Replaced gippy with rasterio

Dockerfile

@@ -74,7 +74,6 @@ RUN pip install -U \
   scipy \
   shapely \
   xmltodict \
-  https://github.com/OpenDroneMap/gippy/archive/numpyfix.zip \
   rasterio \
   attrs==19.1.0
 

configure.sh

@@ -91,7 +91,7 @@ install() {
                          libboost-log-dev
 
     echo "Installing split-merge Dependencies"
-    pip install -U scipy numpy==1.15.4 shapely pyproj https://github.com/OpenDroneMap/gippy/archive/numpyfix.zip psutil
+    pip install -U scipy numpy==1.15.4 shapely pyproj psutil
 
     echo "Compiling SuperBuild"
     cd ${RUNPATH}/SuperBuild

opendm/dem/commands.py

@@ -1,6 +1,6 @@
 import os
 import sys
-import gippy
+import rasterio
 import numpy
 import math
 import time
@@ -236,35 +236,33 @@ def post_process(geotiff_path, output_path, smoothing_iterations=1):
 
     log.ODM_INFO('Starting post processing (smoothing)...')
 
-    img = gippy.GeoImage(geotiff_path)
-    nodata = img[0].nodata()
-    arr = img[0].read()
+    with rasterio.open(geotiff_path) as img:
+        nodata = img.nodatavals[0]
+        dtype = img.dtypes[0]
+        arr = img.read()[0]
 
-    # Median filter (careful, changing the value 5 might require tweaking)
-    # the lines below. There's another numpy function that takes care of 
-    # these edge cases, but it's slower.
-    for i in range(smoothing_iterations):
-        log.ODM_INFO("Smoothing iteration %s" % str(i + 1))
-        arr = signal.medfilt(arr, 5)
+        # Median filter (careful, changing the value 5 might require tweaking)
+        # the lines below. There's another numpy function that takes care of 
+        # these edge cases, but it's slower.
+        for i in range(smoothing_iterations):
+            log.ODM_INFO("Smoothing iteration %s" % str(i + 1))
+            arr = signal.medfilt(arr, 5)
+        
+        # Fill corner points with nearest value
+        if arr.shape >= (4, 4):
+            arr[0][:2] = arr[1][0] = arr[1][1]
+            arr[0][-2:] = arr[1][-1] = arr[2][-1]
+            arr[-1][:2] = arr[-2][0] = arr[-2][1]
+            arr[-1][-2:] = arr[-2][-1] = arr[-2][-2]
+
+        # Median filter leaves a bunch of zeros in nodata areas
+        locs = numpy.where(arr == 0.0)
+        arr[locs] = nodata
+
+        # write output
+        with rasterio.open(output_path, 'w', **img.profile) as imgout:
+            imgout.write(arr.astype(dtype), 1)
     
-    # Fill corner points with nearest value
-    if arr.shape >= (4, 4):
-        arr[0][:2] = arr[1][0] = arr[1][1]
-        arr[0][-2:] = arr[1][-1] = arr[2][-1]
-        arr[-1][:2] = arr[-2][0] = arr[-2][1]
-        arr[-1][-2:] = arr[-2][-1] = arr[-2][-2]
-
-    # Median filter leaves a bunch of zeros in nodata areas
-    locs = numpy.where(arr == 0.0)
-    arr[locs] = nodata
-
-    # write output
-    imgout = gippy.GeoImage.create_from(img, output_path)
-    imgout.set_nodata(nodata)
-    imgout[0].write(arr)
-    output_path = imgout.filename()
-    imgout = None
-
     log.ODM_INFO('Completed post processing to create %s in %s' % (os.path.relpath(output_path), datetime.now() - start))
 
     return output_path

opendm/dem/merge.py

@@ -41,10 +41,7 @@ def euclidean_merge_dems(input_dems, output_dem, creation_options={}):
         logging.disable(logging.DEBUG)
 
     with rasterio.open(existing_dems[0]) as first:
-        src_nodata = 0
-        nodatavals = first.get_nodatavals()
-        if len(nodatavals) > 0:
-            src_nodata = nodatavals[0]
+        src_nodata = first.nodatavals[0]
         res = first.res
         dtype = first.dtypes[0]
         profile = first.profile
@@ -148,10 +145,7 @@ def euclidean_merge_dems(input_dems, output_dem, creation_options={}):
                 # With rio merge this just adds an extra row, but when the
                 # imprecision occurs at each block, you get artifacts
 
-                nodata = 0
-                nodatavals = src_d.get_nodatavals()
-                if len(nodatavals) > 0:
-                    nodata = nodatavals[0]
+                nodata = src_d.nodatavals[0]
 
                 # Alternative, custom get_window using rounding
                 src_window = tuple(zip(rowcol(

opendm/mesh.py

@@ -1,6 +1,5 @@
 from __future__ import absolute_import
 import os, shutil, sys, struct, random, math
-from gippy import GeoImage
 from opendm.dem import commands
 from opendm import system
 from opendm import log

portable.Dockerfile

@@ -74,7 +74,6 @@ RUN pip install -U \
   scipy \
   shapely \
   xmltodict \
-  https://github.com/OpenDroneMap/gippy/archive/numpyfix.zip \
   rasterio \
   attrs==19.1.0