qualia_core.dataset package

Submodules

Module contents

class qualia_core.dataset.BrainMIX(path: str)[source]: Bases: RawDataset

class qualia_core.dataset.CIFAR10(path: str = '', dtype: str = 'float32')[source]: Bases: RawDataset

class qualia_core.dataset.CORe50(path: str, variant: str, sessions: list[str] | None = None)[source]

Bases: RawDataset

CORe50 object recognition.

class Info(path: 'np.int32', session: 'np.int8')[source]

Bases: object

path: int32

session: int8

Info_dtype: Final[list[tuple[str, str]]] = [('path', 'U32'), ('session', 'U8')]

test_list: Final[list[str]] = ['s3', 's7', 's10']

class_list: Final[dict[int, int]] = {1: 0, 2: 0, 3: 0, 4: 0, 5: 0, 6: 1, 7: 1, 8: 1, 9: 1, 10: 1, 11: 2, 12: 2, 13: 2, 14: 2, 15: 2, 16: 3, 17: 3, 18: 3, 19: 3, 20: 3, 21: 4, 22: 4, 23: 4, 24: 4, 25: 4, 26: 5, 27: 5, 28: 5, 29: 5, 30: 5, 31: 6, 32: 6, 33: 6, 34: 6, 35: 6, 36: 7, 37: 7, 38: 7, 39: 7, 40: 7, 41: 8, 42: 8, 43: 8, 44: 8, 45: 8, 46: 9, 47: 9, 48: 9, 49: 9, 50: 9}

property name: str

class qualia_core.dataset.EllcieHAR(path: str = '', variant: str = '1', files: list[str] | None = None)[source]

Bases: HARDataset

class Row(T: 'str', Ax: 'str', Ay: 'str', Az: 'str', Gx: 'str', Gy: 'str', Gz: 'str', P: 'str', CLASS: 'str')[source]

Bases: object

T: str

Ax: str

Ay: str

Az: str

Gx: str

Gy: str

Gz: str

P: str

CLASS: str

activitylist: Final[dict[str, Activities]] = {'DRINKING': Activities.DRINKING, 'DRIVING': Activities.DRIVING, 'LIE_TO_SIT': Activities.LIE_TO_SIT, 'LYING': Activities.LYING, 'RUNNING': Activities.RUNNING, 'SITTING': Activities.SITTING, 'SIT_TO_LIE': Activities.SIT_TO_LIE, 'SIT_TO_STAND': Activities.SIT_TO_STAND, 'STANDING': Activities.STANDING, 'STAND_TO_SIT': Activities.STAND_TO_SIT, 'WALKING': Activities.WALKING, 'WALKING_DOWNSTAIRS': Activities.WALKING_DOWNSTAIRS, 'WALKING_UPSTAIRS': Activities.WALKING_UPSTAIRS}

property name: str

class qualia_core.dataset.GSC(path: str, variant: str = 'v2', subset: str = 'digits', train_valid_split: bool = False)[source]

Bases: RawDataset

class_list_no_background_noise: Final[dict[str, int | None]] = {'_background_noise_': None, 'backward': 0, 'bed': 1, 'bird': 2, 'cat': 3, 'dog': 4, 'down': 5, 'eight': 6, 'five': 7, 'follow': 8, 'forward': 9, 'four': 10, 'go': 11, 'happy': 12, 'house': 13, 'learn': 14, 'left': 15, 'marvin': 16, 'nine': 17, 'no': 18, 'off': 19, 'on': 20, 'one': 21, 'right': 22, 'seven': 23, 'sheila': 24, 'six': 25, 'stop': 26, 'three': 27, 'tree': 28, 'two': 29, 'up': 30, 'visual': 31, 'wow': 32, 'yes': 33, 'zero': 34}

class_list_digits: Final[dict[str, int | None]] = {'_background_noise_': None, 'backward': None, 'bed': None, 'bird': None, 'cat': None, 'dog': None, 'down': None, 'eight': 8, 'five': 5, 'follow': None, 'forward': None, 'four': 4, 'go': None, 'happy': None, 'house': None, 'learn': None, 'left': None, 'marvin': None, 'nine': 9, 'no': None, 'off': None, 'on': None, 'one': 1, 'right': None, 'seven': 7, 'sheila': None, 'six': 6, 'stop': None, 'three': 3, 'tree': None, 'two': 2, 'up': None, 'visual': None, 'wow': None, 'yes': None, 'zero': 0}

load_wave(recording: Path) → ndarray[Any, dtype[float32]][source]

property name: str

class qualia_core.dataset.GTSRB(path: str = '', width: int = 32, height: int = 32)[source]

Bases: RawDataset

class Row(Filename: 'str', Width: 'str', Height: 'str', Roi_X1: 'str', Roi_Y1: 'str', Roi_X2: 'str', Roi_Y2: 'str', ClassId: 'str')[source]

Bases: object

Filename: str

Width: str

Height: str

Roi_X1: str

Roi_Y1: str

Roi_X2: str

Roi_Y2: str

ClassId: str

class qualia_core.dataset.HD(path: str, variant: str | None = None, test_subjects: list[int] | None = None)[source]

Bases: RawDataset

Heidelberg Digits, raw audio (‘hd_audio.tar.gz’).

property name: str

class qualia_core.dataset.UCI_HAR(path: str = '', variant: str = 'features')[source]

Bases: HARDataset

activitylist: Final[dict[str, Activities]] = {'1': Activities.WALKING, '2': Activities.WALKING_UPSTAIRS, '3': Activities.WALKING_DOWNSTAIRS, '4': Activities.SITTING, '5': Activities.STANDING, '6': Activities.LYING}

property name: str

class qualia_core.dataset.WSMNIST(path: str, variant: str = 'spoken')[source]

Bases: RawDataset

property name: str