| import os.path as osp |
| import numpy as np |
| import numpy.random as npr |
| import PIL |
| import cv2 |
|
|
| import torch |
| import torchvision |
| import xml.etree.ElementTree as ET |
| import json |
| import copy |
|
|
| from ...cfg_holder import cfg_unique_holder as cfguh |
|
|
| def singleton(class_): |
| instances = {} |
| def getinstance(*args, **kwargs): |
| if class_ not in instances: |
| instances[class_] = class_(*args, **kwargs) |
| return instances[class_] |
| return getinstance |
|
|
| @singleton |
| class get_loader(object): |
| def __init__(self): |
| self.loader = {} |
|
|
| def register(self, loadf): |
| self.loader[loadf.__name__] = loadf |
|
|
| def __call__(self, cfg): |
| if cfg is None: |
| return None |
| if isinstance(cfg, list): |
| loader = [] |
| for ci in cfg: |
| t = ci.type |
| loader.append(self.loader[t](**ci.args)) |
| return compose(loader) |
| t = cfg.type |
| return self.loader[t](**cfg.args) |
|
|
| class compose(object): |
| def __init__(self, loaders): |
| self.loaders = loaders |
|
|
| def __call__(self, element): |
| for l in self.loaders: |
| element = l(element) |
| return element |
| |
| def __getitem__(self, idx): |
| return self.loaders[idx] |
|
|
| def register(): |
| def wrapper(class_): |
| get_loader().register(class_) |
| return class_ |
| return wrapper |
|
|
| def pre_loader_checkings(ltype): |
| lpath = ltype+'_path' |
| |
| lcache = ltype+'_cache' |
| def wrapper(func): |
| def inner(self, element): |
| if lcache in element: |
| |
| data = element[lcache] |
| else: |
| if ltype in element: |
| raise ValueError |
| if lpath not in element: |
| raise ValueError |
|
|
| if element[lpath] is None: |
| data = None |
| else: |
| data = func(self, element[lpath], element) |
| element[ltype] = data |
|
|
| if ltype == 'image': |
| if isinstance(data, np.ndarray): |
| imsize = data.shape[-2:] |
| elif isinstance(data, PIL.Image.Image): |
| imsize = data.size[::-1] |
| elif isinstance(data, torch.Tensor): |
| imsize = [data.size(-2), data.size(-1)] |
| elif data is None: |
| imsize = None |
| else: |
| raise ValueError |
| element['imsize'] = imsize |
| element['imsize_current'] = copy.deepcopy(imsize) |
| return element |
| return inner |
| return wrapper |
|
|
