Update README.md

README.md

@@ -39,8 +39,6 @@ cd octree/external && git clone --recursive https://github.com/wang-ps/octree-ex
 cd .. && mkdir build && cd build
 cmake .. -DUSE_CUDA=ON && cmake --build . --config Release
 export PATH=`pwd`:$PATH
-cd python
-export PATH=`pwd`:$PATH
 
 cd ../../../tensorflow/libs
 python build.py
@@ -68,27 +66,25 @@ python octree_parse.py
 cd ../
 ```
 #### CNN modeling
-- prepare the data 
-First it will generate the points file for each complex in general, refined, core set. (The density of points can be specificed, low resolution OctSurf can use low density points to accelerate the process, here for depth=6 model, we use density 3).    
+- prepare the data   
+	First it will generate the points file for each complex in general, refined, core set. (The density of points can be specificed, low resolution OctSurf can use low density points to accelerate the process, here for depth=6 model, we use density 3).    
 
-Then the points and labels will be transformed into tfrecords file.   
+	Then the points and labels will be transformed into tfrecords file.   
 ```angular2
 bash data_prepare_model.sh
 cd ..
 ```
-- train model 
-Specify the config files (the network architecture, the input/log path, iterations etc.)  
-
-Train networks.
+- train model   
+	Specify the config files (the network architecture, the input/log path, iterations etc.)  
 ```angular2
 cd tensorflow/script
 python run_cls.py --config configs/train_resnet_depth6.yaml
 ```
 
-- test performance  
-Specify the config files (the path for pretrained model/test dataset, network architecture, iterations etc)  
+- test performance    
+	Specify the config files (the path for pretrained model/test dataset, network architecture, iterations etc)  
 
-Test the pre-trained model on test dataset, and report the performance.  
+	Test the pre-trained model on test dataset, and report the performance.  
 ```angular2
 python test_reg_ave.py --config configs/test_resnet_depth6.yaml
 ```