| This is a little assignment I had to write in high school my senior year. | |
| I had recently received a speeding ticket if I remember correctly. | |
| By the way, Mr. Welsh was the teacher who through some quirk of fate was in charge of detentions. | |
| This is ironic because he was a pretty nice guy and not a good disciplinarian. | |
| “To speed or not to speed – that is the question: | |
| Whether ‘tis nobler in the mind to suffer | |
| The agony of a detention with Mr. Welsh | |
| Or to disregard the law and drive 70 mph |
| http://dl.allaboutbirds.org/merlin---computer-vision--terms-of-use?submissionGuid=8cadb309-30fc-44f5-8871-489e1eed9f06 | |
| had to sign up. they have strict requirements on how to cite them. |
| what is fits? | |
| https://photographingspace.com/how-to-use-fits/ | |
| how to load fits data- | |
| https://www.spacetelescope.org/projects/fits_liberator/ | |
| where to find fits datasets | |
| http://arcoiris.ucsc.edu/candels/data_access/Latest_Release.html |
| { | |
| "description": "Crossing the curl with finite differences", | |
| "publication": "https://arxiv.org/pdf/1808.01531.pdf", | |
| "discriminator": | |
| { | |
| "class": "class:hypergan.discriminators.configurable_discriminator.ConfigurableDiscriminator", | |
| "defaults":{ | |
| "class": "class:hypergan.discriminators.dcgan_discriminator.DCGANDiscriminator", | |
| "activation": "lrelu", | |
| "initializer": "random_normal", |
| import imghdr | |
| import os | |
| #this script will scan every file in a directory and delete any that are not a valid image type that imghdr recognizes. | |
| #see https://docs.python.org/3.1/library/imghdr.html | |
| # The following image types are recognized, as listed below with the return value from what(): | |
| # | |
| # Value Image format | |
| # 'rgb' SGI ImgLib Files |
| { | |
| "description": "Crossing the curl with finite differences", | |
| "publication": "https://arxiv.org/pdf/1808.01531.pdf", | |
| "discriminator": | |
| { | |
| "class": "class:hypergan.discriminators.configurable_discriminator.ConfigurableDiscriminator", | |
| "defaults":{ | |
| "class": "class:hypergan.discriminators.dcgan_discriminator.DCGANDiscriminator", | |
| "activation": "lrelu", | |
| "initializer": "random_normal", |
tips on setting up a custom environment for hypergan
This guide requires Anaconda. Download and install Anaconda3 from:
https://www.anaconda.com/download/
Before you start anything with HyperGAN, you must install the CUDA libraries. If you don't have a CUDA GPU, I wouldn't recommend reading this guide further since this guide assumes you will be using a CUDA powered GPU.
Get cudnn here: https://developer.nvidia.com/cudnn
| run: | |
| $ ipcs -m | |
| and it should list a key owned by crawl. should be something like 0x12345678 | |
| example: | |
| ------ Shared Memory Segments -------- | |
| key shmid owner perms bytes nattch status | |
| 0x52147880 0 crawl 644 33648 1 |
| /* | |
| * Copyright (C) 2009 flakes @ EFNet | |
| * New match logic by Gm4n @ freenode | |
| * Version 1.0 (2012-08-19) | |
| * | |
| * This program is free software; you can redistribute it and/or modify it | |
| * under the terms of the GNU General Public License version 2 as published | |
| * by the Free Software Foundation. | |
| */ |
