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mathildecaron31 avatar mathildecaron31 commented on August 15, 2024 7

Hi, thanks for your interest !
Looking at the error it seems that you don't have enough data points in your dataset.
Indeed I manage to reproduce your error when I use less than 256 points.
Have a look at faiss pca code:
if n the number of points is higher or equal than the points dimension, d_in, then PCAMat is of dim d_in * d_in and the condition is True.
However, if n < d_in (which I assume is your case) then n needs to be higher than d_out for the condition to be True.

In a nutshell, it will throw the error if n < d_out, in your case it seems that your dataset size is less than 256.

It is a pure faiss error, so if I am not able to solve your issue you might post on faiss directly.

Hope it helps

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skasapis avatar skasapis commented on August 15, 2024 3

Hey, I had the same problem with a dataset of 100 pictures. In the code I am using the function sets the pca variable to be 256. You can drop this to lets say 50, and you will solve your problem as I did!

def preprocess_features(npdata, pca=256): #change this to 50
mat = faiss.PCAMatrix (ndim, pca, eigen_power=-0.5)
mat.train(npdata)

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juliangaal avatar juliangaal commented on August 15, 2024

Ah, great to hear, thanks a lot. Yes, my first test set is VERY small to just see if the whole pipeline works. Cheers

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BEFOURD avatar BEFOURD commented on August 15, 2024

you must let the number of your dataset n % batch_size == 0 or n % batch_size >= d_out

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