Inquiry about the Dataset and some metrics about basketballgan HOT 6 CLOSED

@chychen Thank you for your reply, I am trying to calculate the MAE and RMSE on generated data to compare with some models of mine that use the same metrics.

I would do that either on your code directly or by extracting the generated data and calculating these metrics separately so I was wondering if that's doable somehow.

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Hi @ahariri13 ,

thank you for being interested in our work.

50Real.npy -> real play, containing both offensive and defensive trajectories of an entire play..
50Seq.npy -> real offensive strategies, containing only offensive strategies drawn by basketball coach.

why would you like to calculate the MAE and RMSE on generated data?
if you mean how to train a GAN, we use Earth Moving Distance (W-distance) to train our GAN model, I will refer you to WGAN and Spectral Norm papers.

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@chychen Actually, one way to solve my problem is if I could test the trained model by feeding it with initial positions and obtain the generated trajectories' plots and xy coordinates (As was done in the video). Is it possible to do that ?

Thanks in advance

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@ahariri13
You should feed offense strategies(a sequence) rather than initial points.

you might be interested in the branch “gui“. (somehow buggy but it is runnable.) it is the GUI interface in the demo videos.

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@chychen thanks a lot for your help. i ran the GUI, and got the 'output.npy' and 'points.npy' arrays.
'points.npy' is clearly the trajectories that I drew on the left screen, but 'output.npy' is of shape (100,10,74,28) in my case. I know already that 10 refers to 10 players, but what do the other components indicate ?

Sorry for my numerous questions.

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Dear @ahariri13 ,

I think 100 means it sample 100 results with diff latent code.
10 means 10 conditions (offense strategies)
74 means number of frames
28 means 10 players xy (20) + 1 ball xy (2) + who own the ball in one-hot format (6)

(sorry that the code written by students is messy and it won't be maintained anymore.

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