python 2.7中的多线程？

-2

我正在做最后的项目研究与树莓卡，我想同时使用两个摄像头，并运行相同的蟒蛇程序与两个摄像头拍照，并使治疗知道产品我该怎么做到这一点使用多线程python 2.7中的多线程？

from os import listdir 
from os.path import isfile, join 
import numpy 
import cv2 
import os 
import sys 

def match_images(img1, img2): 

    detector = cv2.SURF(200, 1, 1) 
    matcher = cv2.BFMatcher(cv2.NORM_L2) 
    kp1, desc1 = detector.detectAndCompute(img1, None) 
    kp2, desc2 = detector.detectAndCompute(img2, None) 
    print 'img1 %d features, img2 %d features' % (len(kp1), len(kp2)) 
    raw_matches = matcher.knnMatch(desc1, trainDescriptors = desc2, k = 2) 
    kp_pairs = filter_matches(kp1, kp2, raw_matches) 
    return kp_pairs 

def filter_matches(kp1, kp2, matches, ratio = 0.75): 

    mkp1, mkp2 = [], [] 
    for m in matches: 
     if len(m) == 2 and m[0].distance < m[1].distance * ratio: 
      m = m[0] 
      mkp1.append(kp1[m.queryIdx]) 
      mkp2.append(kp2[m.trainIdx]) 
    kp_pairs = zip(mkp1, mkp2) 
    return kp_pairs 

def explore_match(win, img1, img2, kp_pairs, status = None, H = None): 

    h1, w1 = img1.shape[:2] 
    h2, w2 = img2.shape[:2] 
    vis = numpy.zeros((max(h1, h2), w1+w2), numpy.uint8) 
    vis[:h1, :w1] = img1 
    vis[:h2, w1:w1+w2] = img2 
    vis = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR) 
    if H is not None: 
     corners = numpy.float32([[0, 0], [w1, 0], [w1, h1], [0, h1]]) 
     corners = numpy.int32(cv2.perspectiveTransform(corners.reshape(1, -1, 2), H).reshape(-1, 2) + (w1, 0)) 
     cv2.polylines(vis, [corners], True, (255, 255, 255)) 
    if status is None: 
     status = numpy.ones(len(kp_pairs), numpy.bool_) 
    p1 = numpy.int32([kpp[0].pt for kpp in kp_pairs]) 
    p2 = numpy.int32([kpp[1].pt for kpp in kp_pairs]) + (w1, 0) 
    green = (0, 255, 0) 
    red = (0, 0, 255) 
    white = (255, 255, 255) 
    kp_color = (51, 103, 236) 
    for (x1, y1), (x2, y2), inlier in zip(p1, p2, status): 
     if inlier: 
      col = green 
      cv2.circle(vis, (x1, y1), 2, col, -1) 
      cv2.circle(vis, (x2, y2), 2, col, -1) 
     else: 
      col = red 
      r = 2 
      thickness = 3 
      cv2.line(vis, (x1-r, y1-r), (x1+r, y1+r), col, thickness) 
      cv2.line(vis, (x1-r, y1+r), (x1+r, y1-r), col, thickness) 
      cv2.line(vis, (x2-r, y2-r), (x2+r, y2+r), col, thickness) 
      cv2.line(vis, (x2-r, y2+r), (x2+r, y2-r), col, thickness) 
    vis0 = vis.copy() 
    for (x1, y1), (x2, y2), inlier in zip(p1, p2, status): 
     if inlier: 
      cv2.line(vis, (x1, y1), (x2, y2), green) 
    cv2.imshow(win, vis) 

def draw_matches(window_name, kp_pairs, img1, img2): 

mkp1, mkp2 = zip(*kp_pairs)  
p1 = numpy.float32([kp.pt for kp in mkp1]) 
p2 = numpy.float32([kp.pt for kp in mkp2]) 
if len(kp_pairs) >= 100: 
     H, status = cv2.findHomography(p1, p2, cv2.RANSAC, 5.0) 
     print '%d/%d inliers/matched' % (numpy.sum(status), len(status)) 
     import RPI.GPIO as GPIO 
     import time 
     GPIO.setup(LEDPin, GPIO.OUT) 
     GPIO.output(LEDPin, True) 
     print("LED ON") 
     time.sleep(5) 
     GPIO.output(LEDPin, False) 
if len(p1): 
     explore_match(window_name, img1, img2, kp_pairs, status, H) 

if __name__ == '__main__': 

import cv2 
import os 
camera_port = 1 
ramp_frames = 2 
camera = cv2.VideoCapture(camera_port) 
def get_image(): 
    retval, im = camera.read() 
    return im 
    for i in xrange(ramp_frames): 
    temp = get_image() 
    print("Taking image...") 
    camera_capture = get_image() 
    file = "C:/Users/oussema/Desktop/projet/scripts/test_image.png" 
    cv2.imwrite(file, camera_capture) 
    del(camera) 
    img2 = cv2.imread('test_image.png', 0) 
    img1 = cv2.imread('1.jpg', 0) 
    if img1 is None: 
     print 'Failed to load img1:' 
     sys.exit(1)  
    if img2 is None: 
     print 'Failed to load img2:' 
     sys.exit(1) 
    kp_pairs = match_images(img1, img2) 
    if len(kp_pairs) >= 100: 
    draw_matches('find_obj', kp_pairs, img1, img2) 
    cv2.waitKey() 
    cv2.destroyAllWindows() 
    elif len(kp_pairs) <= 100: 
    print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
    img1 = cv2.imread('2.jpg', 0) 
    kp_pairs = match_images(img1, img2) 
    if len(kp_pairs) >= 100: 
     draw_matches('find_obj', kp_pairs, img1, img2) 
     cv2.waitKey() 
     cv2.destroyAllWindows() 
    elif len(kp_pairs) <= 100: 
     print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
     img1 = cv2.imread('3.jpg', 0) 
     kp_pairs = match_images(img1, img2) 
     if len(kp_pairs) >= 100: 
     draw_matches('find_obj', kp_pairs, img1, img2) 
     cv2.waitKey() 
     cv2.destroyAllWindows() 
     elif len(kp_pairs) <= 100: 
      print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
      img1 = cv2.imread('4.jpg', 0) 
      kp_pairs = match_images(img1, img2) 
      if len(kp_pairs) >= 100: 
       draw_matches('find_obj', kp_pairs, img1, img2) 
       cv2.waitKey() 
       cv2.destroyAllWindows() 
      elif len(kp_pairs) <= 100: 
       print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
       img1 = cv2.imread('5.jpg', 0) 
       kp_pairs = match_images(img1, img2) 
       if len(kp_pairs) >= 100: 
       draw_matches('find_obj', kp_pairs, img1, img2) 
       cv2.waitKey() 
       cv2.destroyAllWindows() 
       elif len(kp_pairs) <= 100: 
       print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
       img1 = cv2.imread('6.jpg', 0) 
       kp_pairs = match_images(img1, img2) 
       if len(kp_pairs) >= 100: 
        draw_matches('find_obj', kp_pairs, img1, img2) 
        cv2.waitKey() 
        cv2.destroyAllWindows() 
       elif len(kp_pairs) <= 100: 
        print '%d matches found, not enough for homography estimation' % len(kp_pairs)

来源

2016-03-25 Oussema Helal

您是否尝试过的多线程库？ – Seekheart

可能的重复[如何在Python中使用线程？]（http://stackoverflow.com/questions/2846653/how-to-use-threading-in-python） – Signal

否我不明白如何使用多线程来执行我的代码在同一时间2台摄像机 –

下面是一个例子，我给你留下了空间来放置你的相机代码。

import thread 
import time 

# Define a function for the thread 
def camera(threadName, delay): 
    # Your Code to take a picture, or whatever 

# Create two threads as follows 
try: 
    thread.start_new_thread(camera, ("camera-1", 2,)) 
    thread.start_new_thread(camera, ("camera-2", 4,)) 
except: 
    print "Error: unable to start thread" 

while 1: 
    pass

来源

2016-03-25 03:00:58 ReverseCold

如果你看到我的代码，你可以帮我请 –

我不认为你可以同时运行2个线程，由于GIL。那么，可能你可以试试multiprocessing模块。

突出部分尝试：

from multiprocessing import Process 

def Camera(name): 
    print('hello', name) 

if __name__ == '__main__': 
    p1 = Process(target=Camera, args=('bob',)) 
    p2 = Process(target=Camera, args=('jack',)) 
    p1.start() 
    p2.start() 
    p1.join() 
    p2.join()

来源

2016-03-25 03:11:37

如果你看到我的代码，我该怎么做多处理或多线程我可以用2个摄像头同时代码avec？ –

@OussemaHelal，请等待，如果你有更多的细节要显示，只需编辑你的问题，并在上面的问题中显示你的代码。用正确的缩进显示代码。谢谢！ –

先生您可以寄给我您的邮件，或者如果您想我可以通过邮件向您发送代码，那么我的邮件是：[email protected]，因为我无法理解您对我的要求确切感谢 –

from os import listdir 
from os.path import isfile, join 
import numpy 
import cv2 
import os 
import sys 

def match_images(img1, img2): 

detector = cv2.SURF(200, 1, 1) 
matcher = cv2.BFMatcher(cv2.NORM_L2) 
kp1, desc1 = detector.detectAndCompute(img1, None) 
kp2, desc2 = detector.detectAndCompute(img2, None) 
print 'img1 %d features, img2 %d features' % (len(kp1), len(kp2)) 
raw_matches = matcher.knnMatch(desc1, trainDescriptors = desc2, k = 2) 
kp_pairs = filter_matches(kp1, kp2, raw_matches) 
return kp_pairs 

def filter_matches(kp1, kp2, matches, ratio = 0.75): 

mkp1, mkp2 = [], [] 
for m in matches: 
    if len(m) == 2 and m[0].distance < m[1].distance * ratio: 
     m = m[0] 
     mkp1.append(kp1[m.queryIdx]) 
     mkp2.append(kp2[m.trainIdx]) 
kp_pairs = zip(mkp1, mkp2) 
return kp_pairs 

def explore_match(win, img1, img2, kp_pairs, status = None, H = None): 

h1, w1 = img1.shape[:2] 
h2, w2 = img2.shape[:2] 
vis = numpy.zeros((max(h1, h2), w1+w2), numpy.uint8) 
vis[:h1, :w1] = img1 
vis[:h2, w1:w1+w2] = img2 
vis = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR) 
if H is not None: 
    corners = numpy.float32([[0, 0], [w1, 0], [w1, h1], [0, h1]]) 
    corners = numpy.int32(cv2.perspectiveTransform(corners.reshape(1, -1, 2), H).reshape(-1, 2) + (w1, 0)) 
    cv2.polylines(vis, [corners], True, (255, 255, 255)) 
if status is None: 
    status = numpy.ones(len(kp_pairs), numpy.bool_) 
p1 = numpy.int32([kpp[0].pt for kpp in kp_pairs]) 
p2 = numpy.int32([kpp[1].pt for kpp in kp_pairs]) + (w1, 0) 
green = (0, 255, 0) 
red = (0, 0, 255) 
white = (255, 255, 255) 
kp_color = (51, 103, 236) 
for (x1, y1), (x2, y2), inlier in zip(p1, p2, status): 
    if inlier: 
     col = green 
     cv2.circle(vis, (x1, y1), 2, col, -1) 
     cv2.circle(vis, (x2, y2), 2, col, -1) 
    else: 
     col = red 
     r = 2 
     thickness = 3 
     cv2.line(vis, (x1-r, y1-r), (x1+r, y1+r), col, thickness) 
     cv2.line(vis, (x1-r, y1+r), (x1+r, y1-r), col, thickness) 
     cv2.line(vis, (x2-r, y2-r), (x2+r, y2+r), col, thickness) 
     cv2.line(vis, (x2-r, y2+r), (x2+r, y2-r), col, thickness) 
vis0 = vis.copy() 
for (x1, y1), (x2, y2), inlier in zip(p1, p2, status): 
    if inlier: 
     cv2.line(vis, (x1, y1), (x2, y2), green) 
cv2.imshow(win, vis) 

def draw_matches(window_name, kp_pairs, img1, img2): 

    mkp1, mkp2 = zip(*kp_pairs)  
    p1 = numpy.float32([kp.pt for kp in mkp1]) 
    p2 = numpy.float32([kp.pt for kp in mkp2]) 
    if len(kp_pairs) >= 100: 
    H, status = cv2.findHomography(p1, p2, cv2.RANSAC, 5.0) 
    print '%d/%d inliers/matched' % (numpy.sum(status), len(status)) 
    import RPI.GPIO as GPIO 
    import time 
    GPIO.setup(LEDPin, GPIO.OUT) 
    GPIO.output(LEDPin, True) 
    print("LED ON") 
    time.sleep(5) 
    GPIO.output(LEDPin, False) 
    if len(p1): 
    explore_match(window_name, img1, img2, kp_pairs, status, H) 

if __name__ == '__main__': 

    import cv2 
    import os 
    camera_port = 1 
    ramp_frames = 2 
    camera = cv2.VideoCapture(camera_port) 
    def get_image(): 
    retval, im = camera.read() 
    return im 
    for i in xrange(ramp_frames): 
    temp = get_image() 
    print("Taking image...") 
    camera_capture = get_image() 
    file = "C:/Users/oussema/Desktop/projet/scripts/test_image.png" 
    cv2.imwrite(file, camera_capture) 
    del(camera) 
    img2 = cv2.imread('test_image.png', 0) 
    img1 = cv2.imread('1.jpg', 0) 
    if img1 is None: 
    print 'Failed to load img1:' 
    sys.exit(1)  
    if img2 is None: 
    print 'Failed to load img2:' 
    sys.exit(1) 
    kp_pairs = match_images(img1, img2) 
    if len(kp_pairs) >= 100: 
    draw_matches('find_obj', kp_pairs, img1, img2) 
    cv2.waitKey() 
    cv2.destroyAllWindows() 
    elif len(kp_pairs) <= 100: 
    print '%d matches found, not enough for homography estimation' %  len(kp_pairs) 
    img1 = cv2.imread('2.jpg', 0) 
    kp_pairs = match_images(img1, img2) 
    if len(kp_pairs) >= 100: 
    draw_matches('find_obj', kp_pairs, img1, img2) 
    cv2.waitKey() 
    cv2.destroyAllWindows() 
    elif len(kp_pairs) <= 100: 
    print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
    img1 = cv2.imread('3.jpg', 0) 
    kp_pairs = match_images(img1, img2) 
    if len(kp_pairs) >= 100: 
    draw_matches('find_obj', kp_pairs, img1, img2) 
    cv2.waitKey() 
    cv2.destroyAllWindows() 
    elif len(kp_pairs) <= 100: 
     print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
     img1 = cv2.imread('4.jpg', 0) 
     kp_pairs = match_images(img1, img2) 
     if len(kp_pairs) >= 100: 
      draw_matches('find_obj', kp_pairs, img1, img2) 
      cv2.waitKey() 
      cv2.destroyAllWindows() 
     elif len(kp_pairs) <= 100: 
      print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
      img1 = cv2.imread('5.jpg', 0) 
      kp_pairs = match_images(img1, img2) 
      if len(kp_pairs) >= 100: 
      draw_matches('find_obj', kp_pairs, img1, img2) 
      cv2.waitKey() 
      cv2.destroyAllWindows() 
      elif len(kp_pairs) <= 100: 
      print '%d matches found, not enough for homography estimation' % len(kp_pairs) 
      img1 = cv2.imread('6.jpg', 0)`` 
      kp_pairs = match_images(img1, img2) 
      if len(kp_pairs) >= 100: 
       draw_matches('find_obj', kp_pairs, img1, img2) 
       cv2.waitKey() 
       cv2.destroyAllWindows() 
      elif len(kp_pairs) <= 100: 
       print '%d matches found, not enough for homography estimation' % len(kp_pairs)

来源

2016-03-25 03:15:58

我用2相机，因为我有一个问题，当该产品是在垫子上

来源

2016-03-25 03:37:15

python 2.7中的多线程？

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