Update README.md

data_conversions/README.md

@@ -20,29 +20,3 @@ python download_datasets.py -f [path to data folder] -d [Dataset to download]
 For Scannet, please refer to http://www.scan-net.org/ . In segmentation task, We follow [pointnet++ preprocessed data](https://github.com/charlesq34/pointnet2/tree/master/scannet) ([Onedrive link](https://1drv.ms/u/s!ApbTjxa06z9CgQhxDuSJPB5-FHtm)).
 
 For S3DIS, please refer to http://buildingparser.stanford.edu/dataset.html#Download
-
-## Converting to .h5 Files
-
-For big scene point cloud datasets like **Scannet** and **S3DIS**, we split them into small blocks for training:
-
-```
-python3 split_data/scannet_split.py
-```
-
-```
-python3 split_data/s3dis_prepare_label.py
-python3 split_data/s3dis_split.py
-```
-
-Then, the .h5 files can be generated by:
-
-```
-python3 prepare_[dataset]_data.py -f [Path to data folder]
-```
-
-If you want to use extra features, such as RGB, you can use:
-
-```
-python3 prepare_multiChannel_seg_data.py -f [Path to data folder] -c [Channel number]
-```
-