Tiff images to numpy arrays

Question

import rasterio as rio
from rasterio.plot import show
from sklearn import cluster
import matplotlib.pyplot as plt
import numpy as np
import glob

for filepath in glob.iglob('./dengue3/*.tiff'):
    elhas_raster = rio.open(filepath)
    elhas_arr = elhas_raster.read() # read the opened image
    vmin, vmax = np.nanpercentile(elhas_arr, (5,95))  # 5-95% contrast stretch
    # create an empty array with same dimension and data type
    imgxyb = np.empty((elhas_raster.height, elhas_raster.width, elhas_raster.count), elhas_raster.meta['dtype'])
    # loop through the raster's bands to fill the empty array
    for band in range(imgxyb.shape[2]):
        imgxyb[:,:,band] = elhas_raster.read(band+1)
    #print(imgxyb.shape)
    # convert to 1d array
    img1d=imgxyb[:,:,:7].reshape((imgxyb.shape[0]*imgxyb.shape[1],imgxyb.shape[2]))
    #print(img1d.shape)

Above code I am using to read the tiff images in a folder and get the arrays. However, the output is -

ValueError: cannot reshape array of size 6452775 into shape (921825,12)

Images are 12 band. I tried using 12 in place of 7 in the above code, but the code doesnt execute. How do I resolve this? Thank you for your time.

Are you trying to reshape 7 bands, or just the 7th one? – Mark Setchell Nov 15 '21 at 22:31 — Mark Setchell, Nov 15 '21 at 22:31

score 0 · Answer 1 · answered Nov 15 '21 at 22:33

You have changed the size of the index you're trying to reshape, but not the reshape command parameter:

img1d=imgxyb[:,:,:7].reshape((imgxyb.shape[0]*imgxyb.shape[1],imgxyb.shape[2]))

This should be:

img1d=imgxyb[:,:,:7].reshape((imgxyb.shape[0]*imgxyb.shape[1],7))

Tiff images to numpy arrays

1 Answers1