def __init__(self, config=Encoder_Localizer_config(),
crop_size=(0.5, 0.5)):
super(Encoder_Recovery, self).__init__()
self.config = config
device = config.device
self.encoder = EncoderNetwork(is_embed_message=False,
config=config).to(device)
self.other_noise_layers = [Identity()]
self.other_noise_layers.append(JpegCompression(device))
self.other_noise_layers.append(Quantization(device))
def __init__(self, noise_layers: list, device):
super(Noiser, self).__init__()
self.noise_layers = [Identity()]
for layer in noise_layers:
if type(layer) is str:
if layer == 'JpegPlaceholder':
#self.noise_layers.append(JpegCompression(device))
self.noise_layers.append(Jpeg(device, [70, 95]))
elif layer == 'QuantizationPlaceholder':
self.noise_layers.append(Quantization(device))
else:
raise ValueError(f'Wrong layer placeholder string in Noiser.__init__().'
f' Expected "JpegPlaceholder" or "QuantizationPlaceholder" but got {layer} instead')
else:
self.noise_layers.append(layer)
def __init__(self, device, jpeg_type='jpeg2'):
super(Combined2, self).__init__()
self.identity = Identity()
if jpeg_type == 'jpeg2':
self.jpeg = JpegCompression2()
elif jpeg_type == 'jpeg':
self.jpeg = JpegCompression(device)
elif jpeg_type == 'diff_jpeg':
self.jpeg = DiffJPEG()
else:
self.jpeg = Quantization()
self.dropout = Dropout([0.3, 0.3])
self.gaussian = Gaussian()
self.crop2 = Crop2(
[0.187, 0.187],
[0.187, 0.187]) # Crop2([0.547, 0.547], [0.547, 0.547])
self.cropout = Cropout([0.547, 0.547], [0.547, 0.547])
def __init__(self, noise_config: list, device: torch.device):
super(Noiser, self).__init__()
self.noise_config = noise_config
noise_layers = []
for noise_layer_config in noise_config:
layer_type = noise_layer_config['type'].lower()
if layer_type == 'jpeg_compression':
# TODO: Add jpeg compression level as a config option
noise_layers.append(JpegCompression(device))
elif layer_type == 'crop':
noise_layers.append(
Crop(noise_layer_config['height_ratios'],
noise_layer_config['width_ratios']))
elif layer_type == 'cropout':
noise_layers.append(
Cropout(noise_layer_config['height_ratios'],
noise_layer_config['width_ratios']))
elif layer_type == 'dropout':
noise_layers.append(
Dropout(noise_layer_config['keep_ratio_range']))
elif layer_type == 'resize':
if 'interpolation_method' in noise_layer_config:
noise_layers.append(
Resize(noise_layer_config['resize_ratio_range'],
noise_layer_config['interpolation_method']))
else:
noise_layers.append(
Resize(noise_layer_config['resize_ratio_range']))
elif layer_type == 'rotate':
pass
elif layer_type == 'identity':
noise_layers.append(Identity())
elif layer_type == 'quantization':
noise_layers.append(Quantization())
else:
raise ValueError('Noise layer of {} not supported'.format(
noise_layer_config['type']))
self.noise_layers = nn.Sequential(*noise_layers)