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I am not sure whether or not it is suitable to open a new issue to discuss the speed of Preprocessing.
I notice that the reprocessing speed is so fast. It outperforms around 10x times to my another preprocessing code on the same data. That's impressive. I am curious how do you achieve that. Is there anything you avoid to do in your functions?
The preprocessing stage include what happens in the data.py and train.py.
The text was updated successfully, but these errors were encountered:
Since you didn't mention which other pre-processing techniques you currently use, I can't really say why my code outperforms yours :).
Basically I use scipy and scikit-image libraries, and I guess it can perform even faster with OpenCV, but I can't offer any official benchmark for that claim.
I guess the function get_data might be the problem causes the performance issue, but I am not sure about that. Maybe need add timer for each function for testing. : )
I am not sure whether or not it is suitable to open a new issue to discuss the speed of Preprocessing.
I notice that the reprocessing speed is so fast. It outperforms around 10x times to my another preprocessing code on the same data. That's impressive. I am curious how do you achieve that. Is there anything you avoid to do in your functions?
The preprocessing stage include what happens in the
data.py
andtrain.py
.The text was updated successfully, but these errors were encountered: