------------
status: published
title: Brainwash
desc: Brainwash is a dataset of people from webcams the Brainwash Cafe in San Francisco being used to train face detection algorithms
subdesc: Brainwash dataset includes 11,918 images of people getting coffee at the Brainwash cafe during 2014
caption: An sample image from the Brainwash dataset used for training face detection algorithms for surveillance. License: Open Data Commons Public Domain Dedication (PDDL)
slug: brainwash
image: assets/background.jpg
published: 2019-2-23
updated: 2019-2-23
authors: Adam Harvey
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### Statistics
+ Collected: 2014
+ Published: 2015
+ Location: 1122 Folsom Street San Franscisco
+ Images: 11,917
+ Faces: 91,146
+ Created by: Stanford Department of Computer Science
+ Funding: Max Planck Center for Visual Computing and Communication
+ Resolution: 640x480px
+ Origin: Angelcam IP Cam
+ Purpose: Training face detection
- more info1
- more info2
- more info3
## Brainwash Dataset
*Brainwash* is a face detection dataset created from the Brainwash Cafe's livecam footage. The stream is It was published in 2015 by researchers at the Stanford University and has been used 1122 Folsom Street | USA
The photos were collected on
- Oct 27, 2014
- Nov 11, 2014
- Nov 245, 2017
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{% include 'map.html' %}
## Supplementary Information for Brainwash Dataset
{% include 'citations.html' %}
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RESEARCH below this line
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The file is 4.1GB
- add sha256 hash
- the images were taken from Dropcam which was runnign on https://www.angelcam.com/ "Angelcam’s Real-time Surveillance takes the weight of keeping your home or business secure off your shoulders."
> This package contains the "Brainwash" dataset. The dataset consists of images capturing the everyday life of a busy downtown cafe and is split into the following subsets:
> training set: 10769 with 81975 annotated people
> validation set: 500 images with 3318 annotated people
> test set: 500 images with 5007 annotated people
> Bounding box annotations are provided in a simple text file format. Each line in the file contains
image name followed by the list of annotation rectangles in the \[xmin, ymin, max, ymax\] format.
> We refer to the following arXiv submission for details on the dataset and the evaluation procedure:
http://arxiv.org/abs/1506.04878