Computer Vision News - April 2018

First we must zip all the files in the site-packages folder. You can see the Numpy and OpenCV installations, our code file lambda_file.py , the image file watch.jpg and a number of less important files. In our case the folder looks like this: When we upload the file -- we must specify what file to run, and which function in the file to call -- in our case lambda_file.handler_name ; under Code entry type we select upload a .ZIP file , and under Handler we select the name of the file we previously created and the function we want to run -- lambda_file.handler_name . Once we have successfully uploaded, we can return to the AWS Console and press Test to see the results of running the function. 5. Ongoing remote code development using the Cloud9 work environment Once you’ve uploaded your basic code we can continue its development remotely. To do this, we go back to the AWS Console and select Cloud9 , and select Create Environment , leaving all options at their default values. To import your code to Cloud9, pick the right-hand tab AWS Resources , then under Remote function double-click the name of the function you wish to edit -- this will open a pop-up window where you should press Import . The code is ready to be edited now. Once you’re done editing, select Local Functions on the side menu, from there go to lambdaCVN1 (by right-button clicking it) and in the drop-down menu select Deploy , as can be seen below: 15 Tool Computer Vision News Computer Vision on Amazon Cloud