ap.add_argument(
 
"-v", "--video", help="path to the video file")
ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")
args = vars(ap.parse_args())

# 如果video參數為None，那麽我們從攝像頭讀取數據
if args.get("video", None) is None:
    camera = cv2.VideoCapture(0)
    time.sleep(0.25)

# 否則我們讀取一個視頻文件
else:
    camera 
 
= cv2.VideoCapture(args["video"])

# 初始化視頻流的第一幀
firstFrame = None

# 遍歷視頻的每一幀
while True:
    # 獲取當前幀並初始化occupied/unoccupied文本
    (grabbed, frame) = camera.read()
    text = "Unoccupied"

    # 如果不能抓取到一幀，說明我們到了視頻的結尾
    if not grabbed:
        break

    # 調整該幀的大小，轉換為灰階圖像並且對其進行高斯模糊
    frame = imutils.resize(frame, width=500)
    gray 
 
= cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (21, 21), 0)

    # 如果第一幀是None，對其進行初始化
    if firstFrame is None:
        firstFrame = gray
        continue

    # 計算當前幀和第一幀的不同
    frameDelta = cv2.absdiff(firstFrame, gray)
    thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]

    # 擴展閥值圖像填充孔洞，然後找到閥值圖像上的輪廓
    thresh = cv2.dilate(thresh, None, iterations=2)
    thresh, contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # cv2.findContours()函數返回三個值，第一個返回了你所處理的圖像，第二個是輪廓本身，第三個是每條輪廓對應的屬性

    # 遍歷輪廓
    for c in contours:
        # if the contour is too small, ignore it
        print cv2.contourArea(c)
        if cv2.contourArea(c) < args["min_area"]:
            continue

        # compute the bounding box for the contour, draw it on the frame,
        # and update the text
        # 計算輪廓的邊界框，在當前幀中畫出該框
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
        text = "Occupied"

    # draw the text and timestamp on the frame
    # 在當前幀上寫文字以及時間戳
    cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
    cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
        (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)

    # 顯示當前幀並記錄用戶是否按下按鍵
    cv2.imshow("Security Feed", frame)
    cv2.imshow("Thresh", thresh)
    cv2.imshow("Frame Delta", frameDelta)
    key = cv2.waitKey(1)

    # 如果q鍵被按下，跳出循環
    if key == ord("q"):
        break

# 清理攝像機資源並關閉打開的窗口
camera.release()
cv2.destroyAllWindows()

Python調用OpenCV實現攝像頭的運動檢測