def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
'--input_dir',
type=str,
default='./out',
help='Directory path to the npy files. (default: %(default)s)')
parser.add_argument(
'--graph_dir',
type=str,
default='./graphs',
help='Directory path to the graphs output. (default: %(default)s)')
parser.add_argument('--model_path',
type=str,
required=True,
help='Path of the model. (required)')
parser.add_argument(
'--normalize',
action='store_true',
help=
'Boolean flag activating normalization of the confusion matrix. (default: False)'
)
args = parser.parse_args()
maybe_make_directory(args.input_dir)
maybe_make_directory(args.graph_dir)
return args
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str,
required=True, choices=['train', 'valid', 'test'],
help='Dataset to load the filenames pickle. (required) (default: %(default)s)')
parser.add_argument('--data_path', type=str,
required=True,
help='Directory path to the datasets. (required) (default: %(default)s)')
parser.add_argument('--input_dir', type=str,
default='./out',
help='Directory path to the pickle files. (default: %(default)s)')
parser.add_argument('--output_dir', type=str,
default='./melspec',
help='Directory path to the melspectrograms output. (default: %(default)s)')
parser.add_argument('--n_mels', type=int,
default=128,
help='Number of Mel bands to generate. (default: %(default)s)')
parser.add_argument('--fmax', type=int,
default=8000,
help='Highest frequency (in Hz). (default: %(default)s)')
parser.add_argument('--hop_length', type=int,
default=1024,
help='Number of samples between successive frames. (default: %(default)s)')
args = parser.parse_args()
maybe_make_directory(args.input_dir)
maybe_make_directory(os.path.join(args.output_dir, args.dataset))
return args
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
'--data_path',
type=str,
default='../data/australian_user_reviews.json',
help='Directory path to the data. (default: %(default)s)')
parser.add_argument(
'--input_dir',
type=str,
default='reviews',
help='Directory path to the reviews. (default: %(default)s)')
parser.add_argument(
'--output_dir',
type=str,
default='bin',
help='Directory path to the pickle output. (default: %(default)s)')
parser.add_argument(
'--verbose',
action='store_true',
help='Boolean flag activating console prints. (default: False)')
args = parser.parse_args()
maybe_make_directory(args.output_dir)
return args
def minimize_with_adam(self, optimizer):
if self.verbose:
print('\nMINIMIZING LOSS USING: ADAM OPTIMIZER')
train_op = optimizer.minimize(self.total_loss)
init_op = tf.global_variables_initializer()
self.sess.run(init_op)
self.sess.run(self.net['input'].assign(self.init_img))
if self.write_iterations_adam:
out_dir = os.path.join(self.img_output_dir, self.img_name,
timestr.get_time())
maybe_make_directory(out_dir)
for iterations in range(self.max_iterations):
self.sess.run(train_op)
# write image at every iteration
if self.write_iterations_adam:
img_path = os.path.join(
out_dir, self.img_name + str(iterations) + '.png')
output_img = self.sess.run(self.net['input'])
write_image(img_path, output_img)
if iterations % self.print_iterations == 0 and self.verbose:
curr_loss = self.total_loss.eval()
print("At iterate {}\tf= {}".format(iterations, curr_loss[0]))
def save_feature_histogram(sess, model, image_path, layer):
image = cv2.resize(read_image(image_path), (model.input_shape[1], model.input_shape[0]))
image = preprocess(image)
feature_map = model.get_content_features(sess, image, [layer])[layer]
feature_map = np.ndarray.flatten(feature_map)
ax = sns.distplot(feature_map, kde=False, norm_hist=False)
ax.set_title('Layer: {}, mean: {}'.format(layer, feature_map.mean()))
ax.set_xlabel('activation_value')
ax.set_ylabel('number of activations')
maybe_make_directory('plots')
ax.get_figure().savefig('plots/{}.png'.format(layer))
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
'--input_dir',
type=str,
default='reviews',
help='Directory path to the reviews. (default: %(default)s)')
parser.add_argument(
'--output_dir',
type=str,
default='figures',
help='Directory path to the figures. (default: %(default)s)')
args = parser.parse_args()
maybe_make_directory(args.output_dir)
return args
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
'--data_path',
type=str,
default='../data/australian_user_reviews.json',
help='Directory path to the data. (default: %(default)s)')
parser.add_argument(
'--output_dir',
type=str,
default='reviews',
help='Directory path to the reviews. (default: %(default)s)')
args = parser.parse_args()
maybe_make_directory(args.output_dir)
return args
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
'--heuristic',
type=str,
required=True,
choices=['hc', 'hcr', 'sa'],
help=
'hc for Hill Climbing, hcr for Hill Climbing reduced, sa for simulated_annealing'
)
parser.add_argument(
'--filename',
type=str,
default='100sudoku.txt',
help=
'The filename containing sequence of 81 digits. (default: %(default)s)'
)
parser.add_argument(
'--verbose',
action='store_true',
help=
'Boolean flag indicating if statements should be printed to the console.'
)
parser.add_argument(
'--img_output_dir',
type=str,
default='./graphs_output',
help='Relative or absolute directory path to output image graphs.')
parser.add_argument(
'--results_dir',
type=str,
default='./results',
help='Relative or absolute directory path to data results.')
args = parser.parse_args()
maybe_make_directory(args.img_output_dir)
maybe_make_directory(args.results_dir)
return args
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str,
required=True, choices=['train', 'valid', 'test'],
help='Dataset to load melspectrograms and save as a npy. (required) (default: %(default)s)')
parser.add_argument('--resize', action='store_true',
help='Boolean flag activating resize of melspectrograms (default: False)')
parser.add_argument('--size', type=_size, nargs=1,
default='32,32',
help='Size must be height,width (default: (%(default)s))')
parser.add_argument('--input_dir', type=str,
default='./melspec',
help='Directory path to the melspectrograms. (default: %(default)s)')
parser.add_argument('--output_dir', type=str,
default='./out',
help='Directory path to the outputs. (default: %(default)s)')
parser.add_argument('--verbose', action='store_true',
help='Boolean flag activating console prints (default: False)')
args = parser.parse_args()
maybe_make_directory(args.output_dir)
return args
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
'--input_path',
type=str,
required=True,
help='Input path to a review. (required) (default: %(default)s)')
parser.add_argument(
'--output_dir',
type=str,
default='triples',
help='Directory path to the triples output. (default: %(default)s)')
parser.add_argument(
'--interval',
type=int,
nargs=2,
required=True,
help='Interval of lines to read. (default: %(default)s)')
args = parser.parse_args()
maybe_make_directory(args.output_dir)
return args
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--meta_name',
type=str,
default='meta_data.txt',
help='Configuration file output')
parser.add_argument(
'--content_img',
type=str,
required=True,
help='Filename of the content image (example: lion.jpg)')
parser.add_argument(
'--content_img_dir',
type=str,
default='./image_input',
help='Directory path to the content image. (default: %(default)s)')
parser.add_argument(
'--style_imgs',
nargs='+',
type=str,
required=True,
help='Filenames of the style images (example: starry-night.jpg)')
parser.add_argument(
'--style_imgs_weights',
nargs='+',
type=float,
default=[1.0],
help=
'Interpolation weights of each of the style images. (example: 0.5 0.5)'
)
parser.add_argument(
'--style_imgs_dir',
type=str,
default='./styles',
help='Directory path to the style images. (default: %(default)s)')
parser.add_argument(
'--init_img_type',
type=str,
default='content',
help='Image used to initialize the network. (default: %(default)s)')
parser.add_argument(
'--max_size',
type=int,
default=1920,
help=
'Maximum width or height of the input images. (default: %(default)s)')
parser.add_argument(
'--content_weight',
type=float,
default=5e0,
help='Weight for the content loss function. (default: %(default)s)')
parser.add_argument(
'--style_weight',
type=float,
default=1e4,
help='Weight for the style loss function. (default: %(default)s)')
parser.add_argument(
'--tv_weight',
type=float,
default=1e-3,
help=
'Weight for the total variational loss function. Set small (e.g. 1e-3). (default: %(default)s)'
)
parser.add_argument(
'--content_layers',
nargs='+',
type=str,
default=['conv4_2'],
help='VGG19 layers used for the content image. (default: %(default)s)')
parser.add_argument(
'--style_layers',
nargs='+',
type=str,
default=['relu1_1', 'relu2_1', 'relu3_1', 'relu4_1', 'relu5_1'],
help='VGG19 layers used for the style image. (default: %(default)s)')
parser.add_argument(
'--content_layer_weights',
nargs='+',
type=float,
default=[1.0],
help=
'Contributions (weights) of each content layer to loss. (default: %(default)s)'
)
parser.add_argument(
'--style_layer_weights',
nargs='+',
type=float,
default=[0.2, 0.2, 0.2, 0.2, 0.2],
help=
'Contributions (weights) of each style layer to loss. (default: %(default)s)'
)
parser.add_argument('--model_weights',
type=str,
default='imagenet-vgg-verydeep-19.mat',
help='Weights and biases of the VGG-19 network.')
parser.add_argument(
'--pooling_type',
type=str,
default='avg',
choices=['avg', 'max'],
help=
'Type of pooling in convolutional neural network. (default: %(default)s)'
)
parser.add_argument(
'--device',
type=str,
default='/gpu:0',
choices=['/gpu:0', '/cpu:0'],
help=
'GPU or CPU mode. GPU mode requires NVIDIA CUDA. (default|recommended: %(default)s)'
)
parser.add_argument(
'--img_output_dir',
type=str,
default='./image_output',
help='Relative or absolute directory path to output image and data.')
parser.add_argument('--img_name',
type=str,
default='result',
help='Filename of the output image.')
parser.add_argument(
'--verbose',
action='store_true',
help=
'Boolean flag indicating if statements should be printed to the console.'
)
parser.add_argument(
'--write_iterations_adam',
action='store_true',
help=
'Boolean flag indicating if output images should be written in every iteration under the Adam optimizer.'
)
parser.add_argument(
'--optimizer',
type=str,
default='lbfgs',
choices=['lbfgs', 'adam'],
help=
'Loss minimization optimizer. L-BFGS gives better results. Adam uses less memory. (default|recommended: %(default)s)'
)
parser.add_argument(
'--learning_rate',
type=float,
default=1e0,
help=
'Learning rate parameter for the Adam optimizer. (default: %(default)s)'
)
parser.add_argument(
'--max_iterations',
type=int,
default=300,
help=
'Max number of iterations for the Adam or L-BFGS optimizer. (default: %(default)s)'
)
parser.add_argument(
'--print_iterations',
type=int,
default=5,
help=
'Number of iterations between optimizer print statements. (default: %(default)s)'
)
args = parser.parse_args()
if args.write_iterations_adam and args.optimizer != 'adam':
parser.error('The optimizer argument should be adam')
# normalize weights
args.style_layer_weights = normalize(args.style_layer_weights)
args.content_layer_weights = normalize(args.content_layer_weights)
args.style_imgs_weights = normalize(args.style_imgs_weights)
maybe_make_directory(args.img_output_dir)
check_model(args.model_weights)
return args
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
'--dataset',
type=str,
required=True,
choices=['train', 'valid', 'test'],
help=
'Dataset to generate pickle of features. (required) (default: %(default)s)'
)
parser.add_argument(
'--data_path',
type=str,
required=True,
help='Directory path to the datasets. (required) (default: %(default)s)'
)
parser.add_argument(
'--output_dir',
type=str,
default='./out',
help='Directory path to the outputs. (default: %(default)s)')
parser.add_argument(
'--temp_avg',
action='store_true',
help=
'Boolean flag activating temporal averaging of features. (default: False)'
)
parser.add_argument(
'--sample',
action='store_true',
help=
'Boolean flag activating sampling of training set. (default: False)')
parser.add_argument(
'--n_samples',
type=int,
default=5000,
help=
'Number of samples to take from each instrument family. (default: %(default)s)'
)
parser.add_argument(
'--n_mfcc',
type=int,
default=13,
help='Number of MFCCs to return. (default: %(default)s)')
parser.add_argument(
'--n_mels',
type=int,
default=128,
help='Number of Mel bands to generate. (default: %(default)s)')
parser.add_argument(
'--fmax',
type=int,
default=8000,
help='Highest frequency (in Hz). (default: %(default)s)')
parser.add_argument(
'--hop_length',
type=int,
default=1024,
help=
'Number of samples between successive frames. (default: %(default)s)')
args = parser.parse_args()
maybe_make_directory(args.output_dir)
return args