Add orthorectification module

contrib/orthorectify/orthorectify.py

@@ -0,0 +1,89 @@
+#!/usr/bin/env python3
+import rasterio
+import os
+import numpy as np
+from opensfm import dataset
+
+# TODO: command argument parser
+
+dataset_path = "/datasets/brighton2"
+dem_path = "/datasets/brighton2/odm_meshing/tmp/mesh_dsm.tif"
+
+target_images = [] # all
+target_images.append("DJI_0018.JPG")
+
+# Read DSM
+print("Reading DSM: %s" % dem_path)
+with rasterio.open(dem_path) as dem_raster:
+    dem = dem_raster.read()[0]
+    h, w = dem.shape
+
+    print("DSM dimensions: %sx%s pixels" % (w, h))
+   
+    # Read reconstruction
+    udata = dataset.UndistortedDataSet(dataset.DataSet(os.path.join(dataset_path, "opensfm")))
+    reconstructions = udata.load_undistorted_reconstruction()
+    if len(reconstructions) == 0:
+        raise Exception("No reconstructions available")
+
+    reconstruction = reconstructions[0]
+    for shot in reconstruction.shots.values():
+        if len(target_images) == 0 or shot.id in target_images:
+
+            print("Loading %s..." % shot.id)
+            shot_image = udata.load_undistorted_image(shot.id)
+
+            r = shot.pose.get_rotation_matrix()
+            Xs, Ys, Zs = shot.pose.get_origin()
+            cam_w = shot.camera.width
+            cam_h = shot.camera.height
+            f = shot.camera.focal
+
+            num_bands = shot_image.shape[2]
+
+            imgout = np.full((num_bands, w, h), np.nan, dtype=shot_image.dtype)
+
+            for i in range(w):
+                for j in range(h):
+
+                    # i, j = (168, 442) # TODO REMOVE
+
+                    # World coordinates
+                    Xa, Ya = dem_raster.xy(j, i)
+                    Za = dem[j][i]
+
+                    # Colinearity function http://web.pdx.edu/~jduh/courses/geog493f14/Week03.pdf
+                    dx = (Xa - Xs)
+                    dy = (Ya - Ys)
+                    dz = (Za - Zs)
+
+                    den = r[0][2] * dx + r[1][2] * dy + r[2][2] * dz
+                    x = 0.5 + (-f * (r[0][0] * dx + r[1][0] * dy + r[2][0] * dz) / den)
+                    y = 0.5 + (-f * (r[0][1] * dx + r[1][1] * dy + r[2][1] * dz) / den)
+
+                    # TODO: interpolate?
+                    # xi = round(x * cam_w)
+                    # yi = round(y * cam_h)
+
+                    for b in range(3):
+
+                        # TEST
+                        if x > 0 and y > 0:
+                            imgout[b][i][j] = 255
+            
+            imgout[imgout == np.nan] = 0
+            print(w)
+            print(h)
+
+            profile = {
+                'driver': 'GTiff',
+                'width': imgout.shape[1],
+                'height': imgout.shape[2],
+                'count': num_bands,
+                'dtype': imgout.dtype.name,
+                'nodata': None
+            }
+            with rasterio.open("/datasets/brighton2/odm_meshing/tmp/out.tif", 'w', **profile) as wout:
+                for b in range(num_bands):
+                    wout.write(imgout[b], b + 1)
+