def __init__(self, a, b):
StochasticParameter.__init__(self)
# for two ints the samples will be from range a <= x <= b
assert isinstance(
a, (int, StochasticParameter)
), "Expected a to be int or StochasticParameter, got %s" % (type(a), )
assert isinstance(
b, (int, StochasticParameter)
), "Expected b to be int or StochasticParameter, got %s" % (type(b), )
if ia.is_single_integer(a):
self.a = Deterministic(a)
else:
self.a = a
if ia.is_single_integer(b):
self.b = Deterministic(b)
else:
self.b = b
def _Pool_worker(batch_idx, batch):
assert ia.is_single_integer(batch_idx)
assert isinstance(batch, (UnnormalizedBatch, Batch))
assert Pool._WORKER_AUGSEQ is not None
aug = Pool._WORKER_AUGSEQ
if Pool._WORKER_SEED_START is not None:
seed = Pool._WORKER_SEED_START + batch_idx
seed_global = ia.SEED_MIN_VALUE + (seed - 10**9) % (ia.SEED_MAX_VALUE - ia.SEED_MIN_VALUE)
seed_local = ia.SEED_MIN_VALUE + seed % (ia.SEED_MAX_VALUE - ia.SEED_MIN_VALUE)
ia.seed(seed_global)
aug.reseed(seed_local)
result = aug.augment_batch(batch)
return result
def _Pool_worker(batch_idx, batch):
assert ia.is_single_integer(batch_idx), (
"Expected `batch_idx` to be an integer. Got type %s instead." %
(type(batch_idx)))
assert isinstance(batch, (UnnormalizedBatch, Batch)), (
"Expected `batch` to be either an instance of "
"`imgaug.augmentables.batches.UnnormalizedBatch` or "
"`imgaug.augmentables.batches.Batch`. Got type %s instead." %
(type(batch)))
assert Pool._WORKER_AUGSEQ is not None, (
"Expected `Pool._WORKER_AUGSEQ` to NOT be `None`. Did you manually "
"call _Pool_worker()?")
augseq = Pool._WORKER_AUGSEQ
# TODO why is this if here? _WORKER_SEED_START should always be set?
if Pool._WORKER_SEED_START is not None:
seed = Pool._WORKER_SEED_START + batch_idx
_reseed_global_local(seed, augseq)
result = augseq.augment_batch(batch)
return result
