Updated 19/10/2018
Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.
Updated 19/10/2018
Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.
So you've cloned somebody's repo from github, but now you want to fork it and contribute back. Never fear! | |
Technically, when you fork "origin" should be your fork and "upstream" should be the project you forked; however, if you're willing to break this convention then it's easy. | |
* Off the top of my head * | |
1. Fork their repo on Github | |
2. In your local, add a new remote to your fork; then fetch it, and push your changes up to it | |
git remote add my-fork git@github...my-fork.git |
class ImageBaseAug(object): | |
def __init__(self): | |
sometimes = lambda aug: iaa.Sometimes(0.5, aug) | |
self.seq = iaa.Sequential( | |
[ | |
# Blur each image with varying strength using | |
# gaussian blur (sigma between 0 and 3.0), | |
# average/uniform blur (kernel size between 2x2 and 7x7) | |
# median blur (kernel size between 3x3 and 11x11). | |
iaa.OneOf([ |
az vm create --resource-group bushi-RG1 \ | |
--name glm-bushi-2 --nics bushi-nic-2 \ | |
--size Standard_DS1_v2 --os-type Linux \ | |
--attach-os-disk glm-bushi-2 --attach-data-disks glm-bushi-disk-2 --plan-name linuxdsvmubuntu --plan-product linux-data-science-vm-ubuntu --plan-publisher microsoft-ads |
ls | parallel -n2000 mkdir {#}\;mv {} {#}
-n2000 takes 2000 arguments at a time and {#} is the sequence number of the job.
For FP, find a sweet point of confidence threshold that corresponds to X (X=0.3) mean FP/study, in order to predict the bboxes that are possible missings in GT.
Note : confidence threshold up -> mean FP/study down -> total FP down -> less time & effort, but can miss more good preds
For FN, find a sweet point of confidence threshold that corresponds to X (X=?) mean FN/study, in order to show the GTs that are not detected / badly detected by the model.
from subprocess import call | |
call(["nvidia-smi", "--format=csv", "--query-gpu=index,name,driver_version,memory.total,memory.used,memory.free"]) |
Git submodule: kézako ? (https://fr.wiktionary.org/wiki/qu%C3%A9saco#fr) On rajoute un dossier dans le repository parent qui est un autre repository git. Chaque nouveau commit du repo parent va désormais référencer un commit du repo inclus précis, pour garantir la cohérence de l’état permanent. Le commit de référence peut être sur n’importe quelle branche.
Attention
quand on revient à un état ancien (vieux commit du parent) il faut assurer la synchro en forçant la mise en cohérence du submodule.
Le submodule est dans un état particulier (detached HEAD), avant de commit dessus il faut s’assurer de ne pas être dans ce mode (checkout de la branche courante)
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