Quickly view satellite imagery, hyperspectral imagery, and machine learning image outputs directly i...
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bv is a small tool to quickly view high-resolution multi-band imagery directly in your iTerm 2. It was designed for visualising very large images located on a remote machine over a low-bandwidth connection. It subsamples and compresses the image sends it over the wire as a base64-encoded PNG (hence the name "bv") that iTerm 2 inlines in your terminal.
Here are a number of examples that show how this tool can be used.
Display a 3.5 billion pixel single-band image (3.3GB) using only 467KB over a SSH connection.
Display a six-band image (7.2GB) using only 1.1MB over a SSH connection. Here, we put bands 5-4-3 into the RGB channels using
-b 5 -b 4 -b 3(ordering matters) and set the width of the output image to be 600 pixels using
You can also specify a single band to display (e.g.,
You can subset images using
gdal_translatesyntax which is
-srcwin xoff yoff xsize ysize. For example, only displaying a small 1000x1000 area of the same large image above.
This allows you to quickly identify regions of your image and then paste the same options into
gdal_translateto complete your desired workflow. For example:
remote$ gdal_translate tasmania-2014.tif -b 5 -b 4 -b 3 -srcwin 12000 11000 1000 1000 -of PNG -ot UInt16 -scale 0 4000 ~/out.png Input file size is 20000, 16000 0...10...20...30...40...50...60...70...80...90...100 - done. remote$
Sometimes you might have a single-band image that only contains classes (integers). Different color maps can be applied to these single-band images using the
-cmoption and any choice from matplotlib's colormaps.
The bv tool can read from URLs (see the Trump image above). It can also parse URLs on
stdin, this allows you to do things like this to quicky display available Landsat images roughly over Dubai.
remote$ landsat search --lat 25 --lon 55 --latest 3 | bv -urls -
Filenames can be read from
stdin. For example:
ls -1 *.tif | bv -w 100 -
The level of compression can be changed using the
If your bands are located in seperate images then you can stack them and display them in the RGB channels using
bv -stack RED.tif GREEN.tif BLUE.tif
There is also the
-revstackoption to do it in reverse order.
The subsampling algorithm can be changed using the
-roption (same syntax as GDAL). The available subsamplings are: - Nearest - Average - Cubic Spline - Cubic - Mode - Lanczos - Bilinear
For single-band images, you can specify the color value to set as the alpha channel. This is sometimes useful for machine learning outputs where you want to not display certain classes. You can add multiple of these with different values.
The bv tool will display PDF, EPS, and PNG output inline with out any changes to those files. If you want to disable this behaviour you can pass the
-nopoption allow GDAL to subsample, etc.
You can save your default configuration by setting an alias in your
~/.profilefile. For example, I do:
alias bv='bv -w 800'
It is just a single-file script so all you'll need to do it put it in your
PATH. Dependencies are Python 3, GDAL 2, Numpy, Matplotlib, and iTerm 2. I've found that the best way to install these dependencies are: ```bash
brew install python3
pip3 install numpy matplotlib
brew install gdal --HEAD --without-python pip3 install gdal ```