sconce.datasets package¶
sconce.datasets.csv_image_folder module¶
-
class
sconce.datasets.csv_image_folder.
CsvImageFolder
(root, csv_path, filename_key='image_name', classes_key='tags', csv_delimiter=',', classes_delimiter=' ', loader=<function default_loader>, extensions=['.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm', '.tif'], transform=None, target_transform=<class 'sconce.transforms.NHot'>)[source]¶ Bases:
torch.utils.data.dataset.Dataset
A Dataset that reads images from a folder and classes from a csv file.
Parameters: - root (string) – directory where the images can be found.
- csv_path (string) – the path to the csv file containing image filenames and classes.
- filename_key (string, optional) – the column header of the csv for the column that contains image filenames (without extensions).
- classes_key (string, optional) – the column header of the csv for the column that contains classes for each image.
- csv_delimiter (string, optional) – the character(s) used to separate fields in the csv file.
- loader (callable, optional) – a function to load a sample given its path.
- extensions (list[string], optinoal) – a list of allowed extensions. E.g,
['.jpg', '.tif']
- 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.
Variables: - class_to_idx (dict) – a dictionary mapping class names to indices.
- classes (list[string]) – the human readable names of the classes that images can belong to.
- paths (list[string]) – for each image, the path to the image on disk.
- targets (list[list[int]]) – for each image, a list of class indices to which that image belongs.
-
found_extensions
¶
-
num_classes
¶