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