Update README.md

README.md

@@ -1,12 +1,56 @@
-# KT-Net
-KT-Net: Knowledge Transfer for Unpaired 3D Shape Completion
+## KT-Net: Knowledge Transfer for Unpaired 3D Shape Completion
+- [Preprint paper](https://arxiv.org/abs/2111.11976).
 
-conda create -n kt-net python=3.8
-conda activate kt-net
+## Requirements
+- Ubuntu 14.04 or higher
+- CUDA 10.0 or higher
+- Python v3.7 or higher
+- Pytorch v1.2 or higher
 
+Specifically, The code has been tested with:
+- Ubuntu 18.04, CUDA 10.2, python 3.8.15, Pytorch 1.6.0, GeForce RTX 2080Ti.
 
-cd net/util/emd_module
-python setup.py install
-cd ../../..
+## Installation
+- Create the conda environment.
+  ```
+  conda create -n kt-net python=3.8
+  conda activate kt-net
+  ```
+Installation instructions for Ubuntu 18.04:
+   * Make sure <a href="https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html">CUDA</a>  and <a href="https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html">cuDNN</a> are installed. Only this configurations has been tested:
+     - Python 3.8.15, Pytorch 1.6.0
+    * Follow <a href="https://pytorch.org/">Pytorch installation procedure</a>. Note that the version of cudatoolkit must be strictly consistent with the version of CUDA
 
-sh run_KT.sh 
+- Intall some packages.
+  ```
+  pip install -r requirements
+  ```
+- Install EMD.
+  ```
+  cd net/util/emd_module
+  python setup.py install
+  cd ../../..
+  ```
+
+## Dataset & Pretrained model
+- [3DEPN]();
+- [CRN](https://github.com/junzhezhang/shape-inversion) Refer to ShapeInversion;
+- [Real-World Data](https://github.com/xuelin-chen/pcl2pcl-gan-pub) Refer to Pcl2Pcl;
+- [Pretrained Weights]().
+Also, you can download them from [BaiduDisk](https://pan.baidu.com/s/13GoHmTJ-jqg1zBgRbIUmNQ)(Code:0di4). Please place the data to ```./dataset``` and the pretrained model to '''./pretrain'''.
+
+## Train && Test
+To train the model, you can edit the parameter in the file '''train_KT.sh''' and run the command:
+  '''
+  sh train_KT.sh
+  '''
+
+To test the model, you can edit the parameter in the file '''test_KT.sh''' and run the command:
+  '''
+  sh test_KT.sh
+  '''
+
+ ## Acknowledgement
+The code is in part built on [MSC](https://github.com/ChrisWu1997/Multimodal-Shape-Completion). 
+The original code of emd is rendered from [MSN](https://github.com/Colin97/MSN-Point-Cloud-Completion). 
+The original code of chamfer3D is rendered from ["chamferDistancePytorch"](https://github.com/ThibaultGROUEIX/ChamferDistancePytorch/tree/master/chamfer3D).