CSVDatasetClassification
- class easypl.datasets.classification.csv.CSVDatasetClassification(csv_path: str, image_prefix: str = '', path_transform: Optional[Callable] = None, transform=None, return_label: bool = True, image_column: Optional[str] = None, target_columns: Optional[Union[str, List[str]]] = None)
Csv dataset for classfication
- csv_path
path to csv file with paths of images
- Type:
str
- return_label
if True return dict with two keys (image, target), else return dict with one key (image)
- Type:
bool
- image_column
column name or None. If None then will be getting the first column
- Type:
Optional[str]
- target_columns
column name/names or None. If None then will be getting all but the first column
- Type:
Optional[Union[str, List[str]]]
- image_prefix
path prefix which will be added to paths of images in csv file
- Type:
str
- path_transform
None or function for transform of path. Will be os.path.join(image_prefix, path_transform(image_path))
- Type:
Optional[Callable]
- transform
albumentations transform class or None
- Type:
Optional
- __len__() int
Return length of dataset
- Return type:
int