2799b271367c6d73b8f2fc5effef67d011e1991c,GANs/stylegan2/generate.py,,main,#,98

Before Change

        style_noises = [nn.Variable((batch_size, 512)).apply(d=z)
                        for _ in range(args.mix_after)]
        style_noises += [nn.Variable((batch_size, 512)).apply(d=z2)
                         for _ in range(num_layers - args.mix_after)]
    else:
        // no style mixing (single noise / style is used)
        print(f"using style noise seed {args.seed} for entire layers.")

After Change

        print(f"using style noise seed {args.seed_mix} for layers {args.mix_after}-{num_layers}.")
        rnd = np.random.RandomState(args.seed_mix)
        z2 = rnd.randn(batch_size, 512)
        style_noises = [nn.NdArray.from_numpy_array(z)]
        style_noises += [nn.NdArray.from_numpy_array(z2)]
    else:
        // no style mixing (single noise / style is used)
        print(f"using style noise seed {args.seed} for entire layers.")
        style_noises = [nn.NdArray.from_numpy_array(z) for _ in range(2)]

    nn.set_auto_forward(True)
    nn.load_parameters("styleGAN2_G_params.h5")
    rgb_output = generate(batch_size, style_noises,
                          args.stochastic_seed, args.mix_after, args.truncation_psi)

    // convert to uint8 to save an image file
    image = convert_images_to_uint8(rgb_output, drange=[-1, 1])
    if args.output_filename is None:
        if not args.mixing:
            filename = f"seed{args.seed}"
        else:
            filename = f"seed{args.seed}_{args.seed_mix}"
    else:
        filename = args.output_filename

    os.makedirs(args.output_dir, exist_ok=True)
    
    for i in range(batch_size):
        filepath = os.path.join(args.output_dir, f"{filename}_{i}.png")
        imsave(filepath, image[i], channel_first=True)
        print(f"Genetation completed. Saved {filepath}.")


if __name__ == "__main__":
    main()

Instances