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laoluzi
2016-08-26 23:12:55 +08:00
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@@ -6,12 +6,12 @@ This trains two adversarial deep learning models on real images, in order to pro
The generator model tries to produce images that look real and get a high score from the discriminator.␍
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The discriminator model tries to tell apart between real images and artificial images from the generator.␍
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Usage␍
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## Usage␍
**Training:**␍
`python dcgan.py --mode train --batch_size <batch_size>`␍
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python dcgan.py --mode train --path ~/images --batch_size 128␍
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**Image generation:**␍
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`python dcgan.py --mode generate --batch_size <batch_size> --nice` : top 5% images according to discriminator␍
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python dcgan.py --mode generate --batch_size 128␍
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## Result␍
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**generated images :** **␍
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![generated_image.png](.\assets\generated_image.png)␍
![generated_image.png](./assets/generated_image.png)␍
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![nice_generated_image.png](.\assets\nice_generated_image.png)␍
![nice_generated_image.png](./assets/nice_generated_image.png)␍
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**train process :**␍
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![training_process.gif](.\assets\training_process.gif)␍
![training_process.gif](./assets/training_process.gif)␍
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