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Author: MuonRay

NIRtoNDVI_JPGInputOnly.py

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+# -*- 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()