satellit_sam.workflows.predict.image_masks
satellit_sam.workflows.predict.image_masks
Auto-generated from
satellit_sam/src/satellit_sam/workflows/predict/image_masks.pybysatellit_sam/scripts/generate_api_docs.py.
Image-mask prediction workflow for streamed full-image segmentation inference.
Functions
predict_image_masks
def predict_image_masks(
image_path: Path,
output_path: Path,
text_prompt: str | None,
bbox_prompts: list[tuple[float, float, float, float]],
point_prompts: list[tuple[float, float]],
model: Literal["sam3", "sam2", "dinov3"] = "sam3",
threshold: float = 0.5,
tile_size: int = 640,
tile_overlap: int = 64,
merge_iou_threshold: float = 0.5,
weak_label_bboxes_by_tile: dict[str, list[tuple[float, float, float, float]]]
| None = None,
command: str | None = None,
) -> None:
Predict image masks from one image and save outputs.
The workflow:
- streams model inference over image tiles,
- merges tile detections globally via NMS,
- saves per-tile strong-label artifacts,
- saves one mask visualization, and
- saves merged predicted masks and metadata as one
.npzfile.
Arguments
image_path: Path to the input image. output_path: Output directory for all artifacts. text_prompt: Optional text prompt for segmentation filtering. bbox_prompts: Optional image-space bbox prompts. point_prompts: Optional image-space point prompts. model: Segmentation model family to use (``sam3``, ``sam2``, ``dinov3``). threshold: Confidence threshold for keeping predicted masks. tile_size: Prediction tile size in pixels. tile_overlap: Overlap between neighboring prediction tiles in pixels. merge_iou_threshold: IoU threshold for cross-tile NMS merge. weak_label_bboxes_by_tile: Optional tile-local bboxes keyed by tile id. command: Optional CLI command string used to start the run.
Exceptions
ValueError: If inputs or prompt combinations are invalid.
Classes
No public classes.