super_gradients.training.datasets.detection_datasets package
Submodules
super_gradients.training.datasets.detection_datasets.coco_detection module
super_gradients.training.datasets.detection_datasets.detection_dataset module
- class super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet(root: str, list_file: str, img_size: int = 416, batch_size: int = 16, augment: bool = False, dataset_hyper_params: Optional[dict] = None, cache_labels: bool = False, cache_images: bool = False, sample_loading_method: str = 'default', collate_fn: Optional[Callable] = None, target_extension: str = '.txt', labels_offset: int = 0, class_inclusion_list=None, all_classes_list=None)[source]
Bases:
Generic
[torch.utils.data.dataset.T_co
]- static augment_hsv(img, hgain=0.5, sgain=0.5, vgain=0.5)[source]
- Parameters
img –
- param hgain
- param sgain
- param vgain
- Returns
- static box_candidates(box1, box2, wh_thr=2, ar_thr=20, area_thr=0.1)[source]
- compute candidate boxes
- param box1
before augment
- param box2
after augment
- param wh_thr
wh_thr (pixels)
- param ar_thr
aspect_ratio_thr
- param area_thr
area_ratio
- Returns
- static letterbox(img, new_shape=(416, 416), color=(128, 128, 128), auto=True, scaleFill=False, scaleup=True, interp=3) → tuple[source]
letterbox - Resizes image to a 32-pixel-multiple rectangle :param img: :param new_shape: :param color: :param auto: :param scaleFill: :param scaleup: :param interp: :return:
- load_mosaic(index)[source]
- load_mosaic - Load images in mosaic format to improve noise handling while training
- param index
- return
- random_perspective(img, targets=(), degrees=10, translate=0.1, scale=0.1, shear=10, border=0, perspective=0)[source]
random images and labels using a perspective transform
- static sample_loader(sample_path: str)[source]
- sample_loader - Loads a coco dataset image from path
- param sample_path
- return
- static sample_post_process(image)[source]
- sample_post_process - Normalizes and orders the image to be 3 x img_size x img_size
- param image
- return
- static target_loader(target_path: str, class_inclusion_list=None, all_classes_list=None)[source]
- coco_target_loader
@param target_path: str, path to target. @param all_classes_list: list(str) containing all the class names or None when subclassing is disabled. @param class_inclusion_list: list(str) containing the subclass names or None when subclassing is disabled.
super_gradients.training.datasets.detection_datasets.pascal_voc_detection module
- class super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet(samples_sub_directory, targets_sub_directory, *args, **kwargs)[source]
Bases:
Generic
[torch.utils.data.dataset.T_co
]PascalVOC2012DtectionDataSet - Detection Data Set Class pascal_voc Data Set