Conversion of numpy array to GEE image

Question

My program needs a numpy array for processing, so I convert GEE image into numpy array using this code:

# Define an image.
img1 = ee.Image( 'LANDSAT/LC08/C01/T1_SR/LC08_038029_20180810') \
  .select(['B2','B3','B4', 'B5', 'B6'])
new=img1.toArray().toArray(1)
# Define an area of interest.
aoi = ee.Geometry.Polygon(
  [[[-110.8, 44.7],
    [-110.8, 44.6],
    [-110.6, 44.6],
    [-110.6, 44.7]]], None, False)

# Get 2-d pixel array for AOI - returns feature with 2-D pixel array as property per band.
band_arrs = img1.sampleRectangle(region=aoi)

# Get individual band arrays.
band_arr_b2 = band_arrs.get('B2')
band_arr_b3 = band_arrs.get('B3')
band_arr_b4 = band_arrs.get('B4')


# Transfer the arrays from server to client and cast as np array.
np_arr_b2 = np.array(band_arr_b2.getInfo())
np_arr_b3 = np.array(band_arr_b3.getInfo())
np_arr_b4 = np.array(band_arr_b4.getInfo())
# Expand the dimensions of the images so they can be concatenated into 3-D.
np_arr_b2 = np.expand_dims(np_arr_b2, 2)
np_arr_b3 = np.expand_dims(np_arr_b3, 2)
np_arr_b4 = np.expand_dims(np_arr_b4, 2)
# Stack the individual bands to make a 3-D array.
rgb_img = np.concatenate((  np_arr_b4,np_arr_b3,np_arr_b2), 2)

Now can I go back from numpy array to GEE image?

Answer 1

Here I am uploading code to convert GEE image to array and then again convert that array to GEE image, Instead of Image you can select band to do process with the converted band array and then convert it into the image as you said your requirement.

• As we have image collection and converted it into an array

  var array = image.toarray();
  

• sort array by the first band, keeping other bands

• After converting into an array you can do your required process with the array, as I have done below.

  var axes = { image:0, band:1 }
  var sort = array.arraySlice(axes.band, 0, 1); 
  

• select bands from index 0 to 1` (NDVI)

  var sorted = array.arraySort(sort);
  

• take the last image only (MAX value)

• for the max value sorted

  var length = sorted.arrayLength(axes.image);
  var valuesMax = sorted.arraySlice(axes.image, length.subtract(1), length);
  

• Now convert that sliced array back to image.

  var max = valuesMax.arrayProject([axes.band]).arrayFlatten([['max', 'time']])