用Python和OpenCV做摄像头监控
jopen
9年前
起因：
我的猪笼草不知道被什么虫子咬了，新长的叶子老是被咬烂，以至于长不出笼子，这还能忍！猪猪草可以已经陪了我快一年了！所以我决定要把真凶揪出来！
分析：白天我经常到阳台去，除了蚂蚁没见过什么异常的虫子，所以我判断虫子应该是夜间出没，而且看叶子上的咬痕，应该是昆虫吃过的痕迹. 我特地跑去问淘宝卖家，希望他有过类似的经验，他说有可能是黑色毛毛虫，其实我也不确定是啥，我也没在阳台见到过毛毛虫.
所以我还是要采取行动，考虑到我平时也不会一直在猪笼草旁边，所以就想做一个监控摄像头，这样就可以实时监控猪笼草附近的一举一动，真凶迟早要现行！
手头材料不多，就只有一个webcam，本来打算买个红外摄像头，以便于夜间监控，但是网购还是要花点时间，所以想先用webcam代替，等做 出来了再考虑要不要换.于是我就上网搜索资料，看看有没有类似蛙眼的实现方法，于是就搜到上面的两篇文章，其实是一篇文章，中文版本为英文版的翻译版本.
我对作者的代码做了一点对应我的需求的改动：
1. 每过一段时间刷新一下首帧，这样就算环境有一点点静态的改变，系统也能很快适应
2. 需要把有入侵者的部分录制和拍照下来，以便于事后观察和取证（因为录制视频很占空间，所以只录制有异常的部分）
以下是老规矩，贴代码（代码的解释在上述引用的文章解释得很清楚了，我比较懒，就不在赘述）：
# http://www.pyimagesearch.com/2015/05/25/basic-motion-detection-and-tracking-with-python-and-opencv/ # http://python.jobbole.com/81593/ # import the necessary packages import argparse import datetime import imutils import time import cv2 import cv2.cv as cv import numpy as np # construct the argument parser and parse the arguments ap = argparse.ArgumentParser() ap.add_argument("-v", "--video", help="path to the video file") ap.add_argument("-a", "--min-area", type=int, default=300, help="minimum area size") args = vars(ap.parse_args()) # if the video argument is None, then we are reading from webcam if args.get("video", None) is None: camera = cv2.VideoCapture(0) time.sleep(0.25) # otherwise, we are reading from a video file else: camera = cv2.VideoCapture(args["video"]) # initialize the first frame in the video stream firstFrame = None # Define the codec fourcc = cv.CV_FOURCC('X', 'V', 'I', 'D') framecount = 0 frame = np.zeros((640,480)) out = cv2.VideoWriter('calm_down_video_'+datetime.datetime.now().strftime("%A_%d_%B_%Y_%I_%M_%S%p")+'.avi',fourcc, 5.0, np.shape(frame)) # to begin with, the light is not stable, calm it down tc = 40 while tc: ret, frame = camera.read() out.write(frame) #cv2.imshow("vw",frame) cv2.waitKey(10) tc -= 1 totalc = 2000 tc = totalc out.release() # loop over the frames of the video while True: # grab the current frame and initialize the occupied/unoccupied # text (grabbed, frame) = camera.read() text = "Unoccupied" # if the frame could not be grabbed, then we have reached the end # of the video if not grabbed: time.sleep(0.25) continue # resize the frame, convert it to grayscale, and blur it frame = imutils.resize(frame, width=500) gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) gray = cv2.GaussianBlur(gray, (21, 21), 0) # update firstFrame for every while if tc%totalc == 0: firstFrame = gray tc = (tc+1) % totalc continue else: tc = (tc+1) % totalc #print tc # compute the absolute difference between the current frame and # first frame frameDelta = cv2.absdiff(firstFrame, gray) thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1] # dilate the thresholded image to fill in holes, then find contours # on thresholded image thresh = cv2.dilate(thresh, None, iterations=2) (cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # loop over the contours for c in cnts: # if the contour is too small, ignore it if cv2.contourArea(c) < args["min_area"]: continue # compute the bounding box for the contour, draw it on the frame, # and update the text (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 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) # show the frame and record if the user presses a key cv2.imshow("Security Feed", frame) cv2.imshow("Thresh", thresh) cv2.imshow("Frame Delta", frameDelta) # save the detection result if text == "Occupied": if framecount == 0: # create VideoWriter object out = cv2.VideoWriter(datetime.datetime.now().strftime("%A_%d_%B_%Y_%I_%M_%S%p")+'.avi',fourcc, 10.0, np.shape(gray)[::-1]) cv2.imwrite(datetime.datetime.now().strftime("%A_%d_%B_%Y_%I_%M_%S%p")+'.jpg',frame) # write the flipped frame out.write(frame) framecount += 1 else: # write the flipped frame out.write(frame) framecount += 1 elif framecount > 20 or framecount<2: out.release() framecount = 0 key = cv2.waitKey(1) & 0xFF # if the `ESC` key is pressed, break from the lop if key == 27: break # cleanup the camera and close any open windows camera.release() cv2.destroyAllWindows()
