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diff --git a/LICENSE b/LICENSE
@@ -1,6 +1,6 @@
 The MIT License (MIT)
 
-Copyright (c) 2020 nihui
+Copyright (c) 2021 ArchieMeng
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

diff --git a/README.md b/README.md
@@ -1,18 +1,37 @@
-# RIFE ncnn Vulkan
+# RIFE ncnn Vulkan Python
 
-![CI](https://github.com/nihui/rife-ncnn-vulkan/workflows/CI/badge.svg)
+## Introduction
+[rife-ncnn-vulkan](https://github.com/nihui/rife-ncnn-vulkan) is nihui's ncnn implementation of Real-World Super-Resolution via Kernel Estimation and Noise Injection super resolution.
 
-ncnn implementation of RIFE, Real-Time Intermediate Flow Estimation for Video Frame Interpolation.
+rife-ncnn-vulkan-python wraps [rife-ncnn-vulkan project](https://github.com/nihui/rife-ncnn-vulkan) by SWIG to make it easier to integrate rife-ncnn-vulkan with existing python projects.
 
-rife-ncnn-vulkan uses [ncnn project](https://github.com/Tencent/ncnn) as the universal neural network inference framework.
+## Downloads
 
-## [Download](https://github.com/nihui/rife-ncnn-vulkan/releases)
+Linux/Windos/Mac X86_64 build releases are available now. However, for Linux you may need to compile it yourself if you
+are using python version other than 3.8 . (The compiled python C extension library is bound to python version now)
 
-Download Windows/Linux/MacOS Executable for Intel/AMD/Nvidia GPU
+## Build
 
-**https://github.com/nihui/rife-ncnn-vulkan/releases**
+First, you have to install python, python development package (Python native development libs in Visual Studio), vulkan SDK and SWIG on your platform. And then:
 
-This package includes all the binaries and models required. It is portable, so no CUDA or PyTorch runtime environment is needed :)
+### Linux
+```shell
+git clone https://github.com/ArchieMeng/rife-ncnn-vulkan-python.git
+cd rife-ncnn-vulkan-python
+git submodule update --init --recursive
+cmake -B build src
+cd build
+make
+```
+
+### Windows
+I used Visual Studio 2019 and msvc v142 to build this project for Windows.
+
+Install visual studio and open the project directory, and build. Job done.
+
+The only problem on Windows is that, you cannot use [CMake for Windows](https://cmake.org/download/) to generate the Visual Studio solution file and build it. This will make the lib crash on loading.
+
+The only way is [use Visual Studio to open the project as directory](https://www.microfocus.com/documentation/visual-cobol/vc50/VS2019/GUID-BE1C48AA-DB22-4F38-9644-E9B48658EF36.html), and build it from Visual Studio.
 
 ## About RIFE
 
@@ -25,112 +44,26 @@ Huang, Zhewei and Zhang, Tianyuan and Heng, Wen and Shi, Boxin and Zhou, Shuchan
 https://rife-vfi.github.io
 
 https://arxiv.org/abs/2011.06294
-
 ## Usages
 
-Input two frame images, output one interpolated frame image.
-
-### Example Commands
-
-```shell
-./rife-ncnn-vulkan -0 0.jpg -1 1.jpg -o 01.jpg
-./rife-ncnn-vulkan -i input_frames/ -o output_frames/
-```
-
-Example below runs on CPU, Discrete GPU, and Integrated GPU all at the same time. Uses 2 threads for image decoding, 4 threads for one CPU worker, 4 threads for another CPU worker, 2 threads for discrete GPU, 1 thread for integrated GPU, and 4 threads for image encoding.
-```shell
-./rife-ncnn-vulkan -i input_frames/ -o output_frames/ -g -1,-1,0,1 -j 2:4,4,2,1:4
-```
-
-### Video Interpolation with FFmpeg
-
-```shell
-mkdir input_frames
-mkdir output_frames
-
-# find the source fps and format with ffprobe, for example 24fps, AAC
-ffprobe input.mp4
+### Example Program
 
-# extract audio
-ffmpeg -i input.mp4 -vn -acodec copy audio.m4a
+```Python
+from PIL import Image
+from rife_ncnn_vulkan import RIFE
 
-# decode all frames
-ffmpeg -i input.mp4 input_frames/frame_%08d.png
-
-# interpolate 2x frame count
-./rife-ncnn-vulkan -i input_frames -o output_frames
-
-# encode interpolated frames in 48fps with audio
-ffmpeg -framerate 48 -i output_frames/%08d.png -i audio.m4a -c:a copy -crf 20 -c:v libx264 -pix_fmt yuv420p output.mp4
-```
-
-### Full Usages
-
-```console
-Usage: rife-ncnn-vulkan -0 infile -1 infile1 -o outfile [options]...
-       rife-ncnn-vulkan -i indir -o outdir [options]...
-
-  -h                   show this help
-  -v                   verbose output
-  -0 input0-path       input image0 path (jpg/png/webp)
-  -1 input1-path       input image1 path (jpg/png/webp)
-  -i input-path        input image directory (jpg/png/webp)
-  -o output-path       output image path (jpg/png/webp) or directory
-  -m model-path        rife model path (default=rife-HD)
-  -g gpu-id            gpu device to use (-1=cpu, default=auto) can be 0,1,2 for multi-gpu
-  -j load:proc:save    thread count for load/proc/save (default=1:2:2) can be 1:2,2,2:2 for multi-gpu
-  -x                   enable tta mode
-  -u                   enable UHD mode
-  -f pattern-format    output image filename pattern format (%08d.jpg/png/webp, default=ext/%08d.png)
+im0, im1 = Image.open("0.png"), Image.open("1.png")
+rife = RIFE(0)
+im = rife.process(im0, im1)
+im.save("interframe.png")
 ```
 
-- `input0-path`, `input1-path` and `output-path` accept file path
-- `input-path` and `output-path` accept file directory
-- `load:proc:save` = thread count for the three stages (image decoding + rife interpolation + image encoding), using larger values may increase GPU usage and consume more GPU memory. You can tune this configuration with "4:4:4" for many small-size images, and "2:2:2" for large-size images. The default setting usually works fine for most situations. If you find that your GPU is hungry, try increasing thread count to achieve faster processing.
-- `pattern-format` = the filename pattern and format of the image to be output, png is better supported, however webp generally yields smaller file sizes, both are losslessly encoded
-
 If you encounter a crash or error, try upgrading your GPU driver:
 
 - Intel: https://downloadcenter.intel.com/product/80939/Graphics-Drivers
 - AMD: https://www.amd.com/en/support
 - NVIDIA: https://www.nvidia.com/Download/index.aspx
 
-## Build from Source
-
-1. Download and setup the Vulkan SDK from https://vulkan.lunarg.com/
-  - For Linux distributions, you can either get the essential build requirements from package manager
-```shell
-dnf install vulkan-headers vulkan-loader-devel
-```
-```shell
-apt-get install libvulkan-dev
-```
-```shell
-pacman -S vulkan-headers vulkan-icd-loader
-```
-
-2. Clone this project with all submodules
-
-```shell
-git clone https://github.com/nihui/rife-ncnn-vulkan.git
-cd rife-ncnn-vulkan
-git submodule update --init --recursive
-```
-
-3. Build with CMake
-  - You can pass -DUSE_STATIC_MOLTENVK=ON option to avoid linking the vulkan loader library on MacOS
-
-```shell
-mkdir build
-cd build
-cmake ../src
-cmake --build . -j 4
-```
-
-### TODO
-
-* test-time temporal augmentation aka TTA-t
-
 ### Model
 
 | model | upstream version |
@@ -152,18 +85,10 @@ cmake --build . -j 4
 
 ### Interpolate with rife rife-anime model
 
-```shell
-rife-ncnn-vulkan.exe -m models/rife-anime -0 0.png -1 1.png -o out.png
-```
-
 ![rife](images/out.png)
 
 ### Interpolate with rife rife-anime model + TTA-s
 
-```shell
-rife-ncnn-vulkan.exe -m models/rife-anime -x -0 0.png -1 1.png -o out.png
-```
-
 ![rife](images/outx.png)
 
 ## Original RIFE Project
@@ -176,3 +101,4 @@ rife-ncnn-vulkan.exe -m models/rife-anime -x -0 0.png -1 1.png -o out.png
 - https://github.com/webmproject/libwebp for encoding and decoding Webp images on ALL PLATFORMS
 - https://github.com/nothings/stb for decoding and encoding image on Linux / MacOS
 - https://github.com/tronkko/dirent for listing files in directory on Windows
+- https://github.com/nihui/rife-ncnn-vulkan the original rife-ncnn-vulkan project