最近想做實時目標檢測，需要用到python開啟攝像頭，我手上只有兩個uvc免驅的攝像頭，性能一般。利用python開啟攝像頭費了一番功夫，主要原因是我的攝像頭都不能用cv2的VideCapture打開，這讓我聯想到原來opencv也打不開Android手機上的攝像頭（后來采用QML的Camera模塊實現的）。看來opencv對于攝像頭的兼容性仍然不是很完善。

我嘗了幾種辦法：v4l2，v4l2_capture以及simpleCV，都打不開。最后采用pygame實現了攝像頭的采集功能，這里直接給大家分享具體實現代碼（python3.6，cv2，opencv3.3，ubuntu16.04）。中間注釋的部分是我上述方法打開攝像頭的嘗試，說不定有適合自己的。

import pygame.cameraimport timeimport pygameimport cv2import numpy as np def surface_to_string(surface): """convert pygame surface into string""" return pygame.image.tostring(surface, 'RGB') def pygame_to_cvimage(surface): """conver pygame surface into cvimage"""  #cv_image = np.zeros(surface.get_size, np.uint8, 3) image_string = surface_to_string(surface) image_np = np.fromstring(image_string, np.uint8).reshape(480, 640, 3) frame = cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB) return image_np, frame  pygame.camera.init()pygame.camera.list_cameras()cam = pygame.camera.Camera("/dev/video0", [640, 480]) cam.start()time.sleep(0.1)screen = pygame.display.set_mode([640, 480]) while True: image = cam.get_image()  cv_image, frame = pygame_to_cvimage(image)  screen.fill([0, 0, 0]) screen.blit(image, (0, 0)) pygame.display.update() cv2.imshow('frame', frame) key = cv2.waitKey(1) if key & 0xFF == ord('q'):  break   #pygame.image.save(image, "pygame1.jpg") cam.stop()   

上述代碼需要注意一個地方，就是pygame圖片和opencv圖片的轉化（pygame_to_cvimage）有些地方采用cv.CreateImageHeader和SetData來實現，注意這兩個函數在opencv3+后就消失了。因此采用numpy進行實現。

至于目標檢測，由于現在網上有很多實現的方法，MobileNet等等。這里我不講解具體原理，因為我的研究方向不是這個，這里直接把代碼貼出來，親測成功了。

from imutils.video import FPSimport argparseimport imutils  import v4l2import fcntl import v4l2captureimport selectimport image import pygame.cameraimport pygameimport cv2import numpy as npimport time def surface_to_string(surface): """convert pygame surface into string""" return pygame.image.tostring(surface, 'RGB') def pygame_to_cvimage(surface): """conver pygame surface into cvimage"""  #cv_image = np.zeros(surface.get_size, np.uint8, 3) image_string = surface_to_string(surface) image_np = np.fromstring(image_string, np.uint8).reshape(480, 640, 3) frame = cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB) return frame  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 pretrained model")ap.add_argument("-c", "--confidence", type=float, default=0.2, help="minimum probability to filter weak detection")args = vars(ap.parse_args()) CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow",   "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"]COLORS = np.random.uniform(0, 255, size=(len(CLASSES), 3)) print("[INFO] loading model...")net = cv2.dnn.readNetFromCaffe(args["prototxt"], args["model"])  print("[INFO] starting video stream ...") ###### opencv #########vs = VideoStream(src=1).start()##camera = cv2.VideoCapture(0)#if not camera.isOpened():# print("camera is not open")#time.sleep(2.0)  ###### v4l2 ######## #vd = open('/dev/video0', 'r')#cp = v4l2.v4l2_capability()#fcntl.ioctl(vd, v4l2.VIDIOC_QUERYCAP, cp) #cp.driver  ##### v4l2_capture#video = v4l2capture.Video_device("/dev/video0")#size_x, size_y = video.set_format(640, 480, fourcc= 'MJPEG')#video.create_buffers(30) #video.queue_all_buffers() #video.start() ##### pygame ####pygame.camera.init()pygame.camera.list_cameras()cam = pygame.camera.Camera("/dev/video0", [640, 480]) cam.start()time.sleep(1) fps = FPS().start()  while True: #try: # frame = vs.read() #except: # print("camera is not opened")  #frame = imutils.resize(frame, width=400) #(h, w) = frame.shape[:2]   #grabbed, frame = camera.read() #if not grabbed: # break #select.select((video,), (), ()) #frame = video.read_and_queue()  #npfs = np.frombuffer(frame, dtype=np.uint8) #print(len(npfs)) #frame = cv2.imdecode(npfs, cv2.IMREAD_COLOR)  image = cam.get_image() frame = pygame_to_cvimage(image)  frame = imutils.resize(frame, width=640) blob = cv2.dnn.blobFromImage(frame, 0.00783, (640, 480), 127.5)  net.setInput(blob) detections = net.forward()  for i in np.arange(0, detections.shape[2]):   confidence = detections[0, 0, i, 2]   if confidence > args["confidence"]:    idx = int(detections[0, 0, i, 1])   box = detections[0, 0, i, 3:7]*np.array([640, 480, 640, 480])   (startX, startY, endX, endY) = box.astype("int")    label = "{}:{:.2f}%".format(CLASSES[idx], confidence*100)   cv2.rectangle(frame, (startX, startY), (endX, endY), COLORS[idx], 2)   y = startY - 15 if startY - 15 > 15 else startY + 15    cv2.putText(frame, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, COLORS[idx], 2)  cv2.imshow("Frame", frame) key = cv2.waitKey(1)& 0xFF  if key ==ord("q"):  break  fps.stop()print("[INFO] elapsed time :{:.2f}".format(fps.elapsed()))print("[INFO] approx. FPS :{:.2f}".format(fps.fps()))   cv2.destroyAllWindows() #vs.stop()