Wifi模块与人脸识别录像同时运行，为什么从手机登陆网址看只有一帧

lndf

MJPEG Streaming AP.

这个例子展示了如何在AccessPoint模式下进行MJPEG流式传输。

Android上的Chrome，Firefox和MJpegViewer App已经过测试。

连接到OPENMV_AP并使用此URL：http://192.168.1.1:8080查看流。

import sensor, image, time, network, usocket, sys, mjpeg, pyb

SSID ='wlan work,face detection error' # Network SSID
KEY ='1234567890' # Network key (must be 10 chars)
HOST = '' # Use first available interface
PORT = 8080 # Arbitrary non-privileged port
RED_LED_PIN = 1
BLUE_LED_PIN = 3

Reset sensor

sensor.reset()

Set sensor settings

sensor.set_contrast(1)
sensor.set_brightness(1)
sensor.set_saturation(1)
sensor.set_gainceiling(16)
sensor.set_framesize(sensor.QQVGA)
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.skip_frames(time = 2000) # Let new settings take affect.
face_cascade = image.HaarCascade("frontalface", stages=25)

在AP模式下启动wlan模块。

wlan = network.WINC(mode=network.WINC.MODE_AP)
wlan.start_ap(SSID, key=KEY, security=wlan.WEP, channel=2)

#您可以阻止等待客户端连接
#print(wlan.wait_for_sta(10000))

def start_streaming(s):
print ('Waiting for connections..')
client, addr = s.accept()
# 将客户端套接字超时设置为2秒
client.settimeout(2.0)
print ('Connected to ' + addr[0] + ':' + str(addr[1]))

# 从客户端读取请求
data = client.recv(1024)
# 应该在这里解析客户端请求

# 发送多部分head
client.send("HTTP/1.1 200 OK\r\n" \
            "Server: OpenMV\r\n" \
            "Content-Type: multipart/x-mixed-replace;boundary=openmv\r\n" \
            "Cache-Control: no-cache\r\n" \
            "Pragma: no-cache\r\n\r\n")

# FPS clock
clock = time.clock()

# 开始流媒体图像
#注：禁用IDE预览以增加流式FPS。
while (True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    frame = sensor.snapshot()
    cframe = frame.compressed(quality=35)
    header = "\r\n--openmv\r\n" \
             "Content-Type: image/jpeg\r\n"\
             "Content-Length:"+str(cframe.size())+"\r\n\r\n"
    client.send(header)
    client.send(cframe)
    print(clock.fps())
    print("123")
    pyb.LED(RED_LED_PIN).on()
    print("About to start detecting faces...")
    sensor.skip_frames(time = 2000) # Give the user time to get ready.

    pyb.LED(RED_LED_PIN).off()
    print("Now detecting faces!")
    pyb.LED(BLUE_LED_PIN).on()

    diff = 10 # We'll say we detected a face after 10 frames.
    while(diff):
        img = sensor.snapshot()
        # Threshold是介于0.0-1.0的阈值，较低值会同时提高检出率和假阳性
        # 率。相反，较高值会同时降低检出率和假阳性率。
        # scale是一个必须大于1.0的浮点数。较高的比例因子运行更快，
        # 但其图像匹配相应较差。理想值介于1.35-1.5之间。

        faces = img.find_features(face_cascade, threshold=0.5, scale_factor=1.5)

        if faces:
            diff -= 1
            for r in faces:
                img.draw_rectangle(r)

    m = mjpeg.Mjpeg("example4-%d.mjpeg" % pyb.rng())

    clock = time.clock() # Tracks FPS.
    print("You're on camera!")
    for i in range(200):
        clock.tick()
        m.add_frame(sensor.snapshot())
        print(clock.fps())

    m.close(clock.fps())
    pyb.LED(BLUE_LED_PIN).off()
    print("Restarting...")

while (True):
print("456")
# 创建服务器套接字
s = usocket.socket(usocket.AF_INET, usocket.SOCK_STREAM)
try:
# Bind and listen
s.bind([HOST, PORT])
s.listen(5)

    # 设置服务器套接字超时
    # 注意：由于WINC FW bug，如果客户端断开连接，服务器套接字必须
    # 关闭并重新打开。在这里使用超时关闭并重新创建套接字。
    s.settimeout(3)
    start_streaming(s)
except OSError as e:
    s.close()
    print("socket error: ", e)
    #sys.print_exception(e)

kidswong999

代码不对啊。

不需要多次 sensor.snapshot()，这样发送的图像和检测的图像都不是一样的。

skip_frames也不需要

kidswong999

def start_streaming(s):
    print ('Waiting for connections..')
    client, addr = s.accept()
    # 将客户端套接字超时设置为2秒
    client.settimeout(2.0)
    print ('Connected to ' + addr[0] + ':' + str(addr[1]))

    # 从客户端读取请求
    data = client.recv(1024)
    # 应该在这里解析客户端请求

    # 发送多部分head
    client.send("HTTP/1.1 200 OK\r\n" \
                "Server: OpenMV\r\n" \
                "Content-Type: multipart/x-mixed-replace;boundary=openmv\r\n" \
                "Cache-Control: no-cache\r\n" \
                "Pragma: no-cache\r\n\r\n")

    # FPS clock
    clock = time.clock()

    # 开始流媒体图像
    #注：禁用IDE预览以增加流式FPS。
    while (True):
        clock.tick() # Track elapsed milliseconds between snapshots().
        frame = sensor.snapshot()
        faces = frame.find_features(face_cascade, threshold=0.5, scale_factor=1.5)
        for r in faces:
            frame.draw_rectangle(r)
        cframe = frame.compressed(quality=35)
        header = "\r\n--openmv\r\n" \
                 "Content-Type: image/jpeg\r\n"\
                 "Content-Length:"+str(cframe.size())+"\r\n\r\n"
        client.send(header)
        client.send(cframe)

lndf

@kidswong999 还是不行啊，我想的是WIFI同步影像以及人脸识别录像，这个 WIFI 模块上看实时影像还是只有一张图，卡顿的然后就不更新图像了