What is MapReader?

MapReader is an end-to-end computer vision (CV) pipeline for exploring and analyzing images at scale.

What is unique about MapReader?

MapReader is based on the ‘patchwork method’ in which whole map images are sliced into a grid of squares or ‘patches’:

../_images/patchify.png

This unique way of pre-processing map images enables the use of image classification to identify visual features within maps, in order to answer important research questions.

What is ‘the MapReader pipeline’?

The MapReader pipeline consists of a linear sequence of tasks:

../_images/pipeline_explained.png

Together, these tasks can be used to train a computer vision (CV) classifier to recognize visual features within maps and identify patches containing these features across entire map collections.

What kind of visual features can MapReader help me identify?

In order to train a CV classifier to recognize visual features within your maps, your features must have a homogeneous visual signal across your map collection (i.e. always be represented in the same way).

What are the inputs and outputs of each stage in the MapReader pipeline?

Download

../_images/in_out_download.png

Load

../_images/in_out_load.png

Annotate

../_images/in_out_annotate.png

Classify (Train and Predict)

../_images/in_out_classify.png