DimensionStatsOutput#
- class dataeval.metrics.stats.DimensionStatsOutput(source_index: list[SourceIndex], box_count: NDArray[np.uint16], left: NDArray[np.int32], top: NDArray[np.int32], width: NDArray[np.uint32], height: NDArray[np.uint32], channels: NDArray[np.uint8], size: NDArray[np.uint32], aspect_ratio: NDArray[np.float16], depth: NDArray[np.uint8], center: NDArray[np.int16], distance: NDArray[np.float16])#
Output class for
dimensionstats()stats metric- left#
Offsets from the left edge of images in pixels
- Type:
NDArray[np.int32]
- top#
Offsets from the top edge of images in pixels
- Type:
NDArray[np.int32]
- width#
Width of the images in pixels
- Type:
NDArray[np.uint32]
- height#
Height of the images in pixels
- Type:
NDArray[np.uint32]
- channels#
Channel count of the images in pixels
- Type:
NDArray[np.uint8]
- size#
Size of the images in pixels
- Type:
NDArray[np.uint32]
- aspect_ratio#
Aspect ratio of the images (width/height)
- Type:
NDArray[np.float16]
- depth#
Color depth of the images in bits
- Type:
NDArray[np.uint8]
- center#
Offset from center in [x,y] coordinates of the images in pixels
- Type:
NDArray[np.uint16]
- distance#
Distance in pixels from center
- Type:
NDArray[np.float16]
- get_channel_mask(channel_index: int | Iterable[int] | None, channel_count: int | Iterable[int] | None = None) list[bool]#
Boolean mask for results filtered to specified channel index and optionally the count of the channels per image.
- Parameters:
channel_index (int | Iterable[int] | None) – Index or indices of channel(s) to filter for
channel_count (int | Iterable[int] | None) – Optional count(s) of channels to filter for