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