Update README.md

Author: chenliu-wustl

README.md

@@ -22,12 +22,31 @@ cd ..
 ### Data preparation
 We convert [ScanNet](http://www.scan-net.org/) data to *.tfrecords* files for training and testing. The *.tfrecords* file can be downloaded from [here](https://mega.nz/#!IvAixABb!PD3wJtXX_6W3qtfKZQtl_P07mYPLwWst3cwbvuTXlSY).
 
-### Train the network
+### Training
 To train the network from the pretrained DeepLab network, please first download the DeepLab model [here](https://github.com/DrSleep/tensorflow-deeplab-resnet) (under the Caffe to TensorFlow conversion), and then run the following command.
-
 ```bash
 python train_planenet.py --restore=0 --modelPathDeepLab="path to the deep lab model" --rootFolder="folder which contains tfrecords files"
 ```
 
 ### Evaluation
-Please first download our trained network from [here](https://mega.nz/#!sjpT2DiQ!Uo-6hxyldmtnPoKk3TTdUHKZADRGy6nIPlmAeVzJs_8) and put the uncompressed folder under ./checkpoint
+Please first download our trained network from [here](https://mega.nz/#!sjpT2DiQ!Uo-6hxyldmtnPoKk3TTdUHKZADRGy6nIPlmAeVzJs_8) and put the uncompressed folder under ./checkpoint folder.
+
+To evaluate the performance against existing methods, please run:
+```bash
+python evaluate.py --rootFolder="folder which contains tfrecords files"
+```
+
+### Applications
+Please first download our trained network (see [Evaluation](### Evaluation) section for details). Script *predict.py* and *predict_custom.py* are for ScanNet testing images and custom images respectively. To predict and visualize ScanNet testing images, please run:
+
+```bash
+python predict.py --rootFolder="folder which contains tfrecords files" [--startIndex=0] [--numImages=30]
+```
+
+This will generate visualization images, a webpage containing all the visualization, as well as cache files under folder "predict". Similarly, the following command can be used to predict and visualize custom images:
+
+```bash
+python predict_custom.py --rootFolder="folder which contains custom images"
+```
+
+Same commands can be used for various applications by providing arguments, *--imageIndex*, *--suffix*, and *--textureFilename*