Project for tracking occupancy in Tel-Aviv parking lots.

Overview

Ahuzat Dibuk - Tracking occupancy in Tel-Aviv parking lots

main.py

This module was set-up to be executed on Google Cloud Platform. I run it every 15 minutes to collect more data into a file called data.feather, which I store on the cloud. It relies on the status that Ahuzat Ha-hof website has for (almost) every parking lot, which is either 'Free', 'Full', or 'Few places'.

plot.py

I execute this module on my personal computer, to download the data I've collected from the cloud and plot it.

What I learned from this

  1. You can use Google Cloud Platform pretty much for free. For three months you can even use expensive features with free credit that Google gives you.
  2. Google Cloud's interface for working with files (blobs) is terrible. It looks nothing like the Python interface for working with files, which made it more complicated than necessary to migrate my code from working locally to working in the cloud. This is 2022, why is this not a seamless transition?
  3. In an early stage of the project I mistakenly deleted multiple weeks worth of data when I messed around with the code. Backups are important :)
  4. I was a bit careless, and once the script was working on the cloud I just let it run. After some time I found out the machine had run out of memory (it had very little) and the script was crashing every time. The only problem is that I found out about this a full month after it stopped working, so I lost a lot of data I could have collected. Monitoring is also important! :)
Owner
Geva Kipper
Geva Kipper
A lossless neural compression framework built on top of JAX.

Kompressor Branch CI Coverage main (active) main development A neural compression framework built on top of JAX. Install setup.py assumes a compatible

Rosalind Franklin Institute 2 Mar 14, 2022
MatryODShka: Real-time 6DoF Video View Synthesis using Multi-Sphere Images

Main repo for ECCV 2020 paper MatryODShka: Real-time 6DoF Video View Synthesis using Multi-Sphere Images. visual.cs.brown.edu/matryodshka

Brown University Visual Computing Group 75 Dec 13, 2022
TalkingHead-1KH is a talking-head dataset consisting of YouTube videos

TalkingHead-1KH Dataset TalkingHead-1KH is a talking-head dataset consisting of YouTube videos, originally created as a benchmark for face-vid2vid: On

173 Dec 29, 2022
SeqFormer: a Frustratingly Simple Model for Video Instance Segmentation

SeqFormer: a Frustratingly Simple Model for Video Instance Segmentation SeqFormer SeqFormer: a Frustratingly Simple Model for Video Instance Segmentat

Junfeng Wu 298 Dec 22, 2022
Efficient training of deep recommenders on cloud.

HybridBackend Introduction HybridBackend is a training framework for deep recommenders which bridges the gap between evolving cloud infrastructure and

Alibaba 111 Dec 23, 2022
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.

#NeuralTalk Warning: Deprecated. Hi there, this code is now quite old and inefficient, and now deprecated. I am leaving it on Github for educational p

Andrej 5.3k Jan 07, 2023
Scale-aware Automatic Augmentation for Object Detection (CVPR 2021)

SA-AutoAug Scale-aware Automatic Augmentation for Object Detection Yukang Chen, Yanwei Li, Tao Kong, Lu Qi, Ruihang Chu, Lei Li, Jiaya Jia [Paper] [Bi

DV Lab 182 Dec 29, 2022
Geometric Algebra package for JAX

JAXGA - JAX Geometric Algebra GitHub | Docs JAXGA is a Geometric Algebra package on top of JAX. It can handle high dimensional algebras by storing onl

Robin Kahlow 36 Dec 22, 2022
iBOT: Image BERT Pre-Training with Online Tokenizer

Image BERT Pre-Training with iBOT Official PyTorch implementation and pretrained models for paper iBOT: Image BERT Pre-Training with Online Tokenizer.

Bytedance Inc. 435 Jan 06, 2023
Code release for the ICML 2021 paper "PixelTransformer: Sample Conditioned Signal Generation".

PixelTransformer Code release for the ICML 2021 paper "PixelTransformer: Sample Conditioned Signal Generation". Project Page Installation Please insta

Shubham Tulsiani 24 Dec 17, 2022
Global Rhythm Style Transfer Without Text Transcriptions

Global Prosody Style Transfer Without Text Transcriptions This repository provides a PyTorch implementation of AutoPST, which enables unsupervised glo

Kaizhi Qian 193 Dec 30, 2022
Official PyTorch implementation for paper Context Matters: Graph-based Self-supervised Representation Learning for Medical Images

Context Matters: Graph-based Self-supervised Representation Learning for Medical Images Official PyTorch implementation for paper Context Matters: Gra

49 Nov 23, 2022
Guiding evolutionary strategies by (inaccurate) differentiable robot simulators @ NeurIPS, 4th Robot Learning Workshop

Guiding Evolutionary Strategies by Differentiable Robot Simulators In recent years, Evolutionary Strategies were actively explored in robotic tasks fo

Vladislav Kurenkov 4 Dec 14, 2021
Library for time-series-forecasting-as-a-service.

TIMEX TIMEX (referred in code as timexseries) is a framework for time-series-forecasting-as-a-service. Its main goal is to provide a simple and generi

Alessandro Falcetta 8 Jan 06, 2023
Generative Handwriting using LSTM Mixture Density Network with TensorFlow

Generative Handwriting Demo using TensorFlow An attempt to implement the random handwriting generation portion of Alex Graves' paper. See my blog post

hardmaru 686 Nov 24, 2022
Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation

Auto-Seg-Loss By Hao Li, Chenxin Tao, Xizhou Zhu, Xiaogang Wang, Gao Huang, Jifeng Dai This is the official implementation of the ICLR 2021 paper Auto

61 Dec 21, 2022
MicroNet: Improving Image Recognition with Extremely Low FLOPs (ICCV 2021)

MicroNet: Improving Image Recognition with Extremely Low FLOPs (ICCV 2021) A pytorch implementation of MicroNet. If you use this code in your research

Yunsheng Li 293 Dec 28, 2022
Official Implementation for the "An Empirical Investigation of 3D Anomaly Detection and Segmentation" paper.

An Empirical Investigation of 3D Anomaly Detection and Segmentation Project | Paper Official PyTorch Implementation for the "An Empirical Investigatio

Eliahu Horwitz 55 Dec 14, 2022
Reinforcement Learning with Q-Learning Algorithm on gym's frozen lake environment implemented in python

Reinforcement Learning with Q Learning Algorithm Q learning algorithm is trained on the gym's frozen lake environment. Libraries Used gym Numpy tqdm P

1 Nov 10, 2021
Detector for Log4Shell exploitation attempts

log4shell-detector Detector for Log4Shell exploitation attempts Idea The problem with the log4j CVE-2021-44228 exploitation is that the string can be

Florian Roth 729 Dec 25, 2022