DiscoGAN-pytorch
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carpedm20
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
Hello Sir, I downloaded your code and maps-dataset.. And when I started I met some error. ```python ... Traceback (most recent call last): File "main.py", line 41, in main(config) File...
Once I set '-- input_scale_size' not to 64, an error will be reported. It seems that the discriminator cannot adapt to the size of the input image. How did you...
Looks like you crash if width and height isn't equal on custom datasets. I worked around by forcing my 640x360 images to 640x640.
I get the following warning message; `[!] Sampled dataset from A and B have different # of data. Try resampling...` From what I understand it is not necessary that both...
Hello, please can you show how to test the final model on a single image Thank you Lafi
DiscoGAN paper they assert that "to avoid costly pairing, we address the task of discovering cross-domain relations given unpaired data" But, I don't know why this implementation of DiscoGAN requires...
Hi, I've been trying to run the example code (on the maps dataset): python main.py --dataset=maps --num_gpu=4 I get the error below related to the NCCL library. I'm trying to...
class Generator(nn.Module): def __init__(self, input_size, output_size, hidden_dims): super(Generator, self).__init__() self.layers = [] prev_dim = input_size for hidden_dim in hidden_dims: self.layers.append(nn.Linear(prev_dim, hidden_dim)) self.layers.append(nn.ReLU(True)) prev_dim = hidden_dim self.layers.append(nn.Linear(prev_dim, output_size)) self.layer_module = ListModule(*self.layers)...
