def main(argv):
global config
if not config.test:
train(config)
if config.weights == -1:
config = add_to_config(config, 'weights', config.max_epoch)
else:
config = add_to_config(config, 'weights', config.max_epoch + config.weights)
config = add_to_config(config, 'test', True)
eval_alone(config)
def main(argv):
global config
with open(config.log_file, 'w') as f:
print('STARTING')
print('STARTING', file=f)
if not config.test:
train(config)
if config.weights == -1:
config = add_to_config(config, 'weights', config.max_epoch)
else:
config = add_to_config(config, 'weights', config.max_epoch + config.weights)
config = add_to_config(config, 'test', True)
eval_alone(config)
highest_model_saved = it
ACC_LOGGER.plot(dest=config.log_dir)
LOSS_LOGGER.plot(dest=config.log_dir)
print("LOSS: ", np.mean(losses))
print("ACCURACY", np.mean(accs))
if __name__ == '__main__':
config = get_config()
caffe.set_device(0)
caffe.set_mode_gpu()
data_size = get_dataset_size(config, 'train')
prepare_solver_file(data_size=data_size)
solver = caffe.get_solver(config.solver)
if not config.test:
LOSS_LOGGER = Logger("{}_loss".format(config.name))
ACC_LOGGER = Logger("{}_acc".format(config.name))
train(config, solver)
config = add_to_config(config, 'test', True)
snapshot = get_highest_model(config)
solver.restore(snapshot)
caffemodel = os.path.splitext(snapshot)[0] + '.caffemodel'
solver.net.copy_from(caffemodel)
solver.test_nets[0].copy_from(caffemodel)
print('Model restored')
eval(config, solver)
config = get_config()
with open(config.log_file, 'w') as f:
print("STARTING CONVERSION", file=f)
try:
if config.dataset_type == "shapenet":
from Shapenet import *
elif config.dataset_type == "modelnet":
from Modelnet import *
categories, split, cat_names = get_metadata(config.data)
write_cat_names(config.data, config.output)
if config.dataset_type == "shapenet":
files = get_files_list(config.data, categories)
config = add_to_config(config, 'fov', 35)
elif config.dataset_type == "modelnet":
files = find_files(config.data, 'off')
pool = Pool(processes=config.num_threads)
#pool.map(off2obj, files)
pool.close()
pool.join()
files = find_files(config.data, 'obj')
config = add_to_config(config, 'fov', 70)
config = add_to_config(config, 'cat_names', cat_names)
except:
e = sys.exc_info()
with open(config.log_file, 'a') as f:
print("Exception occured while reading files.", file=f)
print("Exception {}".format(e), file=f)
sys.exit(1)
predictions = list(pred_array)
log(
config.log_file,
'EVALUTAION: epoch: {0:^3d}, loss: {2:.6f}, acc: {3:.5f}'.format(
epoch, loss, acc))
if not config.test:
LOSS_LOGGER.log(loss, epoch, "eval_loss")
ACC_LOGGER.log(acc, epoch, "eval_accuracy")
else:
import Evaluation_tools as et
eval_file = os.path.join(config.log_dir, '{}.txt'.format(config.name))
et.write_eval_file(config.data, eval_file, predictions, labels,
config.name)
et.make_matrix(config.data, eval_file, config.log_dir)
if __name__ == '__main__':
config = get_config()
if not config.test:
LOSS_LOGGER = Logger("{}_loss".format(config.name))
ACC_LOGGER = Logger("{}_acc".format(config.name))
train(config)
if config.weights == -1:
config = add_to_config(config, 'weights', config.max_epoch)
else:
config = add_to_config(config, 'weights',
config.max_epoch + config.weights)
config = add_to_config(config, 'test', True)
test(config)
elif config.dataset_type == "modelnet":
from Modelnet import *
categories, split, cat_names = get_metadata(config.data)
write_cat_names(config.data, config.output)
if config.dataset_type == "shapenet":
files = get_files_list(config.data, categories)
elif config.dataset_type == "modelnet":
files = find_files(config.data, 'off')
pool = Pool(processes=config.num_threads)
pool.map(off2obj, files)
pool.close()
pool.join()
files = find_files(config.data, 'obj')
config = add_to_config(config, 'cat_names', cat_names)
except:
e = sys.exc_info()
with open(config.log_file, 'a') as f:
print("Exception occured while reading files.", file=f)
print("Exception {}".format(e), file=f)
sys.exit(1)
def exists(file):
id = get_file_id(file)
cat = categories[id]
cat_name = cat_names[cat]
dataset = coding[split[id]]
whole_path = os.path.join(config.output, cat_name, dataset, id)
for view in range(config.num_views):
if not os.path.exists(get_name_of_image_file(whole_path, id,
os.path.join(config.output, "{}.npz".format(dataset)))
def log(file, log_string):
with open(file, 'a') as f:
print(log_string)
print(log_string, file=f)
if __name__ == '__main__':
config = get_config()
with open(config.log_file, 'w') as f:
print("STARTING CONVERSION", file=f)
try:
ROT_MATRIX = create_ROT_MATRIX(config.num_rotations)
config = add_to_config(config, 'matrix', ROT_MATRIX)
if config.dataset_type == "shapenet":
from Shapenet import *
elif config.dataset_type == "modelnet":
from Modelnet import *
categories, split, cat_names = get_metadata(config.data)
files = get_files_list(config.data, categories)
write_cat_names(config.data, config.output)
except:
err_string = traceback.format_exc()
log(config.log_file, "Exception occured while reading files.")
log(config.log_file, err_string)
sys.exit(1)
def cli(add, rm, show, all, dotfiles, configs, packages, fonts, old_path,
new_path, remote, reinstall_all, reinstall_configs, reinstall_dots,
reinstall_fonts, reinstall_packages, delete_config, destroy_backup, v):
"""
Easily back up installed packages, dotfiles, and more.
You can edit which dotfiles are backed up in ~/.shallow-backup.
Written by Aaron Lichtman (@alichtman).
"""
# Process CLI args
admin_action = any([v, delete_config, destroy_backup, show, rm
]) or None not in add
has_cli_arg = any([
old_path, all, dotfiles, packages, fonts, configs, reinstall_dots,
reinstall_fonts, reinstall_all, reinstall_configs, reinstall_packages
])
skip_prompt = any([
all, dotfiles, configs, packages, fonts, reinstall_packages,
reinstall_configs, reinstall_dots, reinstall_fonts
])
# Perform administrative action and exit.
if admin_action:
if v:
print_version_info()
elif delete_config:
# TODO: Error checking.
os.remove(get_config_path())
print_red_bold("Removed config file...")
elif destroy_backup:
backup_home_path = get_config()["backup_path"]
destroy_backup_dir(backup_home_path)
elif None not in add:
add_to_config(add[0], add[1])
elif rm:
rm_from_config(rm)
elif show:
show_config()
sys.exit()
# Start CLI
splash_screen()
safe_create_config()
backup_config = get_config()
# User entered a new path, so update the config
if new_path:
abs_path = os.path.abspath(new_path)
print(Fore.BLUE + Style.NORMAL +
"\nUpdating shallow-backup path to -> " + Style.BRIGHT +
"{}".format(abs_path) + Style.RESET_ALL)
backup_config["backup_path"] = abs_path
write_config(backup_config)
# User didn't enter any CLI args so prompt for path update before showing menu
elif not has_cli_arg:
prompt_for_path_update(backup_config)
# Create backup directory and do git setup
backup_home_path = get_config()["backup_path"]
mkdir_warn_overwrite(backup_home_path)
repo, new_git_repo_created = safe_git_init(backup_home_path)
# Create default gitignore if we just ran git init
if new_git_repo_created:
safe_create_gitignore(backup_home_path)
# Prompt user for remote URL
if not remote:
prompt_for_git_url(repo)
# Set remote URL from CLI arg
if remote:
git_set_remote(repo, remote)
dotfiles_path = os.path.join(backup_home_path, "dotfiles")
configs_path = os.path.join(backup_home_path, "configs")
packages_path = os.path.join(backup_home_path, "packages")
fonts_path = os.path.join(backup_home_path, "fonts")
# Command line options
if skip_prompt:
if reinstall_packages:
reinstall_packages_sb(packages_path)
elif reinstall_configs:
reinstall_configs_sb(configs_path)
elif reinstall_fonts:
reinstall_fonts_sb(fonts_path)
elif reinstall_dots:
reinstall_dots_sb(dotfiles_path)
elif reinstall_all:
reinstall_all_sb(dotfiles_path, packages_path, fonts_path,
configs_path)
elif all:
backup_all(dotfiles_path,
packages_path,
fonts_path,
configs_path,
skip=True)
git_add_all_commit_push(repo, "all")
elif dotfiles:
backup_dotfiles(dotfiles_path, skip=True)
git_add_all_commit_push(repo, "dotfiles")
elif configs:
backup_configs(configs_path, skip=True)
git_add_all_commit_push(repo, "configs")
elif packages:
backup_packages(packages_path, skip=True)
git_add_all_commit_push(repo, "packages")
elif fonts:
backup_fonts(fonts_path, skip=True)
git_add_all_commit_push(repo, "fonts")
# No CL options, show action menu and process selected option.
else:
selection = actions_menu_prompt().lower().strip()
selection_words = selection.split()
if selection.startswith("back up"):
if selection_words[-1] == "all":
backup_all(dotfiles_path, packages_path, fonts_path,
configs_path)
git_add_all_commit_push(repo, selection_words[-1])
elif selection_words[-1] == "dotfiles":
backup_dotfiles(dotfiles_path)
git_add_all_commit_push(repo, selection_words[-1])
elif selection_words[-1] == "configs":
backup_configs(configs_path)
git_add_all_commit_push(repo, selection_words[-1])
elif selection_words[-1] == "packages":
backup_packages(packages_path)
git_add_all_commit_push(repo, selection_words[-1])
elif selection_words[-1] == "fonts":
backup_fonts(fonts_path)
git_add_all_commit_push(repo, selection_words[-1])
elif selection.startswith("reinstall"):
if selection_words[-1] == "packages":
reinstall_packages_sb(packages_path)
elif selection_words[-1] == "configs":
reinstall_configs_sb(configs_path)
elif selection_words[-1] == "fonts":
reinstall_fonts_sb(fonts_path)
elif selection_words[-1] == "dotfiles":
reinstall_dots_sb(dotfiles_path)
elif selection_words[-1] == "all":
reinstall_all_sb(dotfiles_path, packages_path, fonts_path,
configs_path)
else:
if selection == "show config":
show_config()
elif selection == "destroy backup":
if prompt_yes_no(
"Erase backup directory: {}?".format(backup_home_path),
Fore.RED):
destroy_backup_dir(backup_home_path)
else:
print_red_bold(
"Exiting to prevent accidental deletion of backup directory."
)
sys.exit()
config = get_config()
prepare_data(os.path.join(config.data, 'train.txt'),
views=config.num_views,
shuffle=True)
prepare_data(os.path.join(config.data, 'test.txt'),
views=config.num_views,
shuffle=False)
caffe.set_device(0)
caffe.set_mode_gpu()
data_size = get_dataset_size(config, 'trainrotnet')
prepare_solver_file(data_size=data_size)
solver = caffe.get_solver(config.solver)
if not config.test:
LOSS_LOGGER = Logger("{}_loss".format(config.name))
ACC_LOGGER = Logger("{}_acc".format(config.name))
train(config, solver)
config = add_to_config(config, 'weights', highest_model_saved)
config = add_to_config(config, 'test', True)
snapshot = get_highest_model(config)
solver.restore(snapshot)
caffemodel = os.path.splitext(snapshot)[0] + '.caffemodel'
solver.net.copy_from(caffemodel)
solver.test_nets[0].copy_from(caffemodel)
print('Model restored')
eval(config, solver)
print('Starting', file=f)
prepare_data(os.path.join(config.data, 'train.txt'),
views=config.num_views,
shuffle=True)
prepare_data(os.path.join(config.data, 'test.txt'),
views=config.num_views,
shuffle=False)
caffe.set_device(0)
caffe.set_mode_gpu()
data_size = get_dataset_size(os.path.join(config.data, 'trainrotnet.txt'))
prepare_solver_file(data_size=data_size)
solver = caffe.get_solver(config.solver)
if not config.test:
LOSS_LOGGER = Logger("{}_loss".format(config.name))
ACC_LOGGER = Logger("{}_acc".format(config.name))
train(config, solver)
config = add_to_config(config, 'weights', get_highest_model(config))
config = add_to_config(config, 'test', True)
snapshot = get_highest_model(config)
solver.restore(snapshot)
caffemodel = os.path.splitext(snapshot)[0] + '.caffemodel'
solver.net.copy_from(caffemodel)
solver.test_nets[0].copy_from(caffemodel)
log(config.log_file, 'Model restored')
eval(config, solver)
