diff --git a/README.md b/README.md
index f07727f..ace83ff 100644
--- a/README.md
+++ b/README.md
@@ -32,8 +32,16 @@ Our inspiration comes from several research papers on this topic, as well as cur
 
 ![mtcnn](http://pic.dface.io/mtcnn.png)
 
-**If you want to contribute to DFace, please review the CONTRIBUTING.md in the project.We use [Slack](https://dfaceio.slack.com/) for
-tracking requests and bugs.**
+**If you want to contribute to DFace, please review the CONTRIBUTING.md in the project.We use [Slack](https://dfaceio.slack.com/) for tracking requests and bugs. Also you can following the QQ group 681403076 or my wechat jinkuaikuai005**
+
+
+## TODO(which you need to develop)
+- Based on cener loss or triplet loss implement the face conpare. Recommended Model is ResNet inception v2. Refer this [Paper](https://arxiv.org/abs/1503.03832) and [FaceNet](https://github.com/davidsandberg/facenet)
+- Face Anti-Spoofing, distinguish from face light and texture。Recomend with the LBP algorithm and SVM.
+- 3D mask  Anti-Spoofing.
+- Mobile first with caffe2 and c++.
+- Tensor rt migration.
+- Docker support, gpu version
 
 ## Installation
 
@@ -54,7 +62,7 @@ You can create your DFace environment very easily.
 conda env create -f path/to/environment.yml
 ```
 
-### Face Detetion
+### Face Detetion and Recognition
 
 If you are interested in how to train a mtcnn model, you can follow next step.
 
@@ -126,7 +134,7 @@ python src/train_net/train_o_net.py
 python test_image.py
 ```    
 
-### Face Recognition  
+### Face Comparing  
 
 TODO  
 
@@ -140,6 +148,10 @@ TODO
 
 #### 681403076  
 
+#### 本人微信(wechat)
+
+![](http://affluent.oss-cn-hangzhou.aliyuncs.com/html/images/perqr.jpg) 
+
 
 ## License
 
diff --git a/environment-win64.yml b/environment-win64.yml
new file mode 100644
index 0000000..ff59803
--- /dev/null
+++ b/environment-win64.yml
@@ -0,0 +1,243 @@
+name: ai_gpu
+channels:
+- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
+- peterjc123
+- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
+- defaults
+dependencies:
+- _ipyw_jlab_nb_ext_conf=0.1.0=py36he6757f0_0
+- alabaster=0.7.10=py36hcd07829_0
+- anaconda-client=1.6.5=py36hd36550c_0
+- anaconda-navigator=1.6.10=py36h51c3d4f_0
+- anaconda-project=0.8.0=py36h8b3bf89_0
+- asn1crypto=0.22.0=py36h8e79faa_1
+- astroid=1.5.3=py36h9d85297_0
+- astropy=2.0.2=py36h06391c4_4
+- babel=2.5.0=py36h35444c1_0
+- backports=1.0=py36h81696a8_1
+- backports.shutil_get_terminal_size=1.0.0=py36h79ab834_2
+- beautifulsoup4=4.6.0=py36hd4cc5e8_1
+- bitarray=0.8.1=py36h6af124b_0
+- bkcharts=0.2=py36h7e685f7_0
+- blaze=0.11.3=py36h8a29ca5_0
+- bleach=2.0.0=py36h0a7e3d6_0
+- bokeh=0.12.10=py36h0be3b39_0
+- boto=2.48.0=py36h1a776d2_1
+- bottleneck=1.2.1=py36hd119dfa_0
+- bzip2=1.0.6=vc14hdec8e7a_1
+- ca-certificates=2017.08.26=h94faf87_0
+- cachecontrol=0.12.3=py36hfe50d7b_0
+- certifi=2017.7.27.1=py36h043bc9e_0
+- chardet=3.0.4=py36h420ce6e_1
+- click=6.7=py36hec8c647_0
+- cloudpickle=0.4.0=py36h639d8dc_0
+- clyent=1.2.2=py36hb10d595_1
+- colorama=0.3.9=py36h029ae33_0
+- comtypes=1.1.2=py36heb9b3d1_0
+- conda-verify=2.0.0=py36h065de53_0
+- console_shortcut=0.1.1=h6bb2dd7_3
+- contextlib2=0.5.5=py36he5d52c0_0
+- cryptography=2.0.3=py36h123decb_1
+- curl=7.55.1=vc14hdaba4a4_3
+- cycler=0.10.0=py36h009560c_0
+- cython=0.26.1=py36h18049ac_0
+- cytoolz=0.8.2=py36h547e66e_0
+- dask=0.15.3=py36h396fcb9_0
+- dask-core=0.15.3=py36hd651449_0
+- datashape=0.5.4=py36h5770b85_0
+- decorator=4.1.2=py36he63a57b_0
+- distlib=0.2.5=py36h51371be_0
+- distributed=1.19.1=py36h8504682_0
+- docutils=0.14=py36h6012d8f_0
+- entrypoints=0.2.3=py36hfd66bb0_2
+- et_xmlfile=1.0.1=py36h3d2d736_0
+- fastcache=1.0.2=py36hffdae1b_0
+- filelock=2.0.12=py36hd7ddd41_0
+- flask=0.12.2=py36h98b5e8f_0
+- flask-cors=3.0.3=py36h8a3855d_0
+- freetype=2.8=vc14h17c9bdf_0
+- get_terminal_size=1.0.0=h38e98db_0
+- gevent=1.2.2=py36h342a76c_0
+- glob2=0.5=py36h11cc1bd_1
+- greenlet=0.4.12=py36ha00ad21_0
+- h5py=2.7.0=py36hfbe0a52_1
+- hdf5=1.10.1=vc14hb361328_0
+- heapdict=1.0.0=py36h21fa5f4_0
+- html5lib=0.999999999=py36ha09b1f3_0
+- icc_rt=2017.0.4=h97af966_0
+- icu=58.2=vc14hc45fdbb_0
+- idna=2.6=py36h148d497_1
+- imageio=2.2.0=py36had6c2d2_0
+- imagesize=0.7.1=py36he29f638_0
+- intel-openmp=2018.0.0=hcd89f80_7
+- ipykernel=4.6.1=py36hbb77b34_0
+- ipython=6.1.0=py36h236ecc8_1
+- ipython_genutils=0.2.0=py36h3c5d0ee_0
+- ipywidgets=7.0.0=py36h2e74ada_0
+- isort=4.2.15=py36h6198cc5_0
+- itsdangerous=0.24=py36hb6c5a24_1
+- jdcal=1.3=py36h64a5255_0
+- jedi=0.10.2=py36hed927a0_0
+- jinja2=2.9.6=py36h10aa3a0_1
+- jpeg=9b=vc14h4d7706e_1
+- jsonschema=2.6.0=py36h7636477_0
+- jupyter=1.0.0=py36h422fd7e_2
+- jupyter_client=5.1.0=py36h9902a9a_0
+- jupyter_console=5.2.0=py36h6d89b47_1
+- jupyter_core=4.3.0=py36h511e818_0
+- jupyterlab=0.27.0=py36h34cc53b_2
+- jupyterlab_launcher=0.4.0=py36h22c3ccf_0
+- lazy-object-proxy=1.3.1=py36hd1c21d2_0
+- libiconv=1.15=vc14h29686d3_5
+- libpng=1.6.32=vc14h5163883_3
+- libssh2=1.8.0=vc14hcf584a9_2
+- libtiff=4.0.9=h0f13578_0
+- libxml2=2.9.4=vc14h8fd0f11_5
+- libxslt=1.1.29=vc14hf85b8d4_5
+- llvmlite=0.20.0=py36_0
+- locket=0.2.0=py36hfed976d_1
+- lockfile=0.12.2=py36h0468280_0
+- lxml=4.1.0=py36h0dcd83c_0
+- lzo=2.10=vc14h0a64fa6_1
+- markupsafe=1.0=py36h0e26971_1
+- matplotlib=2.1.0=py36h11b4b9c_0
+- mccabe=0.6.1=py36hb41005a_1
+- menuinst=1.4.10=py36h42196fb_0
+- mistune=0.7.4=py36h4874169_0
+- mpmath=0.19=py36he326802_2
+- msgpack-python=0.4.8=py36h58b1e9d_0
+- multipledispatch=0.4.9=py36he44c36e_0
+- navigator-updater=0.1.0=py36h8a7b86b_0
+- nbconvert=5.3.1=py36h8dc0fde_0
+- nbformat=4.4.0=py36h3a5bc1b_0
+- networkx=2.0=py36hff991e3_0
+- nltk=3.2.4=py36hd0e0a39_0
+- nose=1.3.7=py36h1c3779e_2
+- notebook=5.0.0=py36hd9fbf6f_2
+- numba=0.35.0=np113py36_10
+- numpydoc=0.7.0=py36ha25429e_0
+- odo=0.5.1=py36h7560279_0
+- olefile=0.44=py36h0a7bdd2_0
+- opencv=3.3.1=py36h20b85fd_1
+- openpyxl=2.4.8=py36hf3b77f6_1
+- openssl=1.0.2l=vc14hcac20b0_2
+- packaging=16.8=py36ha0986f6_1
+- pandas=0.20.3=py36hce827b7_2
+- pandoc=1.19.2.1=hb2460c7_1
+- pandocfilters=1.4.2=py36h3ef6317_1
+- partd=0.3.8=py36hc8e763b_0
+- path.py=10.3.1=py36h3dd8b46_0
+- pathlib2=2.3.0=py36h7bfb78b_0
+- patsy=0.4.1=py36h42cefec_0
+- pep8=1.7.0=py36h0f3d67a_0
+- pickleshare=0.7.4=py36h9de030f_0
+- pillow=4.2.1=py36hdb25ab2_0
+- pip=9.0.1=py36hadba87b_3
+- pkginfo=1.4.1=py36hb0f9cfa_1
+- ply=3.10=py36h1211beb_0
+- progress=1.3=py36hbeca8d3_0
+- prompt_toolkit=1.0.15=py36h60b8f86_0
+- psutil=5.4.0=py36h4e662fb_0
+- py=1.4.34=py36ha4aca3a_1
+- pycodestyle=2.3.1=py36h7cc55cd_0
+- pycosat=0.6.2=py36hf17546d_1
+- pycparser=2.18=py36hd053e01_1
+- pycrypto=2.6.1=py36he68e6e2_1
+- pycurl=7.43.0=py36h086bf4c_3
+- pyflakes=1.6.0=py36h0b975d6_0
+- pygments=2.2.0=py36hb010967_0
+- pylint=1.7.4=py36ha4e6ded_0
+- pyodbc=4.0.17=py36h0006bc2_0
+- pyopenssl=17.2.0=py36h15ca2fc_0
+- pyparsing=2.2.0=py36h785a196_1
+- pyqt=5.6.0=py36hb5ed885_5
+- pysocks=1.6.7=py36h698d350_1
+- pytables=3.4.2=py36h71138e3_2
+- pytest=3.2.1=py36h753b05e_1
+- python=3.6.3=h9e2ca53_1
+- python-dateutil=2.6.1=py36h509ddcb_1
+- pytz=2017.2=py36h05d413f_1
+- pywavelets=0.5.2=py36hc649158_0
+- pywin32=221=py36h9c10281_0
+- pyyaml=3.12=py36h1d1928f_1
+- pyzmq=16.0.2=py36h38c27d9_2
+- qt=5.6.2=vc14h6f8c307_12
+- qtawesome=0.4.4=py36h5aa48f6_0
+- qtconsole=4.3.1=py36h99a29a9_0
+- qtpy=1.3.1=py36hb8717c5_0
+- requests=2.18.4=py36h4371aae_1
+- rope=0.10.5=py36hcaf5641_0
+- ruamel_yaml=0.11.14=py36h9b16331_2
+- scikit-image=0.13.0=py36h6dffa3f_1
+- seaborn=0.8.0=py36h62cb67c_0
+- setuptools=36.5.0=py36h65f9e6e_0
+- simplegeneric=0.8.1=py36heab741f_0
+- singledispatch=3.4.0.3=py36h17d0c80_0
+- sip=4.18.1=py36h9c25514_2
+- six=1.11.0=py36h4db2310_1
+- snowballstemmer=1.2.1=py36h763602f_0
+- sortedcollections=0.5.3=py36hbefa0ab_0
+- sortedcontainers=1.5.7=py36ha90ac20_0
+- sphinx=1.6.3=py36h9bb690b_0
+- sphinxcontrib=1.0=py36hbbac3d2_1
+- sphinxcontrib-websupport=1.0.1=py36hb5e5916_1
+- spyder=3.2.4=py36h8845eaa_0
+- sqlalchemy=1.1.13=py36h5948d12_0
+- sqlite=3.20.1=vc14h7ce8c62_1
+- statsmodels=0.8.0=py36h6189b4c_0
+- sympy=1.1.1=py36h96708e0_0
+- tblib=1.3.2=py36h30f5020_0
+- testpath=0.3.1=py36h2698cfe_0
+- tk=8.6.7=vc14hb68737d_1
+- toolz=0.8.2=py36he152a52_0
+- tornado=4.5.2=py36h57f6048_0
+- traitlets=4.3.2=py36h096827d_0
+- typing=3.6.2=py36hb035bda_0
+- unicodecsv=0.14.1=py36h6450c06_0
+- urllib3=1.22=py36h276f60a_0
+- vs2015_runtime=14.0.25123=hd4c4e62_2
+- wcwidth=0.1.7=py36h3d5aa90_0
+- webencodings=0.5.1=py36h67c50ae_1
+- werkzeug=0.12.2=py36h866a736_0
+- wheel=0.29.0=py36h6ce6cde_1
+- widgetsnbextension=3.0.2=py36h364476f_1
+- win_inet_pton=1.0.1=py36he67d7fd_1
+- win_unicode_console=0.5=py36hcdbd4b5_0
+- wincertstore=0.2=py36h7fe50ca_0
+- wrapt=1.10.11=py36he5f5981_0
+- xlrd=1.1.0=py36h1cb58dc_1
+- xlsxwriter=1.0.2=py36hf723b7d_0
+- xlwings=0.11.4=py36hd3cf94d_0
+- xlwt=1.3.0=py36h1a4751e_0
+- yaml=0.1.7=vc14hb31d195_1
+- zict=0.1.3=py36h2d8e73e_0
+- zlib=1.2.11=vc14h1cdd9ab_1
+- anaconda=custom=py36_0
+- cffi=1.10.0=py36_0
+- mkl=2017.0.3=0
+- mkl-service=1.1.2=py36_3
+- numexpr=2.6.2=np113py36_0
+- numpy=1.13.1=py36_0
+- scikit-learn=0.19.0=np113py36_0
+- scipy=0.19.1=np113py36_0
+- cuda80=1.0=h205658b_0
+- pytorch=0.3.0=py36_0.3.0cu80
+- vc=14.1=h21ff451_0
+- vs2017_runtime=15.4.27004.2010=0
+- pip:
+  - backports.shutil-get-terminal-size==1.0.0
+  - et-xmlfile==1.0.1
+  - ipython-genutils==0.2.0
+  - jupyter-client==5.1.0
+  - jupyter-console==5.2.0
+  - jupyter-core==4.3.0
+  - jupyterlab-launcher==0.4.0
+  - prompt-toolkit==1.0.15
+  - ruamel-yaml==0.11.14
+  - tables==3.4.2
+  - torch==0.3.0b0+591e73e
+  - torchvision==0.2.0
+  - win-inet-pton==1.0.1
+  - win-unicode-console==0.5
+prefix: D:\Tools\Anaconda3\envs\ai_gpu
+