Tech-Xperience-Competition

This repository is part of a Philips' competition that requires the development of an A.I. algorithm to accurately classify different images.

How to Run the app

The procedure to run the application is very simple and straightforward. Nevertheless, the following steps are crucial:

1. The Docker image was uploaded using Git LFS (due to the github upload limit of only 100 mb). For that reason, and after downloading the repository using the option Download Zip, you will need to download the docker image individually. Just go inside Tech-Xperience-Competition/ML_App/Docker_Image/ and download the file mlappImage.tar individually (~950 mb). After downloading the .tar image, please be sure to place it inside the correct folder (Docker_Image/).

2. After you download the whole repository, insert the validation images inside the folder Tech-Xperience-Competition/ML_App/Input/.

3. Now you just need to run the batch file named Run_Docker_Image.bat which is in Tech-Xperience-Competition/ML_App/. (P.S.: This step basically executes some Docker commands. I am assuming you are running on a windows machine. If not, see the next section where I explain the docker commands necessary to execute the application).

4. Besides being displayed in the console application, the scored results will be written in a .txt file named ScoredOutput.txt in Tech-Xperience-Competition/ML_App/Output/.

Details on how to run the app

• You obviously need to have Docker Desktop installed on your machine to run the docker image.
• The batch file was made to make your life easier. But it assumes you are running on Windows. If not, here is an explanation of the commands in it:
  1. Load the image:
     • docker load --input Docker_Image/mlappImage.tar
  2. Run the image by creating a container and sending the validation images to it's respective place inside the container.
     • Windows CMD: docker run -it -v %cd%/Input/:/app/Input/ -t --name mlappcontainer mlapp
     • Ubuntu or Windows Powershell: docker run -it -v ${PWD}/Input/:/app/Input/ -t --name mlappcontainer mlapp
  3. Export the .txt output from the container to the respective folder in the host machine.
     • Windows CMD: docker cp mlappcontainer:/app/Output/ScoredOutput.txt %cd%/Output/ScoredOutput.txt
     • Ubuntu or Windows Powershell: docker cp mlappcontainer:/app/Output/ScoredOutput.txt ${PWD}/Output/ScoredOutput.txt

Aditional Info

The above steps should be enough for you to run the application flawlessly. However, if for some reason you are facing an issue, please contact me at any time. Even if you are just curious to know how I built this solution. I would be very glad to answer any question.
Thank you vey much!!

Author

I'm Isaac Reis, a ML/AI enthusiast from Portugal.
email: [email protected]
LinkedIn: https://www.linkedin.com/in/isaacisforreal/
YouTube chanel: https://www.youtube.com/channel/UC1vFQvk1dnhsh8Xon6tJhqw?view_as=subscriber