NIRtoNDVI_JPGInputOnly.py

# -*- coding: utf-8 -*-
"""
Created on Mon May 25 02:34:05 2020

@author: cosmi
"""


"""
Experimental Vegetation Index Mapping program using DJI Mavic 2 Pro
JPEG 16-bit combo images taken using InfraBlue Filter

%(c)-J. Campbell MuonRay Enterprises 2019
This Python script was created using the Spyder Editor

"""

import warnings
warnings.filterwarnings('ignore')
from scipy import misc
import imageio
import numpy as np
from matplotlib import pyplot as plt  # For image viewing

#!/usr/bin/python
import getopt
import sys

import matplotlib.pyplot as plt
from matplotlib import colors
from matplotlib import ticker
from matplotlib.colors import LinearSegmentedColormap

#dng reading requires libraw to work

# Open an image
image = misc.imread('PANO0003.jpg')

# Get the red band from the rgb image, and open it as a numpy matrix
#NIR = image[:, :, 0]
         
#ir = np.asarray(NIR, float)


ir = (image[:,:,0]).astype('float')


# Get one of the IR image bands (all bands should be same)
#blue = image[:, :, 2]

#r = np.asarray(blue, float)

r = (image[:,:,2]).astype('float')


# Create a numpy matrix of zeros to hold the calculated NDVI values for each pixel
ndvi = np.zeros(r.size)  # The NDVI image will be the same size as the input image

# Calculate NDVI
ndvi = np.true_divide(np.subtract(ir, r), np.add(ir, r))


# Display the results
output_name = 'InfraBlueNDVI3.jpg'

#a nice selection of grayscale colour palettes
cols1 = ['blue', 'green', 'yellow', 'red']
cols2 =  ['gray', 'gray', 'red', 'yellow', 'green']
cols3 = ['gray', 'blue', 'green', 'yellow', 'red']

cols4 = ['black', 'gray', 'blue', 'green', 'yellow', 'red']

def create_colormap(args):
    return LinearSegmentedColormap.from_list(name='custom1', colors=cols3)

#colour bar to match grayscale units
def create_colorbar(fig, image):
        position = fig.add_axes([0.125, 0.19, 0.2, 0.05])
        norm = colors.Normalize(vmin=-1., vmax=1.)
        cbar = plt.colorbar(image,
                            cax=position,
                            orientation='horizontal',
                            norm=norm)
        cbar.ax.tick_params(labelsize=6)
        tick_locator = ticker.MaxNLocator(nbins=3)
        cbar.locator = tick_locator
        cbar.update_ticks()
        cbar.set_label("NDVI", fontsize=10, x=0.5, y=0.5, labelpad=-25)

fig, ax = plt.subplots()
image = ax.imshow(ndvi, cmap=create_colormap(colors))
plt.axis('off')

create_colorbar(fig, image)

extent = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
fig.savefig(output_name, dpi=600, transparent=True, bbox_inches=extent, pad_inches=0)
        # plt.show()