def __init__(self, impath='', label=0, domain=-1, classname=''):
assert isinstance(impath, str)
assert isinstance(label, int)
assert isinstance(domain, int)
assert isinstance(classname, str)
assert check_isfile(impath)
self._impath = impath
self._label = label
self._domain = domain
self._classname = classname
def parse_dir(directory, end_signal, regex_acc, regex_err, args):
print('Parsing {}'.format(directory))
subdirs = listdir_nohidden(directory, sort=True)
valid_fpaths = []
valid_accs = []
valid_errs = []
for subdir in subdirs:
fpath = osp.join(directory, subdir, 'log.txt')
assert check_isfile(fpath)
good_to_go = False
with open(fpath, 'r') as f:
lines = f.readlines()
for line in lines:
line = line.strip()
if line == end_signal:
good_to_go = True
match_acc = regex_acc.search(line)
if match_acc and good_to_go:
acc = float(match_acc.group(1))
valid_accs.append(acc)
valid_fpaths.append(fpath)
match_err = regex_err.search(line)
if match_err and good_to_go:
err = float(match_err.group(1))
valid_errs.append(err)
for fpath, acc, err in zip(valid_fpaths, valid_accs, valid_errs):
print('file: {}. acc: {:.2f}%. err: {:.2f}%'.format(fpath, acc, err))
acc_mean = np.mean(valid_accs)
acc_std = compute_ci95(valid_accs) if args.ci95 else np.std(valid_accs)
err_mean = np.mean(valid_errs)
err_std = compute_ci95(valid_errs) if args.ci95 else np.std(valid_errs)
print('===')
print('outcome of directory: {}'.format(directory))
if args.res_format in ['acc', 'acc_and_err']:
print('* acc: {:.2f}% +- {:.2f}%'.format(acc_mean, acc_std))
if args.res_format in ['err', 'acc_and_err']:
print('* err: {:.2f}% +- {:.2f}%'.format(err_mean, err_std))
print('===')
return acc_mean, err_mean
def check_cfg(self, cfg):
assert check_isfile(cfg.MODEL.INIT_WEIGHTS
), 'The weights of source model must be provided'