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AdamHillier / dataset_info.json
Created May 25, 2021 21:27
{
"citation": "@article{journals/corr/YuZSSX15,\n added-at = {2018-08-13T00:00:00.000+0200},\n author = {Yu, Fisher and Zhang, Yinda and Song, Shuran and Seff, Ari and Xiao, Jianxiong},\n biburl = {https://www.bibsonomy.org/bibtex/2446d4ffb99a5d7d2ab6e5417a12e195f/dblp},\n ee = {http://arxiv.org/abs/1506.03365},\n interhash = {3e9306c4ce2ead125f3b2ab0e25adc85},\n intrahash = {446d4ffb99a5d7d2ab6e5417a12e195f},\n journal = {CoRR},\n keywords = {dblp},\n timestamp = {2018-08-14T15:08:59.000+0200},\n title = {LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.},\n url = {http://dblp.uni-trier.de/db/journals/corr/corr1506.html#YuZSSX15},\n volume = {abs/1506.03365},\n year = 2015\n}",
"configDescription": "Images of category person",
"configName": "person",
"description": "Large scale images showing different objects from given categories like bedroom, tower etc.",
"downloadSize": "511754125920",
"location": {
"urls": [
"https://www.yf.
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AdamHillier / dataset_info.json
Created September 3, 2019 09:16
VOC2012 dataset_info json
{
"citation": "@misc{pascal-voc-2012,\n author = \"Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.\",\n title = \"The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2012 {(VOC2012)} {R}esults\",\n howpublished = \"http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html\"}\n",
"description": "This dataset contains the data from the PASCAL Visual Object Classes Challenge\n2012, a.k.a. VOC2012, corresponding to the Classification and Detection\ncompetitions.\nEach image contains a set of objects, from 20 different classes. The training\nand validation data has 11,530 images with 27,450 annotated objects.\nIn the Classification competition, the goal is to predict the set of labels\ncontained in the image, while in the Detection competition the goal is to\npredict the bounding box and label of each individual object.\n",
"location": {
"urls": [
"http://host.robots.ox.ac.uk/pascal/VOC/voc2012/"
]
},
"name": "voc2012",
"schema": {
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AdamHillier / How to validate a Gurobi academic license on Azure, GCP, EC2, etc.md
Last active February 14, 2019 18:10
How to activate a Gurobi academic license on Azure, GCP, EC2, etc

Gurobi academic licenses will only activate if the machine you are using is connected to a recognised academic network. If you want to use an academic license on a cloud machine, Gurobi recommend using a VPN connection to your university network. The following is much easier.

  1. SSH into your remote machine, forwarding the remote port 8822: ssh -R 8822:localhost:22 remote.host.com.
  2. From the remote, SSH back into your local machine, forwarding local port 8880, by: ssh -p 8822 -L 8880:apps.gurobi.com:80 localhost. For this to work you need to host an SSH server on your local machine; on MacOS you can turn on "Remote Login" in preferences to enable this.
  3. Now, open another connection to the remote, and run grbgetkey --http --port=8880 --server=localhost [your license key].
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AdamHillier / gist:50c2a3f260b82523d705
Last active August 29, 2015 14:07
HAB testing sketch
// RTTY-50 transmitted as 7-bit ascii, no parity, two stop bits.
// Connect GPS Power pin to 5V
// Connect GPS Ground pin to ground
// Connect GPS TX pin to Arduino RX1, RX2 or RX3
// Connect GPS RX pin to matching TX1, TX2 or TX3
#include <avr/io.h>
#include <avr/interrupt.h>
#include <Adafruit_GPS.h>