93 lines
2.4 KiB
Python
93 lines
2.4 KiB
Python
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import torch.utils.data
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from lib.train.data.image_loader import jpeg4py_loader
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class BaseImageDataset(torch.utils.data.Dataset):
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""" Base class for image datasets """
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def __init__(self, name, root, image_loader=jpeg4py_loader):
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"""
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args:
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root - The root path to the dataset
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image_loader (jpeg4py_loader) - The function to read the images. jpeg4py (https://github.com/ajkxyz/jpeg4py)
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is used by default.
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"""
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self.name = name
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self.root = root
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self.image_loader = image_loader
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self.image_list = [] # Contains the list of sequences.
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self.class_list = []
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def __len__(self):
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""" Returns size of the dataset
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returns:
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int - number of samples in the dataset
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"""
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return self.get_num_images()
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def __getitem__(self, index):
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""" Not to be used! Check get_frames() instead.
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"""
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return None
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def get_name(self):
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""" Name of the dataset
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returns:
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string - Name of the dataset
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"""
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raise NotImplementedError
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def get_num_images(self):
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""" Number of sequences in a dataset
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returns:
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int - number of sequences in the dataset."""
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return len(self.image_list)
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def has_class_info(self):
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return False
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def get_class_name(self, image_id):
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return None
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def get_num_classes(self):
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return len(self.class_list)
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def get_class_list(self):
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return self.class_list
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def get_images_in_class(self, class_name):
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raise NotImplementedError
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def has_segmentation_info(self):
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return False
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def get_image_info(self, seq_id):
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""" Returns information about a particular image,
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args:
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seq_id - index of the image
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returns:
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Dict
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"""
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raise NotImplementedError
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def get_image(self, image_id, anno=None):
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""" Get a image
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args:
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image_id - index of image
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anno(None) - The annotation for the sequence (see get_sequence_info). If None, they will be loaded.
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returns:
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image -
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anno -
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dict - A dict containing meta information about the sequence, e.g. class of the target object.
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"""
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raise NotImplementedError
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