cvdatasets/cvdatasets/utils/__init__.py

import numpy as np

try:
	from yaml import CLoader as Loader, CDumper as Dumper
except ImportError:
	from yaml import Loader, Dumper

import yaml

from os.path import isfile

def feature_file_name(subset, part_info, model_info):

	return "{subset}{suffix}.{model}.npz".format(
			subset=subset,
			suffix=part_info.feature_suffix,
			model=model_info.folder)

def read_info_file(fpath):
	with open(fpath) as f:
		return attr_dict(yaml.load(f, Loader=Loader))

def random_idxs(idxs, rnd=None, n_parts=None):

	if rnd is None or isinstance(rnd, int):
		rnd = np.random.RandomState(rnd)
	else:
		assert isinstance(rnd, np.random.RandomState), \
			"'rnd' should be either a random seed or a RandomState instance!"

	n_parts = n_parts or rnd.randint(1, len(idxs))
	res = rnd.choice(idxs, n_parts, replace=False)
	res.sort()
	return res

class attr_dict(dict):
	def __getattr__(self, name):
		if name in self:
			return self[name]
		else:
			return super(attr_dict, self).get(name)

	def __getitem__(self, key):
		res = super(attr_dict, self).__getitem__(key)

		if isinstance(res, dict):
			return attr_dict(res)
		return res

	def __getstate__(self): return self.__dict__

	def __setstate__(self, d): self.__dict__.update(d)


class _MetaInfo(object):
	def __init__(self, **kwargs):
		for name, value in kwargs.items():
			setattr(self, name, value)
		self.structure = []


from .image import asarray, dimensions
from .dataset import new_iterator