## omero_data.OmeroData


Dataclass to store all the data related to the omero project and plate.


Usage

``` python
omero_data.OmeroData(
    well_pos_list=list(),
    image_input=str(),
    image_index=list(),
    screen_dataset=_DatasetWrapper(),
    plate_id=int(),
    plate_name=str(),
    plate=_PlateWrapper(),
    plate_data=pl.LazyFrame(),
    data_path=get_data_path(),
    csv_path=Path(),
    flatfield_masks=(lambda: np.empty((0,)))(),
    pixel_size=None,
    channel_data=dict(),
    intensities=dict(),
    crop_start=tuple(),
    crop_length=tuple(),
    well_list=list(),
    well_id_list=list(),
    well_metadata_list=list(),
    well_ifdata=pl.DataFrame(),
    well_image_index=list(),
    images=(lambda: np.empty((0,)))(),
    image_ids=list(),
    image_positions=list(),
    labels=(lambda: np.empty((0,)))(),
    label_stitched_mode=False,
    stitched_images=(lambda: np.empty((0,)))(),
    cropped_images=list(),
    cropped_labels=list(),
    cropped_cell_meta=list(),
    selected_images=list(),
    selected_labels=list(),
    selected_crops=list(),
    selected_classes=list(),
    selected_cell_meta=list(),
    session_file_path=None
)
```


## Parameter Attributes


`well_pos_list: list[str] = list()`  

`image_input: str = str()`  

`image_index: list[int] = list()`  

`screen_dataset: _DatasetWrapper = _DatasetWrapper()`  

`plate_id: int = int()`  

`plate_name: str = str()`  

`plate: _PlateWrapper = _PlateWrapper()`  

`plate_data: pl.LazyFrame = pl.LazyFrame()`  

`data_path: Path = get_data_path()`  

`csv_path: Path = Path()`  

`flatfield_masks: NDArray[Any] = (lambda: np.empty((0,)))()`  

`pixel_size: Optional[tuple[float, float]] = None`  

`channel_data: dict[str, Any] = dict()`  

`intensities: dict[int, Any] = dict()`  

`crop_start: tuple[int, …] = tuple()`  

`crop_length: tuple[int, …] = tuple()`  

`well_list: list[_WellWrapper] = list()`  

`well_id_list: list[int] = list()`  

`well_metadata_list: list[dict[str, Any]] = list()`  

`well_ifdata: pl.DataFrame = pl.DataFrame()`  

`well_image_index: list[int] = list()`  

`images: NDArray[Any] = (lambda: np.empty((0,)))()`  

`image_ids: list[int] = list()`  

`image_positions: list[tuple[float, float] | None] = list()`  

`labels: NDArray[Any] = (lambda: np.empty((0,)))()`  

`label_stitched_mode: bool = ``False`  

`stitched_images: NDArray[Any] = (lambda: np.empty((0,)))()`  

`cropped_images: list[NDArray[Any]] = list()`  

`cropped_labels: list[NDArray[Any]] = list()`  

`cropped_cell_meta: list[dict[str, Any]] = list()`  

`selected_images: list[NDArray[Any]] = list()`  

`selected_labels: list[NDArray[Any]] = list()`  

`selected_crops: list[NDArray[Any]] = list()`  

`selected_classes: list[str] = list()`  

`selected_cell_meta: list[dict[str, Any]] = list()`  

`session_file_path: Optional[Path] = None`  


## Methods

| Name | Description |
|----|----|
| [reset_well_and_image_data()](#reset_well_and_image_data) | Resets the well and image data to their default states. |

------------------------------------------------------------------------


#### reset_well_and_image_data()


Resets the well and image data to their default states.


Usage

``` python
reset_well_and_image_data()
```