diff --git a/.gitignore b/.gitignore
index 795928a..90c95f5 100644
--- a/.gitignore
+++ b/.gitignore
@@ -105,9 +105,9 @@ MANIFEST-*
# new ignore options for multiple images translation
-deep_image_analogy/datasets/images_content/*
-deep_image_analogy/datasets/images_style/*
-deep_image_analogy/datasets/*.txt
+#deep_image_analogy/datasets/images_content/*
+#deep_image_analogy/datasets/images_style/*
+#deep_image_analogy/datasets/*.txt
deep_image_analogy/output
diff --git a/README.md b/README.md
index 91bfde8..3e5a4aa 100644
--- a/README.md
+++ b/README.md
@@ -2,8 +2,6 @@
# Deep Image Analogy
-The major contributors of this repository include [Jing Liao](https://liaojing.github.io/html/index.html), [Yuan Yao](http://yuanyao.info/), [Lu Yuan](http://www.lyuan.org/), [Gang Hua](http://www.ganghua.org/) and [Sing Bing Kang](http://www.singbingkang.com/publications/) at Microsoft Research.
-
## Introduction
**Deep Image Analogy** is a technique to find semantically-meaningful dense correspondences between two input images. It adapts the notion of image analogy with features extracted from a Deep Convolutional Neural Network.
@@ -16,11 +14,10 @@ The major contributors of this repository include [Jing Liao](https://liaojing.g
## Disclaimer
-This is an official C++ combined with CUDA implementation of [Deep Image Analogy](https://arxiv.org/abs/1705.01088). It is worth noticing that:
-- Our codes are based on [Caffe](https://github.com/Microsoft/caffe).
-- Our codes only have been tested on Windows 10, Windows Server 2012 R2 and Ubuntu with CUDA 8 or 7.5.
-- Our codes only have been tested on several Nvidia GPU: Titan X, Titan Z, K40, GTX770.
-- The size of input image is limited, mostly should not be large than 700x500 if you use 1.0 for parameter **ratio**.
+This is an reimplemention of [Deep Image Analogy](https://github.com/msracver/Deep-Image-Analogy/tree/linux) with C++ combined with CUDA. It is worth noticing that:
+- The codes are based on [Caffe](https://github.com/Microsoft/caffe).
+- The codes only have been tested on Ubuntu with CUDA 8 or 7.5.
+- The codes only support for machine with GPU, and have been tested on Nvidia GeoForce GTX 1080.
## License
@@ -38,69 +35,58 @@ If you find **Deep Image Analogy** (include deep patchmatch) helpful for your re
}
```
-## Application
-
-### Photo to Style
-
-One major application of our code is to transfer the style from a painting to a photo.
-
-
-
-
-
-
-
-### Photo to Photo
-
-It can do color transfer between two photos, such as generating time lapse.
-
-
-
## Getting Started
### Prerequisite
-- Linux or Mac OS X
-- CUDA 8 or 7.5
+- Linux and CUDA 8 or 7.5
### Configure & Build
- Install dependencies for building Caffe. Just follow the tutorial from [Caffe](http://caffe.berkeleyvision.org/).
-- Use configuration script by typing ```sh scripts/config_deep_image_analogy.sh```.
+- Use configuration script to download [VGG19 Caffemodel](http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_19_layers.caffemodel) by typing ```sh scripts/config_deep_image_analogy.sh```.
- Modify the CUDA path in ```Makefile.config.example``` and rename it to ```Makefile.config```.
- Compile Caffe, make sure you installed all the dependencies before. Just type ```make all```.
- Compile deep_image_analogy by ```sh scripts/make_deep_image_analogy.sh```.
- Add libraries built by Caffe into ```LD_LIBRARY_PATH``` by ```export LD_LIBRARY_PATH="./build/lib"```.
+### Datastets
+
+To run the codes for multiple images, the input datasets are required to be formed as follow steps:
+
+- Put the content images and style images into ```./deep_image_analogy/images_content``` and ```./deep_image_analogy/images_style``` folders.
+- Edit the configuration in ```./script/generate_list.sh``` and then run
+```sudo sh ./script/generate_list.sh``` to generate file lists.
+
+- Finally, the datasets will be formed as follows:
+```
+--- datasets/images_content/*.jpg
+--- datasets/images_style/*.jpg
+--- datasets/content_list.txt
+--- datasets/style_list.txt
+```
+
+**Tips:** The size of input image is limited, mostly should not be large than 700x500 if you use 1.0 for parameter **ratio**.
+
### Demo
-Open ```main.cpp``` in ```deep_image_analogy/source/``` to see how to run a demo. You need to set several parameters which have been mentioned in the paper. To be more specific, you need to set
+To run the demo, just type:
+```
+./demo deep_image_analogy/models/ deep_image_analogy/demo/content.png deep_image_analogy/demo/style.png deep_image_analogy/demo/output/ 0 0.5 2 0
+```
+
+You need to set several parameters which have been mentioned in the paper. To be more specific, you need to set
- **path_model**, where the VGG-19 model is.
-- **path_A**, the input image A.
-- **path_BP**, the input image BP.
-- **path_output**, the output path.
+- **path_A**, the file list of input content images A.
+- **path_BP**, the file list of input style images BP.
+- **path_output**, the output path, will be created automatically.
- **GPU Number**, GPU ID you want to run this experiment.
- **Ratio**, the ratio to resize the inputs before sending them into the network.
- **Blend Weight**, the level of weights in blending process.
- **Flag of WLS Filter**, if you are trying to do photo style transfer, we recommend to switch this on to keep the structure of original photo.
-To run the demo, just type:
-```
-./demo deep_image_analogy/models/ deep_image_analogy/demo/content.png deep_image_analogy/demo/style.png deep_image_analogy/demo/output/ 0 0.5 2 0
-```
+
### Tips