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I am trying to use Xcessiv to an image classification project (together with Keras or PyTorch). By reading the walkthrough, I found that I have to pass the entire dataset as a (X, y) tuple. This is unfeasible for a large image dataset. How can I outcome this problem?
One solution that I thought about was to pass image paths as the X, and let fit load the data lazily. Is this the best approach?
PS: Thanks for creating and maintaining Xcessiv!
The text was updated successfully, but these errors were encountered:
Hi @fabioperez, unfortunately I built Xcessiv without deep learning/image processing in mind. It is certainly not feasible to use Xcessiv with the large amounts of data necessary for deep learning (which are usually passed in to a neural network as batches, anyway).
Also, you give me too much credit. While I built Xcessiv, I certainly haven't had the time to maintain it in the last year, and I don't see that changing soon. :(
I am trying to use Xcessiv to an image classification project (together with Keras or PyTorch). By reading the walkthrough, I found that I have to pass the entire dataset as a
(X, y)
tuple. This is unfeasible for a large image dataset. How can I outcome this problem?One solution that I thought about was to pass image paths as the
X
, and letfit
load the data lazily. Is this the best approach?PS: Thanks for creating and maintaining Xcessiv!
The text was updated successfully, but these errors were encountered: