fixes for orcale deploy e.g. tiling center

Dockerfile

@@ -44,6 +44,4 @@ WORKDIR /app
 ENTRYPOINT ["/miniconda/bin/conda", "run", "-n", "pdal-env", "python", "/app/run_oracle_wrapper.py"]
 
 
-# CMD ["--help" ]
-
 

config/config.yaml

 general:
-  input_folder: './local_input_folder'
-  output_folder: './local_output_folder'
+  input_folder: 'local_input_folder'
+  output_folder: 'local_output_folder'
   clean_output_folder: false
   run_sematic_segmentation: true
-  run_instance_segmentation: false
+  run_instance_segmentation: true
 label_formats:
   label_for_instances_in_gt: 'treeID'
   label_for_instances_in_predicted: 'instance_nr'
@@ -13,7 +13,7 @@ semantic_segmentation_params:
   batch_size : 5 # batch size for inference
   tile_size: 10 # tile size in meters
   min_density: 100 # minimum density of points in a tile(used for removing small tiles)
-  remove_small_tiles: 1 # 1: remove small tiles, 0: not remove small tiles
+  remove_small_tiles: 0 # 1: remove small tiles, 0: not remove small tiles
 instance_segmentation_params:
   instance_segmentation_script: './run_bash_scripts/tls.sh' 
   n_tiles: 3

d_run.sh

+
+docker container rm test_oracle
+docker image rm nibio/pc-geoslam-oracle
+./build.sh
+echo "Running the container"
+# docker run --gpus all --name test_oracle nibio/pc-geoslam-oracle
+docker run -it --gpus all --name test_oracle nibio/pc-geoslam-oracle
+
+

nibio_preprocessing/tiling.py

@@ -44,7 +44,9 @@ class Tiling:
                 { 
                     "type":"filters.splitter", 
                     "length":str(self.tile_size), 
-                    "buffer":str(self.tile_buffer) 
+                    "buffer":str(self.tile_buffer), 
+                    "origin_x":"0.0",
+                    "origin_y":"0.0"
                 },
                 {
                     "type":"writers.ply",

run_bash_scripts/sem_seg_sean.sh

@@ -3,7 +3,7 @@
 ############################ parameters #################################################
 # General parameters
 CLEAR_INPUT_FOLDER=1  # 1: clear input folder, 0: not clear input folder
-CONDA_ENV="pdal-env-1" # conda environment for running the pipeline
+CONDA_ENV="pdal-env" # conda environment for running the pipeline
 
 # Parameters for the semetnic segmentation
 data_folder="" # path to the folder containing the data