brails.processors.vlm_segmenter.segment_anything.automatic_mask_generator module
- class brails.processors.vlm_segmenter.segment_anything.automatic_mask_generator.SamAutomaticMaskGenerator(model: Sam, points_per_side: int | None = 32, points_per_batch: int = 64, pred_iou_thresh: float = 0.88, stability_score_thresh: float = 0.95, stability_score_offset: float = 1.0, box_nms_thresh: float = 0.7, crop_n_layers: int = 0, crop_nms_thresh: float = 0.7, crop_overlap_ratio: float = 0.3413333333333333, crop_n_points_downscale_factor: int = 1, point_grids: List[ndarray] | None = None, min_mask_region_area: int = 0, output_mode: str = 'binary_mask')
Bases:
object- generate(image: ndarray) List[Dict[str, Any]]
Generates masks for the given image.
- Arguments:
image (np.ndarray): The image to generate masks for, in HWC uint8 format.
- Returns:
- list(dict(str, any)): A list over records for masks. Each record is
- a dict containing the following keys:
- segmentation (dict(str, any) or np.ndarray): The mask. If
output_mode=’binary_mask’, is an array of shape HW. Otherwise, is a dictionary containing the RLE.
bbox (list(float)): The box around the mask, in XYWH format. area (int): The area in pixels of the mask. predicted_iou (float): The model’s own prediction of the mask’s
quality. This is filtered by the pred_iou_thresh parameter.
- point_coords (list(list(float))): The point coordinates input
to the model to generate this mask.
- stability_score (float): A measure of the mask’s quality. This
is filtered on using the stability_score_thresh parameter.
- crop_box (list(float)): The crop of the image used to generate
the mask, given in XYWH format.