Create visualization.md

docs/visualization.md

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+## 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 ``.ply`` file then use an visualization application such as [MeshLab](https://www.meshlab.net/) to see the results. Just pass the arg ``--out YOUR_FILE.ply`` to 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
+```
+
+
+