Generating Digital Painting Lighting Effects via RGB-space Geometry (SIGGRAPH2020/TOG2020)

Related tags

Deep LearningPaintingLight
Overview

Project PaintingLight

PaintingLight is a project conducted by the Style2Paints team, aimed at finding a method to manipulate the illumination in digital paintings. The project started at about 2019 January, and the core algorithm is accepted by ACM Transitions on Graphics at 2020.

Because digital painting illumination data is not easy to obtain, this algorithm does not use deep learning. The core idea is to make use of color geometry to build up a perceptually workable relighting system. Such relighting may not be physically accurate, but are good enough for artistic use cases.

Note that the project is still in its technical researching stage. If you are a digital painting artist and you accidentally find this page, you may have to wait for our ongoing PhotoShop plug-in for practical usages.

Technical Paper

Please refer to our project page for our TOG/SIGGRAPH paper.

(c) artwork traced by ToS2P from an artwork by David Revoy under CC-BY license, www.peppercarrot.com

Video and Animated Demos

video_link

(c) artwork traced by ToS2P from an artwork by David Revoy under CC-BY license, www.peppercarrot.com

Installation

The codes have been tested for python 3.6 in both Windows 10 and Ubuntu 16.04. (If you use windows then python 3.6 is a must.)

To download codes:

git clone https://github.com/lllyasviel/PaintingLight.git
cd PaintingLight
cd code

To install some environment:

pip install opencv-python
pip install opencv-contrib-python
pip install h5py

To install some super accurate environment:

pip install tensorflow==1.4.0
pip install scipy==1.1.0
pip install trimesh==2.37.1

Then install the rtree package. The original rtree does not support windows, nevertheless here I provide a windows binary so that you can directly install it.

(linux only) sudo apt install libspatialindex-dev
(linux only) pip install rtree==0.9.3

(windows only) pip install Rtree-0.9.3-cp36-cp36m-win_amd64.whl

To install pyembree to enable GPU ray tracing:

(Optional, you can skip this step if you do not care about speed.)

Linux Pyembree

Windows Pyembree

Playing with Examples

You may directly play with our interactive examples!

The image noise artifacts in this webpage is caused by web GIF compression.

These artifacts do not exist when you try on your own.

002 * Example 002
* Not need a mask
* Input image "002.jpg"



To try it:

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>> python example002.py
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Image has copyrights.
003 * Example 003
* Not need a mask
* Input image "003.jpg"



To try it:

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>> python example003.py
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Image has copyrights.
004 * Example 004
* Not need a mask
* Input image "004.jpg"



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>> python example004.py
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005 * Example 005
* Not need a mask
* Input image "005.jpg"



To try it:

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>> python example005.py
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Image has copyrights.
006 * Example 006
* Not need a mask
* Input image "006.jpg"



To try it:

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>> python example006.py
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Image has copyrights.
007 * Example 007
* Not need a mask
* Input image "007.jpg"



To try it:

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>> python example007.py
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008 * Example 008
* Not need a mask
* Input image "008.jpg"



To try it:

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>> python example008.py
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009 * Example 009
* Not need a mask
* Input image "009.jpg"



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>> python example009.py
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010 * Example 010
* Not need a mask
* Input image "010.jpg"



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>> python example010.py
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011 * Example 011
* Not need a mask
* Input image "011.jpg"



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>> python example011.py
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012 * Example 012
* Not need a mask
* Input image "012.jpg"



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>> python example012.py
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013 * Example 013
* Not need a mask
* Input image "013.jpg"



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>> python example013.py
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014 * Example 014
* Not need a mask
* Input image "014.jpg"



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>> python example014.py
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015 * Example 015
* Not need a mask
* Input image "015.jpg"



To try it:

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>> python example015.py
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Image has copyrights.
016 * Example 016
* Not need a mask
* Input image "016.jpg"



To try it:

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>> python example016.py
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Image has copyrights.
017 * Example 017
* Not need a mask
* Input image "017.jpg"



To try it:

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>> python example017.py
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Image has copyrights.
018 * Example 018
* Not need a mask
* Input image "018.jpg"



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>> python example018.py
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Image has copyrights.
019 * Example 019
* Not need a mask
* Input image "019.jpg"



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>> python example019.py
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Image has copyrights.
020 * Example 020
* Not need a mask
* Input image "020.jpg"



To try it:

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>> python example020.py
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Image has copyrights.
021 * Example 021
* Not need a mask
* Input image "021.jpg"



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>> python example021.py
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Image has copyrights.
022 * Example 022
* Not need a mask
* Input image "022.jpg"



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>> python example022.py
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Image has copyrights.
023 * Example 023
* Not need a mask
* Input image "023.jpg"



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>> python example023.py
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Image has copyrights.
024 * Example 024
* Not need a mask
* Input image "024.jpg"



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>> python example024.py
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Image has copyrights.
025 * Example 025
* Not need a mask
* Input image "025.jpg"



To try it:

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>> python example025.py
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Image has copyrights.
026 * Example 026
* Not need a mask
* Input image "026.jpg"



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>> python example026.py
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Image has copyrights.
027 * Example 027
* Not need a mask
* Input image "027.jpg"



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>> python example027.py
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028 * Example 028
* Not need a mask
* Input image "028.jpg"



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>> python example028.py
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029 * Example 029
* Not need a mask
* Input image "029.jpg"



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>> python example029.py
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030 * Example 030
* Not need a mask
* Input image "030.jpg"



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>> python example030.py
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Image has copyrights.
031 * Example 031
* Not need a mask
* Input image "031.jpg"



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>> python example031.py
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Image has copyrights.
032 * Example 032
* Not need a mask
* Input image "032.jpg"



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>> python example032.py
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Image has copyrights.
033 * Example 033
* Not need a mask
* Input image "033.jpg"



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>> python example033.py
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034 * Example 034
* Not need a mask
* Input image "034.jpg"



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>> python example034.py
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035 * Example 035
* Not need a mask
* Input image "035.jpg"



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>> python example035.py
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036 * Example 036
* Not need a mask
* Input image "036.jpg"



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037 * Example 037
* Not need a mask
* Input image "037.jpg"



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038 * Example 038
* Not need a mask
* Input image "038.jpg"



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>> python example038.py
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039 * Example 039
* Not need a mask
* Input image "039.jpg"



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>> python example039.py
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040 * Example 040
* Not need a mask
* Input image "040.jpg"



To try it:

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>> python example040.py
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Image has copyrights.
041 * Example 041
* Not need a mask
* Input image "041.jpg"



To try it:

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>> python example041.py
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Image has copyrights.
042 * Example 042
* Not need a mask
* Input image "042.jpg"



To try it:

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>> python example042.py
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Image has copyrights.
043 * Example 043
* Not need a mask
* Input image "043.jpg"



To try it:

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>> python example043.py
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Image has copyrights.
044 * Example 044
* Not need a mask
* Input image "044.jpg"



To try it:

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>> python example044.py
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Image has copyrights.

Playing with Examples with Masks

045 * Example 045
* Need a mask
* Input image "045.jpg"



To try it:

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>> python example045.py
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Image has copyrights.

Playing with Your Own Images

Just try:

python default.py your_image.png

It is also possible to edit parameters in default.py. See codes for detals.

Note that big images may cause a out-of-memory error. See Here. Please resize your images to about 512px before processing.

FAQs

Q: It is mentioned that this project does not using 
   deep learning, then why it is still required to install tensorflow?

A: This is because we use SRCNN, a tensorflow neural network, to 
   pre-process input images in order to remove JPEG artifacts. Therefore 
   you still need to install tensorflow with a proper version.


Q: I am trying with my own images. Can you explain 
   the parameters so that I can get better results?

A: Here we list all possible parameters:

image:                               the input image.

mask:                                a paired mask. you can set it to None as it is optional.

ambient_intensity:                   the environment ambient light intensity. 0.45 recommended.

light_intensity:                     the intensity of your light. 0.85 recommended.

light_source_height:                 the height of your light source. It is the distance 
                                     from the image to your light source. 1.0 recommended.
                            
gamma_correction:                    the gamma correction parameter. It is a common parameter in 
                                     many digital cameras or smartphone cameras, and we provide 
                                     it if necessary. 1.0 recommended.
                            
stroke_density_clipping:             a scalar to clip the stroke density. Bigger number results 
                                     in sharper results. 1.2 recommended.
                            
enabling_multiple_channel_effects:   whether to generate multiple-channel lighting 
                                     effects. True recommended.
                                     
light_color_red:                     color of your light. 1.0 recommended.

light_color_green:                   color of your light. 1.0 recommended.

light_color_blue:                    color of your light. 1.0 recommended.


Q: I am currently trying with flat cell illustrations or line drawings, but 
   the results are bad. Is this method not suitable to line drawings and flat 
   cell illustrations?

A: This method not suitable to line drawings and flat cell illustrations. This 
   is because the main technique of this algorithm is called stroke density. 
   The algorithm fails if the input image do not contain such strokes or 
   similar patterns.


Q: I have tried many parameters but I am still not very satisfied. 
    What can I do to realize the full potential of this algorithm?

A: If you really need you may manually annotate a mask and use the masked mode. 
   You may see also the code for the “Playing with Examples with Masks” examples.

Citation

@Article{ZhangTOG2020,
   author    = {Lvmin Zhang and Edgar Simo-Serra and Yi Ji and Chunping Liu},
   title     = {{Generating Digital Painting Lighting Effects via RGB-space Geometry}},
   journal   = "Transactions on Graphics (Presented at SIGGRAPH)",
   year      = 2020,
   volume    = 39,
   number    = 2,
}

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Comments
  • Important Installation Note & Bug Report about Memory Usage

    Important Installation Note & Bug Report about Memory Usage

    First of all, thank you for providing such an awesome research project!

    Important Installation Note: (code version:07d12f2) 1.For Windows user, Python version must be Python 3.6 x86-64. Higher python version doesn't support the pre-compiled whl file. You will receive the following error info if incorrect python version is used:

    Rtree-0.9.3-cp36-cp36m-win_amd64.whl is not a supported wheel on this platform.


    2. If you get the following error:

    ImportError: 'load_model' requires h5py.

    then you need to install h5py: pip install h5py


    3. [BUG] The 'ray intersecting process' sometimes consumes more than 5GB of physical memory, which will lead to crash with a "Memory Error" info.

    (MemoryError: Unable to allocate XXX. MiB for an array with shape (XXXXXX, 3) and data type float64)

    In addition, it sometimes (about 70% probability) causes the whole operating system to become frozen (without giving any error information, just keeps showing Begin ray intersecting ...). The reason may be that all the physical memory is used up. (And the physical memory usage of python.exe increase too fast so that windows memory management doesn't have enough time to swap it to the virtual memory.) When my computer is frozen, I can't move the cursor or open the Task Manager, and the keyboard does not respond. The only solution is to forcely reboot the computer by pressing the power button. It's quite a strange bug!

    [Workaround] I finally found a workaround to prevent my computer from being frozen. Use Process Governor to limit the memory usage of 'python.exe'. Command: procgov64 --maxmem 5000M python default.py image.png

    After I use the tool, though the "memory error" persists, my computer won't get frozen!

    Hardware and software environment: OS: Win 8.1 x64 Physical memory: 8GB Pyembree not installed.


    I know it's quite HARD to develop such a complex research project. Hope the above information could benefit other users and help the authors to fix the bug.



    [Update_2020-06-09]

    1. Solved. This has been added to readme.md.
    2. Solved. This has been added to readme.md.
    3. It seems that this system frozen bug ONLY occurs when physical memory is equal to or less than 8GB. (For default 512px image examples.)

    A BETTER solution is Here! (This solution can prevent the system from being frozen.)

    opened by gceboh 11
  • License issue

    License issue

    Hey,

    The artwork here: https://github.com/lllyasviel/PaintingLight/blob/master/index_files/paintlight_title.jpg published on https://lllyasviel.github.io/PaintingLight/ is an artwork traced from my art and a copy of my OC and design of Shichimi... source comic page for proof: https://www.peppercarrot.com/0_sources/0ther/artworks/hi-res/2016-08-16_comic-page_from-A-to-Z_tutorial_by-David-Revoy.jpg

    But! I publish this art under Creative Commons attribution 4.0 International to "David Revoy"; it allows you to do use it, do derivation, etc. I just request here you write somewhere "artwork traced by <insertnamehere> from an artwork by David Revoy under CC-BY license, www.peppercarrot.com" . Thanks!

    opened by Deevad 8
  • SRCNN.NET does not load

    SRCNN.NET does not load

    Expected Output: Model would load and proceed to show lighting of examples/custom image

    Obtained Output: Failure to load model with the correct dependencies installed. Error reason is unknown but can be guessed at where the root issue is.

    Code snippet

    Traceback (most recent call last): File "example001.py", line 18, in <module> from ProjectPaintingLight import run File "C:\Users\prome\PycharmProjects\PaintingLight\PaintingLight-master\code\ProjectPaintingLight.py", line 26, in <module> srcnn = tf.keras.models.load_model('srcnn.net') File "C:\Users\prome\PycharmProjects\PaintingLight\core\lib\site-packages\tensorflow\python\keras\_impl\keras\models.py", line 244, in load_model model_config = json.loads(model_config.decode('utf-8')) AttributeError: 'str' object has no attribute 'decode'

    I have gotten this program to work in the past, varies on day I installed python, some builds it will work, some builds it won't, even if they use the same dependencies and so on... A standalone version (packaged) or even a docker image might be useful, as this "app" is touchy enough to break from a number of other factors.

    opened by 78Alpha 7
  • Seriously, the licence needs fixed.

    Seriously, the licence needs fixed.

    There's been interest in adding this to Krita, but given people will use Krita for commercial works it's necessary to know how this project can be used. The Apache Licences in this repo would permit it; however, the copyright claim on the project's page would not.

    opened by VegaDeftwing 7
  • Small advice about readme.md

    Small advice about readme.md

    Small Advice about readme.md:

    1. At readme.md line 33: I suggest change "super accurate" to "Image super resolution".

    2. About the license statement: Licensed by Style2Paints for noncommercial research use only. Currently the license statement only appears in the project page, but not in readme.md. I suggest add the License statement to readme.md. (Note that the above license statement is contrary with the license file lies in the root dir. The Apache License 2.0 allows for "Commercial use". Probably the root license file is wrong.)

    3. By the way, style2paints also seems to suffer from the license file problem.

    Hope these are helpful!

    opened by gceboh 4
  • not an issue really but really have no idea where to ask

    not an issue really but really have no idea where to ask

    how exactly do i save my results? i've been loving playing arround with this but i just wish i knew how to save some angles since some of these look very impressive

    opened by pokeheadroom 2
  • error:1407742E:SSL routines:SSL23_GET_SERVER_HELLO:tlsv1 alert protocol version

    error:1407742E:SSL routines:SSL23_GET_SERVER_HELLO:tlsv1 alert protocol version

    This error comes out fatal: unable to access 'https://github.com/lllyasviel/PaintingLight.git/': error:1407742E:SSL routines:SSL23_GET_SERVER_HELLO:tlsv1 alert protocol version

    opened by ash00013 0
  • Cv2 Module Not Found

    Cv2 Module Not Found

    I get an error when execute python default.py my_image.png This: Traceback (most recent call last): File "default.py", line 1, in import cv2 ModuleNotFoundError: No module named 'cv2'

    What can i do?

    opened by Oltrex 0
  • Attribute Error: 'str' object has no attribute 'decode'

    Attribute Error: 'str' object has no attribute 'decode'

    Hi, I have followed the instructions on both Weight and Biases and GitHub Readme. I was using anaconda, created a Python 3.6.12, I have successfully installed everything except Pyembree. However, as I tried to run an example, I was greeted with Attribute Error: 'str' object has no attribute 'decode' Note: I am new to Github, so I don't know if there is something I did wrong.

    Kind regards Ian Attribute error

    opened by I201IH 1
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