Add max depth for stereo

cli_utils.py

@@ -62,6 +62,8 @@ def set_argparser():
     pm_parser.add_argument('--more_sift_features', action="store_true")
     pm_parser.add_argument('--save_space', action="store_true")
     pm_parser.add_argument('--add_new_videos', action="store_true")
+    pm_parser.add_argument('--stereo_min_depth', type=float, default=0.1)
+    pm_parser.add_argument('--stereo_max_depth', type=float, default=100)
 
     om_parser = parser.add_argument_group("Occlusion Mesh")
     om_parser.add_argument('--normals_method', default="radius", choices=["radius", "neighbours"])

main_pipeline.py

@@ -131,10 +131,10 @@ def main():
         colmap.align_model(output=env["georef_recon"],
                            input=thorough_model,
                            ref_images=env["georef_frames_list"])
-        if not (env["georef_frames_list"]/"images.bin").isfile():
+        if not (env["georef_recon"]/"images.bin").isfile():
             # GPS alignment failed, possibly because not enough GPS referenced images
             # Copy the original model without alignment
-            (env["thorough_recon"] / "0").merge_tree(env["georef_recon"])
+            thorough_model.merge_tree(env["georef_recon"])
         env["georef_recon"].merge_tree(env["georef_full_recon"])
     if args.inspect_dataset:
         colmap.export_model(output=env["georef_recon"] / "georef_sparse.ply",
@@ -166,7 +166,7 @@ def main():
         print_step(i, "Full reconstruction point cloud densificitation")
         env["georef_full_recon"].makedirs_p()
         colmap.undistort(input=env["georef_full_recon"])
-        colmap.dense_stereo()
+        colmap.dense_stereo(min_depth=env["stereo_min_depth"], max_depth=env["stereo_max_depth"])
         colmap.stereo_fusion(output=env["georefrecon_ply"])
 
     def get_matrix(path):

main_pipeline_no_lidar.py

@@ -87,10 +87,11 @@ def main():
         colmap.align_model(output=env["georef_recon"],
                            input=env["thorough_recon"] / "0",
                            ref_images=env["georef_frames_list"])
-        if not (env["georef_frames_list"]/"images.bin").isfile():
+        if not (env["georef_recon"]/"images.bin").isfile():
             # GPS alignment failed, possibly because not enough GPS referenced images
             # Copy the original model without alignment
-            (env["thorough_recon"] / "0").merge_tree(env["georef_recon"])
+            print("Warning, model alignment failed, the model will be normalized, and thus the depth maps too")
+            thorough_model.merge_tree(env["georef_recon"])
         env["georef_recon"].merge_tree(env["georef_full_recon"])
     if args.inspect_dataset:
         colmap.export_model(output=env["georef_recon"] / "georef_sparse.ply",
@@ -121,7 +122,7 @@ def main():
         print_step(i, "Full reconstruction point cloud densificitation")
         env["georef_full_recon"].makedirs_p()
         colmap.undistort(input=env["georef_full_recon"])
-        colmap.dense_stereo()
+        colmap.dense_stereo(min_depth=env["stereo_min_depth"], max_depth=env["stereo_max_depth"])
         colmap.stereo_fusion(output=env["georefrecon_ply"])
 
     i += 1

wrappers/colmap.py

@@ -98,10 +98,14 @@ class Colmap(Wrapper):
                    "--output_type", "COLMAP", "--max_image_size", str(max_image_size)]
         self.__call__(options)
 
-    def dense_stereo(self):
+    def dense_stereo(self, max_depth=None, min_depth=None):
         options = ["patch_match_stereo", "--workspace_path", self.dense_workspace,
                    "--workspace_format", "COLMAP",
                    "--PatchMatchStereo.geom_consistency", "1"]
+        if min_depth is not None:
+            options += ["--PatchMatchStereo.depth_min", str(min_depth)]
+        if max_depth is not None:
+            options += ["--PatchMatchStereo.depth_max", str(max_depth)]
         self.__call__(options)
 
     def stereo_fusion(self, output):