torchsat.datasets package

Submodules

torchsat.datasets.eurosat module

class torchsat.datasets.eurosat.EuroSAT(root, mode='RGB', download=False, **kwargs)

Bases: torchsat.datasets.folder.DatasetFolder

download()

url_allband = 'http://madm.dfki.de/files/sentinel/EuroSATallBands.zip'

url_rgb = 'http://madm.dfki.de/files/sentinel/EuroSAT.zip'

torchsat.datasets.folder module

class torchsat.datasets.folder.ChangeDetectionDataset(root, extentions='jpg', transforms=None)

Bases: torch.utils.data.dataset.Dataset

A generic data loader where the images are arranged in this way: ::

.

├── train │ ├── pre │ │ ├── train_1.png │ │ ├── train_2.png │ │ ├── … │ ├── post │ │ ├── train_1.png │ │ ├── train_2.png │ │ ├── … │ └── label │ ├── train_1.png │ ├── train_2.png │ ├── … └── val

├── pre │ ├── val_10.png │ ├── val_11.png │ ├── … ├── post │ ├── val_10.png │ ├── val_11.png │ ├── … └── label

├── val_10.png ├── val_11.png ├── …

Args:

root (string): root dir of train or validate dataset. extensions (tuple or list): extention of training image.

class torchsat.datasets.folder.DatasetFolder(root, loader, extensions, classes=None, class_to_idx=None, transform=None, target_transform=None)

Bases: torch.utils.data.dataset.Dataset

A generic data loader where the samples are arranged in this way:

root/class_x/xxx.ext
root/class_x/xxy.ext
root/class_x/xxz.ext

root/class_y/123.ext
root/class_y/nsdf3.ext
root/class_y/asd932_.ext

Args:

root (string): Root directory path. loader (callable): A function to load a sample given its path. extensions (list[string]): A list of allowed extensions. classes (callable, optional): List of the class names. class_to_idx (callable, optional): Dict with items (class_name, class_index). transform (callable, optional): A function/transform that takes in

a sample and returns a transformed version. E.g, transforms.RandomCrop for images.

target_transform (callable, optional): A function/transform that takes

in the target and transforms it.

Attributes:

classes (list): List of the class names. class_to_idx (dict): Dict with items (class_name, class_index). samples (list): List of (sample path, class_index) tuples targets (list): The class_index value for each image in the dataset

class torchsat.datasets.folder.ImageFolder(root, transform=None, target_transform=None, loader=<function default_loader>, **kwargs)

Bases: torchsat.datasets.folder.DatasetFolder

A generic data loader where the images are arranged in this way:

root/dog/xxx.png
root/dog/xxy.png
root/dog/xxz.png

root/cat/123.png
root/cat/nsdf3.png
root/cat/asd932_.png

Args:

root (string): Root directory path. transform (callable, optional): A function/transform that takes in an PIL image

and returns a transformed version. E.g, transforms.RandomCrop

target_transform (callable, optional): A function/transform that takes in the

target and transforms it.

loader (callable, optional): A function to load an image given its path.

Attributes:

classes (list): List of the class names. class_to_idx (dict): Dict with items (class_name, class_index). imgs (list): List of (image path, class_index) tuples

class torchsat.datasets.folder.SegmentationDataset(root, extentions='jpg', transforms=None)

Bases: object

A generic data loader where the images are arranged in this way: ::

. ├── train │ ├── image │ │ ├── train_1.png │ │ ├── train_2.png │ │ ├── … │ └── label │ ├── train_1.png │ ├── train_2.png │ ├── … └── val

├── image │ ├── val_10.png │ ├── val_11.png │ ├── … └── label

├── val_10.png ├── val_11.png ├── …

Args:

root (string): root dir of train or validate dataset. extensions (tuple or list): extention of training image.

torchsat.datasets.folder.has_file_allowed_extension(filename, extensions)

Checks if a file is an allowed extension.

Args:

filename (string): path to a file extensions (iterable of strings): extensions to consider (lowercase)

Returns:

bool: True if the filename ends with one of given extensions

torchsat.datasets.folder.is_image_file(filename)

Checks if a file is an allowed image extension.

Args:

filename (string): path to a file

Returns:

bool: True if the filename ends with a known image extension

torchsat.datasets.folder.make_dataset(dir, class_to_idx, extensions)

torchsat.datasets.nwpu_resisc45 module

class torchsat.datasets.nwpu_resisc45.NWPU_RESISC45(root, download=False, **kwargs)

Bases: torchsat.datasets.folder.DatasetFolder

download()

url = 'https://sov8mq.dm.files.1drv.com/y4m_Fo6ujI52LiWHDzaRZVtkMIZxF7aqjX2q7KdVr329zVEurIO-wUjnqOAKHvHUAaoqCI0cjYlrlM7WCKVOLfjmUZz6KvN4FmV93qsaNIB9C8VN2AHp3JXOK-l1Dvqst8HzsSeOs-_5DOYMYspalpc1rt_TNAFtUQPsKylMWcdUMQ_n6SHRGRFPwJmSoJUOrOk2oXe9D7CPEq5cq9S9LI8hA/NWPU-RESISC45.rar?download&psid=1'

torchsat.datasets.patternnet module

class torchsat.datasets.patternnet.PatternNet(root, download=False, **kwargs)

Bases: torchsat.datasets.folder.DatasetFolder

download()

url = 'https://doc-0k-9c-docs.googleusercontent.com/docs/securesc/s4mst7k8sdlkn5gslv2v17dousor99pe/5kjb9nqbn6uv3dnpsqu7n7vbc2sjkm9n/1553925600000/13306064760021495251/10775530989497868365/127lxXYqzO6Bd0yZhvEbgIfz95HaEnr9K?e=download'

torchsat.datasets.sat module

class torchsat.datasets.sat.SAT(root, mode='SAT-4', image_set='train', download=False, transform=False, target_transform=False)

Bases: torch.utils.data.dataset.Dataset

SAT-4 and SAT-6 datasets

Arguments:

data {root} – [description]

Raises:

ValueError – [description] ValueError – [description]

Returns:

[type] – [description]

classes_sat4 = {'barren land': 0, 'grassland': 2, 'none': 3, 'trees': 1}

classes_sat6 = {'barren land': 1, 'building': 0, 'grassland': 3, 'road': 4, 'trees': 2, 'water': 5}

download()

torchsat.datasets.utils module

torchsat.datasets.utils.accimage_loader(path)

torchsat.datasets.utils.default_loader(path)

torchsat.datasets.utils.download_url(url, root, filename=None, md5=None)

Download a file from a url and place it in root. Args:

url (str): URL to download file from root (str): Directory to place downloaded file in filename (str, optional): Name to save the file under. If None, use the basename of the URL md5 (str, optional): MD5 checksum of the download. If None, do not check

torchsat.datasets.utils.gen_bar_updater()

torchsat.datasets.utils.image_loader(path)

torchsat.datasets.utils.pil_loader(path)

torchsat.datasets.utils.tifffile_loader(path)

Module contents