Code Modified from https://github.com/lukedeo/keras-acgan,
This is CIFAR10 version. Some interesting tricks refers to Soumith Chintala ganhacks(https://github.com/soumith/ganhacks).
I directly use the Minibatch Layer Code from:
https://github.com/forcecore/Keras-GAN-Animeface-Character
Thanks for the great work!
Any suggestion is welcomed!
This is one of generated images after 50 epochs:
keras-acgan-cifar10's Introduction
keras-acgan-cifar10's People
Forkers
xiaoboxie dingxiaoke gh26300 unit8co irene9adler siddharthdivi angel-hernandez91 belvegmar annelsm613 changkaiyan erfandarzi bxz9200 tony-chenjw chenbeixii ttyzh1 binarytoucan ssgantayatkeras-acgan-cifar10's Issues
License code
Hello, could you please provide a license for your code?
生成图片全灰色
您好,我生成的图片全部是灰色的,并且我打印了代码中的generated_images参数,发现全都是e-3次方量级,请问这是什么原因呢?我对代码的改动只限于一些版本问题导致import的替换,尝试改小学习率也没有效果。如果您能抽空回复我,我将十分感激
Reproducing the results in this repository
Hello.
I've been trying to reproduce the results shown in the README file.
I have used your code, as is, and ran it multiple times but the images generated where never close to the ones in the README.
Here's an example of my results by epoch 20:
Do you have any idea why I'm failing to achieve the same results you did, or is there any tip you could give to help me?
Thank you in advance!
The quality of the generator
Hi, from the picture you have shown in the Readme, I find the quality of the genreated images are not quit well .What dou you think about it.
mini batch discrimination hyperparameters
as i see, you call MinibatchDiscrimination(50, 30)
in order to implement discrimination. Are these parameters 50 and 30 related with image size, etc. or completely arbitrary? thanks...
Confusion Matrix
Can you please share how u made the confusion matrix?
image extraction
thank for your awesome work, after whole training complete how can i generate examples and save them one by one. thanks...
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A problem about your code
Keras-ACGAN-CIFAR10/cifar10.py
Line 253 in c5a89be
Hello sir.
I have a problem with these part of your code. Based on you previous codes, you set Real data has label in the range of 0.7-1.2 and Fake data is 0.0-0.3. But why in this place you reverse them and let Real data is 0.0-1.3?
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