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I'm running dp2coor.py on the DeepFashion high resolution test data as instructed in Dataset and Downloads. However, it takes a long time (>20 seconds) to process each image. I believe it is because scipy.interpolate.griddata is slow on large matrices.
Is this expected behavior from dp2coor.py, and is there a way to speed it up? It would take an exorbitantly long time to process the training data at my current rate. Thank you.
The text was updated successfully, but these errors were encountered:
@1702609 I remember making two changes. First, I implemented a faster griddata, but I'm afraid you'll need to do that yourself as I cannot share my code either.
The second change also speeds up the code a lot; however, it might not be the best fit for your dataset. Change line 110 of dpcoor.py to the following:
Hello,
I'm running dp2coor.py on the DeepFashion high resolution test data as instructed in Dataset and Downloads. However, it takes a long time (>20 seconds) to process each image. I believe it is because
scipy.interpolate.griddata
is slow on large matrices.Is this expected behavior from dp2coor.py, and is there a way to speed it up? It would take an exorbitantly long time to process the training data at my current rate. Thank you.
The text was updated successfully, but these errors were encountered: