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1.5 KiB
1.5 KiB
Visualization
Before visualization, you need to change save_semantic, save_pt_offsets, save_instance to True in the config file and run the inference to write the output predictions.
There are two options for visualization:
-
Visualization using through a pop-up using open3D (default). Prerequisite:
pip install open3D==0.8.0 -
Write point clouds to
.plyfile then use an visualization application such as MeshLab to see the results. Just pass the arg--out YOUR_FILE.plyto enable this option.
After inference, run visualization by execute the following command
python visualization.py --dataset {} --prediction_path --split {} --scene_name {} --task {} --out {}
usage: visualization.py [-h] [--dataset {scannet,s3dis}]
[--prediction_path PREDICTION_PATH]
[--data_split DATA_SPLIT] [--room_name ROOM_NAME]
[--task TASK] [--out OUT]
optional arguments:
--dataset {scannet,s3dis}
dataset for visualization
--prediction_path PREDICTION_PATH
path to the prediction results
--data_split DATA_SPLIT
train/val/test for scannet or Area_ID for s3dis
--room_name ROOM_NAME
room_name
--task TASK input / semantic_gt / semantic_pred /
offset_semantic_pred / instance_gt / instance_pred
--out OUT output point cloud file in FILE.ply format