def _load_segmentation_mask(data: DataSetBase,
image: str) -> Optional[np.ndarray]:
"""Build a mask from segmentation ignore values.
The mask is non-zero only for pixels with segmentation
labels not in segmentation_ignore_values.
"""
ignore_values = data.segmentation_ignore_values(image)
if not ignore_values:
return None
segmentation = data.load_segmentation(image)
if segmentation is None:
return None
return mask_from_segmentation(segmentation, ignore_values)
def read_images(
queue: queue.Queue,
data: DataSetBase,
images: List[str],
counter: Counter,
expected: int,
force: bool,
) -> None:
full_queue_timeout = 120
for image in images:
logger.info(f"Reading data for image {image} (queue-size={queue.qsize()}")
image_array = data.load_image(image)
if data.config["features_bake_segmentation"]:
segmentation_array = data.load_segmentation(image)
instances_array = data.load_instances(image)
else:
segmentation_array, instances_array = None, None
args = image, image_array, segmentation_array, instances_array, data, force
queue.put(args, block=True, timeout=full_queue_timeout)
counter.increment()
if counter.value() == expected:
logger.info("Finished reading images")
queue.put(None)
