Color correction plugin for rasterio

Overview

rio-color

Build Status Coverage Status

A rasterio plugin for applying basic color-oriented image operations to geospatial rasters.

Goals

  • No heavy dependencies: rio-color is purposefully limited in scope to remain lightweight
  • Use the image structure: By iterating over the internal blocks of the input image, we keep memory usage low and predictable while gaining the ability to
  • Use multiple cores: thanks to rio-mucho
  • Retain all the GeoTIFF info and TIFF structure: nothing is lost. A GeoTIFF input → GeoTIFF output with the same georeferencing, internal tiling, compression, nodata values, etc.
  • Efficient colorspace conversions: the intensive math is written in highly optimized C functions and for use with scalars and numpy arrays.
  • CLI and Python module: accessing the functionality as a python module that can act on in-memory numpy arrays opens up new opportunities for composing this with other array operations without using intermediate files.

Operations

Gamma adjustment adjusts RGB values according to a power law, effectively brightening or darkening the midtones. It can be very effective in satellite imagery for reducing atmospheric haze in the blue and green bands.

Sigmoidal contrast adjustment can alter the contrast and brightness of an image in a way that matches human's non-linear visual perception. It works well to increase contrast without blowing out the very dark shadows or already-bright parts of the image.

Saturation can be thought of as the "colorfulness" of a pixel. Highly saturated colors are intense and almost cartoon-like, low saturation is more muted, closer to black and white. You can adjust saturation independently of brightness and hue but the data must be transformed into a different color space.

animated

Examples

Sigmoidal

Contrast

sigmoidal_contrast

Bias

sigmoidal_bias

Gamma

Red

gamma_red

Green

gamma_green

Blue

gamma_blue

Saturation

saturation

Combinations of operations

combos

Install

We highly recommend installing in a virtualenv. Once activated,

pip install -U pip
pip install rio-color

Or if you want to install from source

git checkout https://github.com/mapbox/rio-color.git
cd rio-color
pip install -U pip
pip install -r requirements-dev.txt
pip install -e .

Python API

rio_color.operations

The following functions accept and return numpy ndarrays. The arrays are assumed to be scaled 0 to 1. In some cases, the input array is assumed to be in the RGB colorspace.

All arrays use rasterio ordering with the shape as (bands, columns, rows). Be aware that other image processing software may use the (columns, rows, bands) axis order.

  • sigmoidal(arr, contrast, bias)
  • gamma(arr, g)
  • saturation(rgb, proportion)
  • simple_atmo(rgb, haze, contrast, bias)

The rio_color.operations.parse_operations function takes an operations string and returns a list of python functions which can be applied to an array.

ops = "gamma b 1.85, gamma rg 1.95, sigmoidal rgb 35 0.13, saturation 1.15"

assert arr.shape[0] == 3
assert arr.min() >= 0
assert arr.max() <= 1

for func in parse_operations(ops):
    arr = func(arr)

This provides a tiny domain specific language (DSL) to allow you to compose ordered chains of image manipulations using the above operations. For more information on operation strings, see the rio color command line help.

rio_color.colorspace

The colorspace module provides functions for converting scalars and numpy arrays between different colorspaces.

>>> from rio_color.colorspace import ColorSpace as cs  # enum defining available color spaces
>>> from rio_color.colorspace import convert, convert_arr
>>> convert_arr(array, src=cs.rgb, dst=cs.lch) # for arrays
...
>>> convert(r, g, b, src=cs.rgb, dst=cs.lch)  # for scalars
...
>>> dict(cs.__members__)  # can convert to/from any of these color spaces
{
 'rgb': <ColorSpace.rgb: 0>,
 'xyz': <ColorSpace.xyz: 1>,
 'lab': <ColorSpace.lab: 2>,
 'lch': <ColorSpace.lch: 3>,
 'luv': <ColorSpace.luv: 4>
 }

Command Line Interface

Rio color provides two command line interfaces:

rio color

A general-purpose color correction tool to perform gamma, contrast and saturation adjustments.

The advantages over Imagemagick convert: rio color is geo-aware, retains the profile of the source image, iterates efficiently over interal tiles and can use multiple cores.

Usage: rio color [OPTIONS] SRC_PATH DST_PATH OPERATIONS...

  Color correction

  Operations will be applied to the src image in the specified order.

  Available OPERATIONS include:

      "gamma BANDS VALUE"
          Applies a gamma curve, brightening or darkening midtones.
          VALUE > 1 brightens the image.

      "sigmoidal BANDS CONTRAST BIAS"
          Adjusts the contrast and brightness of midtones.
          BIAS > 0.5 darkens the image.

      "saturation PROPORTION"
          Controls the saturation in LCH color space.
          PROPORTION = 0 results in a grayscale image
          PROPORTION = 1 results in an identical image
          PROPORTION = 2 is likely way too saturated

  BANDS are specified as a single arg, no delimiters

      `123` or `RGB` or `rgb` are all equivalent

  Example:

      rio color -d uint8 -j 4 input.tif output.tif \
          gamma 3 0.95, sigmoidal rgb 35 0.13


Options:
  -j, --jobs INTEGER              Number of jobs to run simultaneously, Use -1
                                  for all cores, default: 1
  -d, --out-dtype [uint8|uint16]  Integer data type for output data, default:
                                  same as input
  --co NAME=VALUE                 Driver specific creation options.See the
                                  documentation for the selected output driver
                                  for more information.
  --help                          Show this message and exit.

Example:

$ rio color -d uint8 -j 4 rgb.tif test.tif \
    gamma G 1.85 gamma B 1.95 sigmoidal RGB 35 0.13 saturation 1.15

screen shot 2016-02-17 at 12 18 47 pm

rio atmos

Provides a higher-level tool for general atmospheric correction of satellite imagery using a proven set of operations to adjust for haze.

Usage: rio atmos [OPTIONS] SRC_PATH DST_PATH

  Atmospheric correction

Options:
  -a, --atmo FLOAT                How much to dampen cool colors, thus cutting
                                  through haze. 0..1 (0 is none), default:
                                  0.03.
  -c, --contrast FLOAT            Contrast factor to apply to the scene.
                                  -infinity..infinity(0 is none), default: 10.
  -b, --bias FLOAT                Skew (brighten/darken) the output. Lower
                                  values make it brighter. 0..1 (0.5 is none),
                                  default: 0.15
  -d, --out-dtype [uint8|uint16]  Integer data type for output data, default:
                                  same as input
  --as-color                      Prints the equivalent rio color command to
                                  stdout.Does NOT run either command, SRC_PATH
                                  will not be created
  -j, --jobs INTEGER              Number of jobs to run simultaneously, Use -1
                                  for all cores, default: 1
  --co NAME=VALUE                 Driver specific creation options.See the
                                  documentation for the selected output driver
                                  for more information.
  --help                          Show this message and exit.
Owner
Mapbox
Mapbox is the location data platform for mobile and web applications. We're changing the way people move around cities and explore our world.
Mapbox
GetOSM is an OpenStreetMap tile downloader written in Python that is agnostic of GUI frameworks.

GetOSM GetOSM is an OpenStreetMap tile downloader written in Python that is agnostic of GUI frameworks. It is used with tkinter by ProjPicker. Require

Huidae Cho 3 May 20, 2022
Python project to generate Kerala's distrcit level panchayath map.

Kerala-Panchayath-Maps Python project to generate Kerala's distrcit level panchayath map. As of now, geojson files of Kollam and Kozhikode are added t

Athul R T 2 Jan 10, 2022
Get-countries-info - A python code that fetches data of any country

Country-info A python code getting countries information including country's map

CODE 2 Feb 21, 2022
Xarray backend to Copernicus Sentinel-1 satellite data products

xarray-sentinel WARNING: this product is a "technology preview" / pre-Alpha Xarray backend to explore and load Copernicus Sentinel-1 satellite data pr

B-Open 191 Dec 15, 2022
A Django application that provides country choices for use with forms, flag icons static files, and a country field for models.

Django Countries A Django application that provides country choices for use with forms, flag icons static files, and a country field for models. Insta

Chris Beaven 1.2k Jan 03, 2023
GebPy is a Python-based, open source tool for the generation of geological data of minerals, rocks and complete lithological sequences.

GebPy is a Python-based, open source tool for the generation of geological data of minerals, rocks and complete lithological sequences. The data can be generated randomly or with respect to user-defi

Maximilian Beeskow 16 Nov 29, 2022
Geocoding library for Python.

geopy geopy is a Python client for several popular geocoding web services. geopy makes it easy for Python developers to locate the coordinates of addr

geopy 3.8k Dec 30, 2022
WhiteboxTools Python Frontend

whitebox-python Important Note This repository is related to the WhiteboxTools Python Frontend only. You can report issues to this repo if you have pr

Qiusheng Wu 304 Dec 15, 2022
Get Landsat surface reflectance time-series from google earth engine

geextract Google Earth Engine data extraction tool. Quickly obtain Landsat multispectral time-series for exploratory analysis and algorithm testing On

Loïc Dutrieux 50 Dec 15, 2022
Python Data. Leaflet.js Maps.

folium Python Data, Leaflet.js Maps folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js

6k Jan 02, 2023
Calculate the area inside of any GeoJSON geometry. This is a port of Mapbox's geojson-area for Python

geojson-area Calculate the area inside of any GeoJSON geometry. This is a port of Mapbox's geojson-area for Python. Installation $ pip install area U

Alireza 87 Dec 14, 2022
Asynchronous Client for the worlds fastest in-memory geo-database Tile38

This is an asynchonous Python client for Tile38 that allows for fast and easy interaction with the worlds fastest in-memory geodatabase Tile38.

Ben 53 Dec 29, 2022
Digital Earth Australia notebooks and tools repository

Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and xarray

Geoscience Australia 335 Dec 24, 2022
Computer Vision in Python

Mahotas Python Computer Vision Library Mahotas is a library of fast computer vision algorithms (all implemented in C++ for speed) operating over numpy

Luis Pedro Coelho 792 Dec 20, 2022
WebGL2 powered geospatial visualization layers

deck.gl | Website WebGL2-powered, highly performant large-scale data visualization deck.gl is designed to simplify high-performance, WebGL-based visua

Vis.gl 10.5k Jan 08, 2023
Geocode rows in a SQLite database table

Geocode rows in a SQLite database table

Chris Amico 225 Dec 08, 2022
Search and download Copernicus Sentinel satellite images

sentinelsat Sentinelsat makes searching, downloading and retrieving the metadata of Sentinel satellite images from the Copernicus Open Access Hub easy

837 Dec 28, 2022
How to use COG's (Cloud optimized GeoTIFFs) with Rasterio

How to use COG's (Cloud optimized GeoTIFFs) with Rasterio According to Cogeo.org: A Cloud Opdtimized GeoTIFF (COG) is a regular GeoTIFF file, aimed at

Marvin Gabler 8 Jul 29, 2022
Replace MSFS2020's bing map to google map

English verison here 中文 免责声明 本教程提到的方法仅用于研究和学习用途。我不对使用、拓展该教程及方法所造成的任何法律责任和损失负责。 背景 微软模拟飞行2020的地景使用了Bing的卫星地图,然而卫星地图比较老旧,很多地区都是几年前的图设置直接是没有的。这种现象在全球不同地区

hesicong 272 Dec 24, 2022
This GUI app was created to show the detailed information about the weather in any city selected by user

WeatherApp Content Brief description Tools Features Hotkeys How it works Screenshots Ways to improve the project Installation Brief description This G

TheBugYouCantFix 5 Dec 30, 2022