Merge branch 'master' of https://github.com/matlab-deep-learning/Image-domain-conversion-using-CycleGAN

Upload pre-trained model

Author: taqji

README.md

@@ -11,9 +11,8 @@ CycleGAN is a GAN model that is generally used for the following purposes.
 The difference from Pix2Pix, which also perform image-image conversion, is that CycleGAN uses the unsupervised learning, so there is no need for a paired image dataset.
 In this example, even with the unsupervised learning, you can see the model convert the images by understanding whether the fruit was a whole one or a cut one.
 
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-![result image](https://insidelabs-git.mathworks.com/tfukumot/cyclegan-for-github/raw/master/pics_for_doc/Result.mp4)
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+![result image](https://github.com/matlab-deep-learning/Image-domain-conversion-using-CycleGAN/raw/master/pics_for_doc/image_6.png)
+![result image](https://github.com/matlab-deep-learning/Image-domain-conversion-using-CycleGAN/raw/master/pics_for_doc/image_7.png)
 
 ## **Requirements**
 - [MATLAB](https://jp.mathworks.com/products/matlab.html)
@@ -30,18 +29,13 @@ MATLAB version should be R2019b and later
 -	generator.m — Function to create a CycleGAN generator network
 -	discriminator.m — Function to create a CycleGAN discriminator network
 -	cycleGanImageDatastore.m — Datastore to prepare batches of images for training
--	models.mat — Pretrained model that converts apples to oranges and vice-versa
 
 To run, open CycleGANExample.mlx and run the script. You can train the model or use the pretrained model by setting the doTraining flag to false. 
 
-![result image](https://insidelabs-git.mathworks.com/tfukumot/cyclegan-for-github/raw/master/pics_for_doc/image_6.png)
-![result image](https://insidelabs-git.mathworks.com/tfukumot/cyclegan-for-github/raw/master/pics_for_doc/image_7.png)
 
 # **Reference**
 [Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks](http://openaccess.thecvf.com/content_ICCV_2017/papers/Zhu_Unpaired_Image-To-Image_Translation_ICCV_2017_paper.pdf)
  (Jun-Yan Zhu.etc, 2017)
 
 
 Copyright 2019-2020 The MathWorks, Inc.
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