We have released our dataset for public use. The dataset can be downloaded through following links:
Sketch-image pairs: https://cloudstor.aarnet.edu.au/plus/s/rMSBYCjEZJ70ab2
Sketch with control color blocks: https://cloudstor.aarnet.edu.au/plus/s/ixj8XS0rMmUqq0Z
It is the original implementation of the journal article: Auto-painter: Cartoon image generation from sketch by using conditional Wasserstein generative adversarial networks https://www.sciencedirect.com/science/article/pii/S0925231218306209?via%3Dihub
This project mean to make an end-to-end network for the sketch of cartoon to have color automatically.
Try our demo here: http://103.202.133.77:10086/
Since the lab's server has temporarily expired, the demo is now unavailable. You can see the demo video and train your own model. Or you can build your demo page based on our provided models following this project: https://github.com/irfanICMLL/Auto_painter_demo
New model has been updated!~ The performance is much better than in the orginal paper! See the demo video:https://youtu.be/g9rf-YFGgbg
Have a try~
The pre-trained model can be downloaded from the following link: https://cloudstor.aarnet.edu.au/plus/s/LvyREKsiaH47Aa6
My homepage: https://irfanicmll.github.io/
Welcome to contact me~
python3.5
tensorflow1.4
Vgg model from:https://github.com/machrisaa/tensorflow-vgg(optional, if you use the loss_f)
Color images: Collected on the Internet
Sketch: Generated from the preprocessing/gen_sketch/sketch.py
Put you orginal data in the folder preprocessing/gen_sketch/pic_org
Run the sketch.py and you will get the training set in the preprocessing/gen_sketch/pic_sketch folder
Download the pre-train weight of Vgg16, and put the model and the pretrian weight uder the folder of training&test/my_vgg
Run the training command as:
python auto-painter.py --mode train --input_dir $TRAINING_SET --output_dir $OUTPUT --checkpoint None
Run the testing command as:
python auto-painter.py --mode test --input_dir $TESTING_SET --output_dir $OUTPUT_TEST --checkpoint $OUTPUT