geophotos 0.21

A package to pull, plot, and analyze coordinates from photos.

GeoPhotos is a package to pull, analyze, and plot coordinates from photos.

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What is GeoPhotos?

GeoPhotos is a Python library designed to make it easy to pull coordinates from photos, analyze them in order to obtain useful information, and plot them on a map.

Main features

An overview of some of the major features of GeoPhotos are as follows:

• Extract metadata (timestamp, coordinates, etc.) from one or more files, and write to a csv file if desired
• Plot coordinate data on a fully customizable heatmap, including markers, tooltips, layer control, and more
• Analyze coordinate data to determine unique countries, most common countries, and more
• Highlight certain countries on the heatmap easily and painlessly
• Save the map to an html file for reference or for use with web development frameworks such as flask
• Open the html file directly from the code for debugging

How to get it

Dependencies

Currently, the following packages are required:

• pillow
• webbrowser
• folium
• osgeo
• geopandas

There are plans to make certain packages, such as geopandas, optional due to how difficult they are to install properly.

Installation

Assuming you've already got the dependencies covered, you can use pip to install this package:

pip install geophotos

However, you will most likely run into problems doing it this way. Unfortunately, I have tried and failed to overcome these obstacles myself. My recommendation is to install geopandas using Anaconda/conda, and then pip install it into your current environment:

conda install geopandas
pip install geophotos

This should handle all of the dependencies for you, although you still might run into some issues (I sure did!).

Updating

To update geophotos to the latest version, simple use the command:

pip install --upgrade geophotos

Example usage

One of the main reasons I made this package was to pull GPS information from the pictures in my iCloud library, then plot them on a map. Skipping the pulling of the coordinates for simplicity's sake, the following code does the following:

1. Read latitudes and longitudes from a csv file
2. Generate a heatmap using this coordinate data
3. Add a marker that marks my hometown
4. Analyze the data and determine which countries I've visited
5. Highlight only the countries I've been to on a separate layer
6. Save the map as an html file and open it in a web browser

The html file is completely interactive, and I hope to eventually use it on my personal website! Unfortunately, I had to post a still image of the map because Github doesn't like cool things.

import geophotos as gp

# Read coordinate data from csv
data = gp.coordinates_from_csv(r'coordinates.csv', 2, 3)
# Initialize the Map object
nys_center = [42.965000, -76.016667]
heatmap = gp.Map(location=nys_center, zoom_start=7)
# Feed the Heatmap object the coordinates
heatmap.coordinates = data
# Create the heatmap
heatmap.create_heatmap(max_zoom=10, min_opacity=0.05, radius=13, blur=25,
                       name='Photo Heatmap')
# Add a marker to the heatmap
hamburg_ny = [42.715746, -78.829416]
heatmap.add_marker(location=hamburg_ny,
                   tooltip='<strong>Hamburg, NY</strong><br>Hometown')
# Analyze the data to determine which countries are unique
analyzer = gp.Analyzer(data)
unique_countries = analyzer.unique_countries(),
# Use the data to determine which countries to highlight
border_layer = gp.BorderLayer(unique_countries, name='Countries Visited')
border_layer.add_to(heatmap)
# Add layer control functionality to the map
heatmap.add_layer_control()
# Save the heatmap and open it in a browser
heatmap.save_html('sample.html', open_html=True)

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Authors

• Jake Brehm - Initial Work - Email | Github | LinkedIn