Follow Along!

Follow along: AlexNet Example

The program launching process along with parameter settings are all simplified and set up on the Jupyter Notebook Environment.

• Open the alexnet.ipynb jupyter notebook
• Import the necessary libraries
• With the input picture, execute the image recognition
• Terminate the task upon its completion

(The Jetson Board used for these examples are => Jetson Nano)

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• 02_2-1. Detect oranges in images - alexnet.ipynb

• Running the cell code

  Ctrl + Enter

• Import the subprocess module to run the example scripts (i.e. show.sh, kill.sh)

import subprocess

• Check the input image

  # Check the original image
  run_command_before = 'bash ~/ai_example/show.sh orange before'
  subprocess.call((run_command_before.split('\n')), shell=True)
  

  

• After confirming that the Input image is correct, terminate the image window

  # terminating the process
  kill_command_before = 'bash ~/ai_example/kill.sh display'
  subprocess.call((kill_command_before.split('\n')), shell=True)
  

• Guess what the image is!

  # Detect objects
  detect_command_orange = 'bash ~/ai_example/detect.sh orange_alexnet'
  subprocess.call((detect_command_orange.split('\n')), shell=True)
  

• Output the result on the image window

  # Check the detected image
  run_command_after = 'bash ~/ai_example/show.sh orange after alexnet'
  subprocess.call((run_command_after.split('\n')), shell=True)
  

  

• Terminate the process

  # terminating the process
  kill_command_after = 'bash ~/ai_example/kill.sh display'
  subprocess.call((kill_command_after.split('\n')), shell=True)