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Downloading pretrained weights (~140MB) seven times for every subject...can we have a better solution #259

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wang-bingh opened this issue Oct 24, 2023 · 0 comments

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@wang-bingh
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wang-bingh commented Oct 24, 2023

When we solve the Errors like
"EOFError: Ran out of input"
"RuntimeError: unexpected EOF, expected 31322553 more bytes. The file might be corrupted."
"requests.exceptions.SSLError: HTTPSConnectionPool(host='zenodo.org', port=443): Max retries exceeded with url: /record/3518331/files/best_weights_ep143.npz?download=1 (Caused by SSLError(SSLZeroReturnError(6, 'TLS/SSL connection has been closed (EOF) (ssl.c:1129)')))"
We often use----“rm -r ~/.tractseg”
**This does solve the problem of reporting errors,but we have to download same pretrained_weights
(~140MB)data for different subjects frequently. When we treat one subject, we have to download different_pretrained_weights(~140MB)_data seven times (aboat 980M):**
__Loading weights from: /home/w/.tractseg/pretrained_weights_tract_segmentation_v3.npz
Downloading pretrained weights (~140MB) ...

Loading weights from: /home/w/.tractseg/pretrained_weights_endings_segmentation_v4.npz
Downloading pretrained weights (~140MB) ...

Loading weights from: /home/w/.tractseg/pretrained_weights_peak_regression_part1_v2.npz
Downloading pretrained weights (~140MB) ..

Loading weights from: /home/w/.tractseg/pretrained_weights_peak_regression_part1_v2.npz
Downloading pretrained weights (~140MB) ...

Loading weights from: /home/w/.tractseg/pretrained_weights_peak_regression_part2_v2.npz
Downloading pretrained weights (~140MB) ...

Loading weights from: /home/w/.tractseg/pretrained_weights_peak_regression_part3_v2.npz
Downloading pretrained weights (~140MB) ...

Loading weights from: /home/w/.tractseg/pretrained_weights_peak_regression_part4_v2.npz
Downloading pretrained weights (~140MB) ...__

In batch_TractSeg_data processing, this will consume significant network traffic, time and energy.
Can you optimize the program for optimal time and network traffic consumption? or can we have a better other solution for the problem.
Thank you.

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