Hide screen when boss is approaching.

Last update: Jan 07, 2023

Overview

BossSensor

Hide your screen when your boss is approaching.

Demo

The boss stands up. He is approaching.

When he is approaching, the program fetches face images and classifies the image.

If the image is classified as the Boss, it will monitor changes.

Requirements

WebCamera
Python3.5
OSX
Anaconda
Lots of images of your boss and other person image

Put images into data/boss and data/other.

Usage

First, Train boss image.

$ python boss_train.py

Second, start BossSensor.

$ python camera_reader.py

Install

Install OpenCV, PyQt4, Anaconda.

conda create -n venv python=3.5
source activate venv
conda install -c https://conda.anaconda.org/menpo opencv3
conda install -c conda-forge tensorflow
pip install -r requirements.txt

Change Keras backend from Theano to TensorFlow.

Licence

MIT

Author

Hironsan

Owner

Hiroki Nakayama

OSS developer | Interested in Natural Language Processing

GitHub Repository http://ahogrammer.com/2016/11/15/deep-learning-enables-you-to-hide-screen-when-your-boss-is-approaching/

CLEAR algorithm for multi-view data association

CLEAR: Consistent Lifting, Embedding, and Alignment Rectification Algorithm The Matlab, Python, and C++ implementation of the CLEAR algorithm, as desc

30 Jan 02, 2023

BBScan py3 - BBScan py3 With Python

BBScan_py3 This repository is forked from lijiejie/BBScan 1.5. I migrated the fo

12 Dec 30, 2022

(CVPR 2022) Pytorch implementation of "Self-supervised transformers for unsupervised object discovery using normalized cut"

(CVPR 2022) TokenCut Pytorch implementation of Tokencut: Self-supervised Transformers for Unsupervised Object Discovery using Normalized Cut Yangtao W

200 Jan 02, 2023

Deep Learning Theory

Deep Learning Theory 整理了一些深度学习的理论相关内容，持续更新。 Overview Recent advances in deep learning theory 总结了目前深度学习理论研究的六个方向的一些结果，概述型，没做深入探讨(2021)。 1.1 complexity

103 Jan 04, 2023

A universal memory dumper using Frida

Fridump Fridump (v0.1) is an open source memory dumping tool, primarily aimed to penetration testers and developers. Fridump is using the Frida framew

551 Jan 07, 2023

An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi

MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu

141 Jan 07, 2023

Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.

Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa

48 Nov 09, 2022

Fast and customizable reconnaissance workflow tool based on simple YAML based DSL.

Fast and customizable reconnaissance workflow tool based on simple YAML based DSL, with support of notifications and distributed workload of that work

3 Mar 11, 2022

Deep-Learning-Image-Captioning - Implementing convolutional and recurrent neural networks in Keras to generate sentence descriptions of images

Deep Learning - Image Captioning with Convolutional and Recurrent Neural Nets ========================================================================

23 Apr 06, 2022

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

Translated in 🇰🇷 Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on

8.7k Dec 31, 2022

Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

flownet2-pytorch Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. Multiple GPU training is supported, a

2.8k Dec 27, 2022

Husein pet projects in here!

project-suka-suka Husein pet projects in here! List of projects mysejahtera-density. Generate resolution points using meshgrid and request each points

47 Dec 09, 2022

x-transformers-paddle 2.x version

x-transformers-paddle x-transformers-paddle 2.x version paddle 2.x版本 https://github.com/lucidrains/x-transformers 。 requirements paddlepaddle-gpu==2.2

7 Dec 08, 2022

MDETR: Modulated Detection for End-to-End Multi-Modal Understanding

MDETR: Modulated Detection for End-to-End Multi-Modal Understanding Website • Colab • Paper This repository contains code and links to pre-trained mod

770 Dec 28, 2022

TensorFlow ROCm port

Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a

622 Jan 09, 2023

MRI reconstruction (e.g., QSM) using deep learning methods

deepMRI: Deep learning methods for MRI Authors: Yang Gao, Hongfu Sun This repo is devloped based on Pytorch (1.8 or later) and matlab (R2019a or later

17 Dec 18, 2022

Model-based Reinforcement Learning Improves Autonomous Racing Performance

Racing Dreamer: Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars In this work, we propose to learn a racing contro

38 Dec 06, 2022

A PyTorch Implementation of the Luna: Linear Unified Nested Attention

Unofficial PyTorch implementation of Luna: Linear Unified Nested Attention The quadratic computational and memory complexities of the Transformer’s at

32 Nov 07, 2022

Crowd-Kit is a powerful Python library that implements commonly-used aggregation methods for crowdsourced annotation and offers the relevant metrics and datasets

Crowd-Kit: Computational Quality Control for Crowdsourcing Documentation Crowd-Kit is a powerful Python library that implements commonly-used aggregat

125 Dec 30, 2022

This repo includes the supplementary of our paper "CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels"

Supplementary Materials for CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels This repository includes all supplementary mater

0 Jan 05, 2022