Closed KatrionaGoldmann closed 11 months ago
Updated the issue name to reflect the goal of replicating the Rolnick model exactly, with the same dataset they mention in READMEs.
Currently running using CPUs on baskerville, but then running into memory and/or time capacity issues.
New issue opened: Run models on baskerville with GPU/CUDA#17 to resolve improve the time capacity barrier
Much faster now using GPUs. Model is predicted to run to completion in around 2.5 hours, however we run into disk quota issues.
Model running in https://github.com/AMI-trap/on_device_classifier/pull/19
We can achieve similar accuracies using the increased number of images (aim for 1000 per species).
Models run for:
See https://github.com/AMI-trap/on_device_classifier/commit/6919a39cdbf900407dc605414067769a76084c04
Add pytorch based model to model sub-directory