Tutorial
Table Of Contents
- 1. Premise
- 2. Raspberry Pi System Installation and Developmen
- 3 Log In to The Raspberry Pi and Install The App
- 4 Assembly and Precautions
- 5 Controlling Robot via WEB App
- 6 Common Problems and Solutions(Q&A)
- 7 Set The Program to Start Automatically
- 8 Remote Operation of Raspberry Pi Via MobaXterm
- 9 How to Control WS2812 RGB LED
- 10 How to Control The Servo
- 11 How to Control DC Motor
- 12 Ultrasonic Module
- 13 Line Tracking
- 14 Make A Police Light or Breathing Light
- 15 Real-Time Video Transmission
- 16 Automatic Obstacle Avoidance
- 17 Why OpenCV Uses Multi-threading to Process Vide
- 18 OpenCV Learn to Use OpenCV
- 19 Using OpenCV to Realize Color Recognition and T
- 20 Machine Line Tracking Based on OpenCV
- 21 Create A WiFi Hotspot on The Raspberry Pi
- 22 Install GUI Dependent Item under Window
- 23 How to Use GUI
- 24 Control The WS2812 LED via GUI
- 25 Real-time Video Transmission Based on OpenCV
- 26 Use OpenCV to Process Video Frames on The PC
- 27 Enable UART
- 28 Control Your AWR with An Android Device
- Conclusion
96
for frame in frames_iterator:
BaseCamera.frame = frame
BaseCamera.event.set() # send signal to clients
time.sleep(0)
# if there hasn't been any clients asking for frames in
# the last 10 seconds then stop the thread
if time.time() - BaseCamera.last_access > 10:
frames_iterator.close()
print('Stopping camera thread due to inactivity.')
break
BaseCamera.thread = None
●When you use the follow-up tutorial to develop a certain OpenCV related function, you only need to put
the corresponding camera_opencv.py in the same folder as this app.py and base_camera.py, and then run it in
the Raspberry Pi console just app.py.
● Open the browser with a device on the same local area network as the Raspberry Pi, enter the IP
address of the Raspberry Pi in the address bar, and access port 5000. The address is shown in the following
example:
192.168.3.161:5000