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data-augmentation-using-deep-convolutional-gan's Introduction

Face Generation using Deep Convolutional Generative Adversarial Network

This repository contains code to generate faces from the given celebrity dataset

Steps to run the code

  1. Git clone the folder.
  2. Download and extract the celeb dataset into data folder.
  3. Run python train.py from terminal.

You can also use this code for data augmentation just replace the celeb dataset with your dataset folder. Although GAN's have been found to be unstable while training re running the same code with same or different parameters will give you different resutls.

Results: Fake images

References:

GAN
Data Augmentation
Pytorch tutorial

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data-augmentation-using-deep-convolutional-gan's Issues

Error while training

Set no of workers to 0
as for 5 it is showing BrokenPipeError: [Errno 32] Broken pipe

But getting this error:

File "D:\Project\Image extraction\Data-Augmentation-using-Deep-Convolutional-GAN-master\Data-Augmentation-using-Deep-Convolutional-GAN-master\train.py", line 161, in
train()

File "D:\Project\Image extraction\Data-Augmentation-using-Deep-Convolutional-GAN-master\Data-Augmentation-using-Deep-Convolutional-GAN-master\train.py", line 99, in train
label = torch.full((b_size,), real_label, device=device)

RuntimeError: Providing a bool or integral fill value without setting the optional dtype or out arguments is currently unsupported. In PyTorch 1.7, when dtype and out are not set a bool fill value will return a tensor of torch.bool dtype, and an integral fill value will return a tensor of torch.long dtype.

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