• OpenMV VSCode 扩展发布了,在插件市场直接搜索OpenMV就可以安装
  • 如果有产品硬件故障问题,比如无法开机,论坛很难解决。可以直接找售后维修
  • 发帖子之前,请确认看过所有的视频教程,https://singtown.com/learn/ 和所有的上手教程http://book.openmv.cc/
  • 每一个新的提问,单独发一个新帖子
  • 帖子需要目的,你要做什么?
  • 如果涉及代码,需要报错提示全部代码文本,请注意不要贴代码图片
  • 必看:玩转星瞳论坛了解一下图片上传,代码格式等问题。
  • 我想把深度学习检测到的结果通过WiFi模块发送到电脑上



    • import sensor, image, time, os, tf, uos, gc, network, usocket, sys, json
      
      SSID ='OPENMV_AP'    # Network SSID
      KEY  ='1234567890'    # Network key (must be 10 chars)
      HOST = ''           # Use first available interface
      PORT = 8080         # Arbitrary non-privileged port
      
      
      
      # 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.RGB565)    # Set pixel format to RGB565 (or GRAYSCALE)
      sensor.set_windowing((240, 240))       # Set 240x240 window.
      sensor.skip_frames(time=2000)          # Let the camera adjust.
      
      net = None
      labels = None
      
      try:
          # load the model, alloc the model file on the heap if we have at least 64K free after loading
          net = tf.load("trained.tflite", load_to_fb=uos.stat('trained.tflite')[6] > (gc.mem_free() - (64*1024)))
      except Exception as e:
          print(e)
          raise Exception('Failed to load "trained.tflite", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')
      
      try:
          labels = [line.rstrip('\n') for line in open("labels.txt")]
      except Exception as e:
          raise Exception('Failed to load "labels.txt", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')
      
      clock = time.clock()
      
      
      # Init wlan module in AP mode.
      wlan = network.WINC(mode=network.WINC.MODE_AP)
      wlan.start_ap(SSID, key=KEY, security=wlan.WEP, channel=2)
      
      # You can block waiting for client to connect
      #print(wlan.wait_for_sta(10000))
      
      def response(s):
          print ('Waiting for connections..')
          client, addr = s.accept()
          # set client socket timeout to 2s
          client.settimeout(2.0)
          print ('Connected to ' + addr[0] + ':' + str(addr[1]))
      
          # Read request from client
          data = client.recv(1024)
          # Should parse client request here
      
          # Send multipart header
          client.send("HTTP/1.1 200 OK\r\n" \
                      "Server: OpenMV\r\n" \
                      "Content-Type: application/json\r\n" \
                      "Cache-Control: no-cache\r\n" \
                      "Pragma: no-cache\r\n\r\n")
      
          # FPS clock
          clock = time.clock()
      
          # Start streaming images
          # NOTE: Disable IDE preview to increase streaming FPS.
      
          clock.tick()
      
          img = sensor.snapshot()
      
          # default settings just do one detection... change them to search the image...
          for obj in net.classify(img, min_scale=1.0, scale_mul=0.8, x_overlap=0.5, y_overlap=0.5):
              #print("**********\nPredictions at [x=%d,y=%d,w=%d,h=%d]" % obj.rect())
              img.draw_rectangle(obj.rect())
              # This combines the labels and confidence values into a list of tuples
              predictions_list = list(zip(labels, obj.output()))
      
              for i in range(len(predictions_list)):
                  #print("%s = %f" % (predictions_list[i][0], predictions_list[i][1]))
                  a=obj.output()[0]
                  b=obj.output()[1]
                  c=obj.output()[2]
                  d=obj.output()[3]
                  f=obj.output()[4]
                  g=obj.output()[5]
                  if a>0.95:
                      h=1
                      print(h)
          client.send(json.dumps(h))
          client.close()
      
      while (True):
          # Create server socket
          s = usocket.socket(usocket.AF_INET, usocket.SOCK_STREAM)
          try:
              # Bind and listen
              s.bind([HOST, PORT])
              s.listen(5)
      
              # Set server socket timeout
              # NOTE: Due to a WINC FW bug, the server socket must be closed and reopened if
              # the client disconnects. Use a timeout here to close and re-create the socket.
              s.settimeout(3)
              response(s)
          except OSError as e:
              s.close()
              print("socket error: ", e)
              #sys.print_exception(e)
      

      0_19.png



    • 在73行:img = sensor.snapshot()下面,添加一句h=0



    • @kidswong999
      我加了那个可是现在的问题就是那个196.168.1.1都进不去



    • @kidswong999 我感觉我这个模型训练和这个WiFi传输没有加好,还有一个问题就是我这个程序运行起来没几分钟摄像头就不动了,就像卡住了一样,但是不报错



    • 你的程序是,每次访问才采集和运行一次。



    • @kidswong999 那我需要怎么改才能像那个传输小球坐标一样一直传呢



    • @k5r1 传输小球坐标,也是访问一次识别一次。你可以写一个js,每秒循环访问。



    • @kidswong999 不太懂应该怎么写啊 关键是现在我这个代码就是那个网站都进不去水为什么呢