def test_speed():
with Pipeline() as pipeline:
level1 = Unpack(range(N_STEPS))
level2 = Unpack(range(N_STEPS))
Sleep()
with Timer("sequential") as t:
expected_result = [
(obj[level1], obj[level2]) for obj in pipeline.transform_stream()
]
elapsed_sequential = t.elapsed
with Pipeline() as pipeline:
level1 = Unpack(range(N_STEPS))
with ParallelPipeline(4) as pp:
level2 = Unpack(range(N_STEPS))
Sleep()
with Timer("parallel") as t:
result = [(obj[level1], obj[level2]) for obj in pipeline.transform_stream()]
elapsed_parallel = t.elapsed
assert result == expected_result
assert elapsed_parallel < elapsed_sequential
def test_Format():
# Assert that the arguments are appended in the right order
fmt = "{},{},{},{},{},{},{a},{b},{c},{d}"
args = (1, 2, 3)
_args = (4, 5, 6)
_kwargs = {"a": 7, "b": 8}
kwargs = {"c": 9, "d": 10}
with Pipeline() as pipeline:
result = Format(fmt, *args, _args=_args, _kwargs=_kwargs, **kwargs)
stream = pipeline.transform_stream()
obj = next(stream)
assert obj[result] == "1,2,3,4,5,6,7,8,9,10"
# Assert that the keyword arguments replace as expected
fmt = "{a},{b}"
_kwargs = {"a": 1, "b": 2}
kwargs = {"a": 3, "b": 4}
with Pipeline() as pipeline:
result = Format(fmt, _kwargs=_kwargs, **kwargs)
stream = pipeline.transform_stream()
obj = next(stream)
assert obj[result] == "3,4"
def test_ecotaxa(tmp_path):
archive_fn = tmp_path / "ecotaxa.zip"
print(archive_fn)
# Create an archive
with Pipeline() as p:
i = Unpack(range(10))
meta = Call(dict, i=i, foo="Sömé UTF-8 ſtríng…")
image = BinaryBlobs()
image_name = Format("image_{}.png", i)
EcotaxaWriter(archive_fn, (image_name, image), meta)
result = [o.to_dict(meta=meta, image=image) for o in p.transform_stream()]
# Read the archive
with Pipeline() as p:
image, meta = EcotaxaReader(archive_fn)
roundtrip_result = [
o.to_dict(meta=meta, image=image) for o in p.transform_stream()
]
for meta_field in ("i", "foo"):
assert [o["meta"][meta_field] for o in result
] == [o["meta"][meta_field] for o in roundtrip_result]
assert_equal([o["image"] for o in result],
[o["image"] for o in roundtrip_result])
def test_KeyError():
with Pipeline() as pipeline:
with ParallelPipeline(4) as pp:
KeyErrorRaiser()
with pytest.raises(KeyError, match="foo"):
pipeline.run()
def test_DrawContours():
image = skimage.data.camera()
with Pipeline() as pipeline:
mask = ThresholdConst(image, 255)
result = DrawContours(image, mask, (0, 255, 0))
pipeline.run()
def test_num_workers(num_workers):
with Pipeline() as pipeline:
level1 = Unpack(range(N_STEPS))
with ParallelPipeline(num_workers) as pp:
level2 = Unpack(range(N_STEPS))
pipeline.run()
def test_Find(data_path):
d = data_path / "images"
with Pipeline() as pipeline:
result = Find(d, [".png"])
stream = pipeline.transform_stream()
pipeline.run()
def test_Glob(data_path):
d = data_path / "images/*.png"
with Pipeline() as pipeline:
result = Glob(d, True)
stream = pipeline.transform_stream()
pipeline.run()
def test_FindRegions():
image = skimage.data.camera()
with Pipeline() as pipeline:
mask = ThresholdConst(image, 255)
result = FindRegions(mask, image, 0, 100, padding=10)
pipeline.run()
def test_PiCamera():
with Pipeline() as p:
frame = PiCameraReader()
# Only capture 10 frames
Slice(10)
p.run()
def test_ImageProperties():
with Pipeline() as pipeline:
image = Unpack([skimage.data.camera()])
mask = ThresholdConst(image, 255)
region = ImageProperties(mask, image)
image2 = ExtractROI(image, region, 0)
for obj in pipeline.transform_stream():
assert_equal(obj[image], obj[image2])
def test_ThresholdConst():
images = [skimage.data.camera(), np.zeros((10, 10), np.uint8) + 255]
with Pipeline() as pipeline:
image = Unpack(images)
mask = ThresholdConst(image, 255)
objects = list(pipeline.transform_stream())
assert not objects[1][mask].any()
def test_Call():
def foo(bar, baz):
return bar, baz
with Pipeline() as pipeline:
result = Call(foo, 1, 2)
obj, *_ = list(pipeline.transform_stream())
assert obj[result] == (1, 2)
def test_StreamBuffer():
with Pipeline() as pipeline:
item = Unpack(range(10))
result = StreamBuffer(1)
stream = pipeline.transform_stream()
result = [o[item] for o in stream]
assert result == list(range(10))
def test_RGB2Gray():
image = skimage.data.astronaut()
with Pipeline() as pipeline:
result = RGB2Gray(image)
stream = pipeline.transform_stream()
obj = next(stream)
assert obj[result].ndim == 2
def test_vignette_corrector_no_channel(image_fns):
with Pipeline() as pipeline:
img_fn = Unpack(image_fns)
image = Call(imread, img_fn, as_gray=True)
result = VignettingCorrector(image)
stream = pipeline.transform_stream()
obj = next(stream)
def test_ImageWriter(tmp_path):
d = tmp_path / "sub"
d.mkdir()
p = d / "new.jpg"
image = skimage.data.camera()
with Pipeline() as pipeline:
result = ImageWriter(p, image)
pipeline.run()
def test_Enumerate():
with Pipeline() as pipeline:
a = Unpack(range(10))
i = Enumerate()
stream = pipeline.transform_stream()
for obj in stream:
assert obj[a] == obj[i]
def test_ExtractROI():
with Pipeline() as pipeline:
image = Unpack([skimage.data.camera()])
mask = ThresholdConst(image, 255)
regions = FindRegions(mask, image)
ExtractROI(image, regions)
ExtractROI(image, regions, 0.5)
pipeline.run()
def test_Gray2RGB():
image = skimage.data.camera()
with Pipeline() as pipeline:
result = Gray2RGB(image)
stream = pipeline.transform_stream()
obj = next(stream)
assert obj[result].ndim == 3
assert obj[result].shape[-1] == 3
def test_StreamBuffer():
with Pipeline() as pipeline:
item = Unpack(range(10))
StreamBuffer(1)
stream = pipeline.transform_stream()
objects = [o for o in stream]
assert objects[0].n_remaining_hint == 10
assert [o[item] for o in objects] == list(range(10))
def test_DrawContoursOnParent():
image = skimage.data.camera()
with Pipeline() as pipeline:
mask = ThresholdConst(image, 255)
regions = FindRegions(mask, image, 0, 100, padding=10)
output_ref = image
result = DrawContoursOnParent(image, mask, output_ref, regions, (0, 255, 0))
stream = pipeline.transform_stream()
pipeline.run()
def test_exception_worker():
with Pipeline() as pipeline:
level1 = Unpack(range(N_STEPS))
with ParallelPipeline(4) as pp:
Sleep()
Raiser()
with pytest.raises(SomeException, match="foo"):
pipeline.run()
def test_TQDM():
# Assert that the progress bar works with stream
with Pipeline() as pipeline:
item = Unpack(range(10))
result = TQDM("Description")
stream = pipeline.transform_stream()
result = [o[item] for o in stream]
assert result == list(range(10))
def test_ecotaxa(tmp_path, ext):
archive_fn = tmp_path / ("ecotaxa" + ext)
print(archive_fn)
# Create an archive
with Pipeline() as p:
i = Unpack(range(10))
meta = Call(dict, i=i, foo="Sömé UTF-8 ſtríng…")
image = BinaryBlobs()
image_name = Format("image_{}.png", i)
EcotaxaWriter(
archive_fn,
(image_name, image),
meta,
object_meta={"foo": 0},
acq_meta={"foo": 1},
process_meta={"foo": 2},
sample_meta={"foo": 3},
)
result = [o.to_dict(meta=meta, image=image) for o in p.transform_stream()]
# Read the archive
with Pipeline() as p:
image, meta = EcotaxaReader(archive_fn)
roundtrip_result = [
o.to_dict(meta=meta, image=image) for o in p.transform_stream()
]
for meta_field in ("i", "foo"):
assert [o["meta"][meta_field] for o in result
] == [o["meta"][meta_field] for o in roundtrip_result]
for i, prefix in enumerate(("object_", "acq_", "process_", "sample_")):
assert [o["meta"][prefix + "foo"]
for o in result] == [i for _ in roundtrip_result]
assert_equal([o["image"] for o in result],
[o["image"] for o in roundtrip_result])
def test_worker_die():
with Pipeline() as pipeline:
level1 = Unpack(range(N_STEPS))
with ParallelPipeline(4):
Call(lambda: os.kill(os.getpid(), signal.SIGKILL))
with pytest.raises(
RuntimeError,
match=r"Worker \d+ died unexpectedly. Exit code: -SIGKILL"):
pipeline.run()
def test_Unpack():
values = list(range(10))
with Pipeline() as pipeline:
value = Unpack(values)
stream = pipeline.transform_stream()
objects = [o for o in stream]
assert objects[0].n_remaining_hint == 10
assert values == [o[value] for o in objects]
def test_Slice():
# Assert that the stream is sliced
items = "ABCDEFG"
with Pipeline() as pipeline:
result = Slice(2)
stream = pipeline.transform_stream(items)
obj = list(stream)
assert obj == ["A", "B"]
# Assert that the stream is sliced from the specified start and end
with Pipeline() as pipeline:
result = Slice(2, 4)
stream = pipeline.transform_stream(items)
obj = list(stream)
assert obj == ["C", "D"]
def test_Unpack():
values = list(range(10))
with Pipeline() as pipeline:
value = Unpack(values)
stream = pipeline.transform_stream()
result = [o[value] for o in stream]
assert values == result
def test_Node():
# Assert that Node checks for the existence of a pipeline
with pytest.raises(RuntimeError):
TestNode(1, 2, 3)
# Assert that Node checks for the existance of transform
with Pipeline() as pipeline:
TestNodeNoTransform()
with pytest.raises(AttributeError):
pipeline.run()
# Assert that parameters and outputs are passed as expected
with Pipeline() as pipeline:
a, b, c = TestNode(1, 2, 3)
obj, *_ = list(pipeline.transform_stream())
assert obj[a] == 1
assert obj[b] == 2
assert obj[c] == 3