I'm new here, dumb questions

How can I compete if I don’t have infrastructure, only google colab ? is there another option ?

Thank you :slight_smile:

Hi @diegoto,

Welcome! Can you elaborate on what you mean by not having infrastructure? Does this mean you don’t have access to a GPU (besides Google Colab), or you don’t have a machine that you can use to test your submission using the Docker container?

Having access to a GPU is not required in order to make a submission. You may be able to develop your solution in Google Colab and then copy your files into a zip file to submit on the platform. Note that you are not required to submit the code component of the submission (main.py script) in order to have your submission scored, although this is required before the end of Phase 1 in order to be prize-eligible. If it makes things easier, you could just submit the .csv for the Matching Track, or .npz descriptors for the Descriptor Track.

Having a machine with at least 12GB of free space and the other prerequisites installed will make it much easier to test your solution locally, although in theory you could do without it.

If you let us know more about what resources are available to you, perhaps we or other participants can provide more ideas.


Hi @mike-dd,

Yes, my local machine is very useless and google colab does not support docker. Also, google colab does not have enough space in disk. What can I do to compete? I have tried using subsets for dataset and tricks for docker on google colab but it is very tiring, I have not achieved anything.

Thank you for your help,


Hi @diegoto,

Sorry for the slow reply during the holidays here.

Also, google colab does not have enough space in disk. What can I do to compete?

Have you tried uploading competition data to Google Drive and mounting that onto the Google Colab virtual machine? I have not personally done this but it seems like it should work. See docs here.

My other suggestion would be to focus initially on producing a submission with the prediction csv or descriptor npz files (for the matching or descriptor tracks, respectively). Don’t worry about the main.py script for now – you can get to this later once you’re satisfied with the rest of the submission.

I hope this helps. If other participants have used Google Colab for this or other competitions, please feel free to add your own comments.