def repeated_sequence_headers(codec_features):
"""
**Tests the decoder can handle a stream with repeated sequence headers.**
This test case consists of a sequence containing two frames in which the
sequence header is repeated before every picture.
This test will be omitted if the VC-2 level prohibits the repetition of the
sequence header.
"""
try:
# Generate a base sequence in which we'll replace the sequence headers
# later. We ensure we have at least two pictures to ensure we get
# pictures and sequence headers being interleaved.
sequence = make_sequence(
codec_features,
repeat_pictures(
static_sprite(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
),
2,
),
# Force an extra sequence header between every data unit
"(sequence_header .)+",
)
except IncompatibleLevelAndDataUnitError:
# Do not try to force levels which don't support this level of sequence
# header interleaving to accept it.
return None
return Stream(sequences=[sequence])
def absent_next_parse_offset(codec_features):
"""
**Tests handling of missing 'next parse offset' field.**
The 'next parse offset' field of the ``parse_info`` header (see (10.5.1))
can be set to zero (i.e. omitted) for pictures. This test case verifies
that decoders are still able to decode streams with this field absent.
"""
sequence = make_sequence(
codec_features,
repeat_pictures(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
),
2,
),
)
# Prevent the default auto numbering of picture-containing data units
# during serialisation
for data_unit in sequence["data_units"]:
parse_info = data_unit["parse_info"]
if parse_info["parse_code"] in (
ParseCodes.low_delay_picture,
ParseCodes.high_quality_picture,
ParseCodes.low_delay_picture_fragment,
ParseCodes.high_quality_picture_fragment,
):
parse_info["next_parse_offset"] = 0
return Stream(sequences=[sequence])
def test_iter_transform_parameters_in_sequence(profile, fragment_slice_count):
codec_features = MINIMAL_CODEC_FEATURES.copy()
codec_features["profile"] = profile
codec_features["fragment_slice_count"] = fragment_slice_count
codec_features["slices_x"] = 3
codec_features["slices_y"] = 2
codec_features["picture_bytes"] = 100
num_pictures = 2
sequence = make_sequence(
codec_features,
repeat_pictures(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
),
num_pictures,
),
)
transform_parameters = list(
iter_transform_parameters_in_sequence(codec_features, sequence))
# Should have found every slice
assert len(transform_parameters) == num_pictures
def picture_numbers(codec_features):
"""
**Tests picture numbers are correctly read from the bitstream.**
Each test case contains 8 blank pictures numbered in a particular way.
``picture_numbers[start_at_zero]``
The first picture has picture number 0.
``picture_numbers[non_zero_start]``
The first picture has picture number 1000.
``picture_numbers[wrap_around]``
The first picture has picture number 4294967292, with the picture
numbers wrapping around to 0 on the 4th picture in the sequence.
``picture_numbers[odd_first_picture]``
The first picture has picture number 7. This test case is only included
when the picture coding mode is 0 (i.e. pictures are frames) since the
first field of each frame must have an even number when the picture
coding mode is 1 (i.e. pictures are fields) (11.5).
"""
# Create a sequence with at least 8 pictures (and 4 frames)
mid_gray_pictures = list(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
))
mid_gray_pictures = list(
repeat_pictures(
mid_gray_pictures,
8 // len(mid_gray_pictures),
))
test_cases = [
("start_at_zero", [0, 1, 2, 3, 4, 5, 6, 7]),
("non_zero_start", [1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007]),
("wrap_around",
[4294967292, 4294967293, 4294967294, 4294967295, 0, 1, 2, 3]),
]
if codec_features[
"picture_coding_mode"] == PictureCodingModes.pictures_are_frames:
test_cases.append(("odd_first_picture", [7, 8, 9, 10, 11, 12, 13, 14]))
for description, picture_numbers in test_cases:
yield TestCase(
Stream(sequences=[
make_sequence(
codec_features,
[
dict(picture, pic_num=pic_num) for picture, pic_num in
zip(mid_gray_pictures, picture_numbers)
],
)
]),
description,
)
def test_iter_slices_in_sequence(profile, fragment_slice_count):
codec_features = MINIMAL_CODEC_FEATURES.copy()
codec_features["profile"] = profile
codec_features["fragment_slice_count"] = fragment_slice_count
codec_features["slices_x"] = 3
codec_features["slices_y"] = 2
codec_features["picture_bytes"] = 100
num_pictures = 2
sequence = make_sequence(
codec_features,
repeat_pictures(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
),
num_pictures,
),
)
slices = list(iter_slices_in_sequence(codec_features, sequence))
# Should have found every slice
assert len(slices) == (codec_features["slices_x"] *
codec_features["slices_y"] * num_pictures)
# Should have correct states
if profile == Profiles.high_quality:
for state, _, _, _ in slices:
assert state == State(
slice_prefix_bytes=0,
slice_size_scaler=1,
slices_x=codec_features["slices_x"],
slices_y=codec_features["slices_y"],
)
elif profile == Profiles.low_delay:
slice_bytes = Fraction(
codec_features["picture_bytes"],
codec_features["slices_x"] * codec_features["slices_y"],
)
for state, _, _, _ in slices:
assert state == State(
slice_bytes_numerator=slice_bytes.numerator,
slice_bytes_denominator=slice_bytes.denominator,
slices_x=codec_features["slices_x"],
slices_y=codec_features["slices_y"],
)
# Should have correct coordinates
it = iter(slices)
for _ in range(num_pictures):
for exp_sy in range(codec_features["slices_y"]):
for exp_sx in range(codec_features["slices_x"]):
_, sx, sy, _ = next(it)
assert exp_sx == sx
assert exp_sy == sy
def test_multiple_repeats(self, pictures):
repeated = list(repeat_pictures(iter(pictures), 3))
assert len(repeated) == len(pictures) * 3
# Check repeated
for orig, new in zip(cycle(pictures), repeated):
assert orig["Y"] == new["Y"]
assert orig["C1"] == new["C1"]
assert orig["C2"] == new["C2"]
# Check picture numbers consecutive
assert [p["pic_num"] for p in repeated] == list(range(len(repeated)))
def test_iter_slice_parameters_in_sequence(fragment_slice_count):
codec_features = MINIMAL_CODEC_FEATURES.copy()
codec_features["profile"] = Profiles.high_quality
codec_features["fragment_slice_count"] = fragment_slice_count
num_pictures = 2
sequence = make_sequence(
codec_features,
repeat_pictures(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
),
num_pictures,
),
)
slice_parameters = list(iter_slice_parameters_in_sequence(sequence))
# Should have found every set of slice parameters
assert len(slice_parameters) == num_pictures
def test_minimum_qindex(kwargs, exp_qis):
codec_features = MINIMAL_CODEC_FEATURES.copy()
pictures = list(
repeat_pictures(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
),
3,
))
assert len(pictures) == 3
seq = make_sequence(codec_features, pictures, **kwargs)
qis = []
for data_unit in seq["data_units"]:
if "picture_parse" in data_unit:
tx_data = data_unit["picture_parse"]["wavelet_transform"][
"transform_data"]
qis.append(tx_data["hq_slices"][0]["qindex"])
assert qis == exp_qis
def signal_range(codec_features):
"""
**Tests that an encoder has sufficient numerical dynamic range.**
These test cases contain test patterns designed to produce extreme signals
within encoders. During these test cases, no integer clamping or overflows
must occur.
A test case is produced for each picture component:
``signal_range[Y]``
Luma component test patterns.
``signal_range[C1]``
Color difference 1 component test patterns.
``signal_range[C2]``
Color difference 2 component test patterns.
Though the test patterns produce near worst case signal levels, they are
not guaranteed to produce the largest values possible.
.. note::
For informational purposes, an example of a set of test patterns are shown below:
.. image:: /_static/user_guide/signal_range_encoder.png
An informative metadata file is provided along side each test case which
gives, for each picture in the bitstream, the parts of a encoder which are
being tested by the test patterns. See
:py:class:`vc2_bit_widths.helpers.TestPoint` for details.
"""
try:
(
analysis_luma_pictures,
synthesis_luma_pictures,
analysis_color_diff_pictures,
synthesis_color_diff_pictures,
) = get_test_pictures(codec_features)
except MissingStaticAnalysisError:
logging.warning(
("No static analysis available for the wavelet "
"used by codec '%s'. Signal range test cases cannot "
"be generated."),
codec_features["name"],
)
return
for component, analysis_test_pictures in [
("Y", analysis_luma_pictures),
("C1", analysis_color_diff_pictures),
("C2", analysis_color_diff_pictures),
]:
# Generate an initially empty set of mid-gray pictures
one_gray_frame = list(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
))
pictures = list(
repeat_pictures(
one_gray_frame,
((len(analysis_test_pictures) + len(one_gray_frame) - 1) //
len(one_gray_frame)),
))
# Fill-in the test patterns
for test_picture, picture in zip(analysis_test_pictures, pictures):
picture[component] = test_picture.picture.tolist()
# Extract the testpoints in JSON-serialisable form
metadata = [[tp._asdict() for tp in p.test_points]
for p in analysis_test_pictures]
out = EncoderTestSequence(
pictures=pictures,
video_parameters=codec_features["video_parameters"],
picture_coding_mode=codec_features["picture_coding_mode"],
)
yield TestCase(out, component, metadata=metadata)
def padding_data(codec_features):
"""
**Tests that the contents of padding data units are ignored.**
This test case consists of a sequence containing two blank frames in which
every-other data unit is a padding data unit (10.4.5) of various lengths
and contents (described below).
``padding_data[empty]``
Padding data units containing zero padding bytes (i.e. just consisting
of a parse info header).
``padding_data[zero]``
Padding data units containing 32 bytes set to 0x00.
``padding_data[non_zero]``
Padding data units containing 32 bytes containing the ASCII encoding of
the text ``Ignore this padding data please!``.
``padding_data[dummy_end_of_sequence]``
Padding data units containing 32 bytes containing an encoding of an end
of sequence data unit (10.4.1).
Where padding data units are not permitted by the VC-2 level in use, these
test cases are omitted.
"""
# Generate a base sequence in which we'll modify the padding data units. We
# ensure there are always at least two pictures in the sequences to make
# premature termination obvious.
try:
base_sequence = make_sequence(
codec_features,
repeat_pictures(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
),
2,
),
# Insert padding data between every data unit
"sequence_header (padding_data .)* padding_data end_of_sequence $",
)
except IncompatibleLevelAndDataUnitError:
# Padding not allowed in the supplied video format so just skip this
# test
return
for description, data in [
(
"empty",
b"",
),
(
"zero",
b"\x00" * 32,
),
(
"non_zero",
b"Ignore this padding data please!",
),
(
"dummy_end_of_sequence",
make_dummy_end_of_sequence().ljust(32, b"\x00"),
),
]:
yield TestCase(
Stream(sequences=[replace_padding_data(base_sequence, data)]),
description,
)
class TestGenericPictureGeneratorBehaviour(object):
@pytest.fixture(params=[
real_pictures,
moving_sprite,
static_sprite,
mid_gray,
white_noise,
linear_ramps,
lambda *a, **kw: repeat_pictures(mid_gray(*a, **kw), 2),
])
def picture_generator(
self,
request,
replace_real_pictures_with_test_pictures, # noqa: F811
):
return request.param
@pytest.fixture
def vp(self):
return VideoParameters(
frame_width=16,
frame_height=8,
frame_rate_numer=1,
frame_rate_denom=1,
pixel_aspect_ratio_numer=1,
pixel_aspect_ratio_denom=1,
source_sampling=SourceSamplingModes.progressive,
top_field_first=True,
color_diff_format_index=ColorDifferenceSamplingFormats.color_4_4_4,
color_primaries_index=PresetColorPrimaries.hdtv,
color_matrix_index=PresetColorMatrices.hdtv,
transfer_function_index=PresetTransferFunctions.tv_gamma,
luma_offset=0,
luma_excursion=255,
color_diff_offset=128,
color_diff_excursion=255,
)
@pytest.mark.parametrize("ssm", SourceSamplingModes)
@pytest.mark.parametrize("pcm", PictureCodingModes)
def test_produces_correct_dict_type(self, picture_generator, vp, ssm, pcm):
vp["source_sampling"] = ssm
int_types = (int, )
if sys.version_info < (3, 0, 0):
int_types += (long, ) # noqa: F821
for picture in list(picture_generator(vp, pcm)):
assert isinstance(picture["Y"], list)
assert isinstance(picture["Y"][0], list)
assert type(picture["Y"][0][0]) in int_types
assert isinstance(picture["C1"], list)
assert isinstance(picture["C1"][0], list)
assert type(picture["C1"][0][0]) in int_types
assert isinstance(picture["C2"], list)
assert isinstance(picture["C2"][0], list)
assert type(picture["C2"][0][0]) in int_types
assert isinstance(picture["pic_num"], int)
@pytest.mark.parametrize("ssm", SourceSamplingModes)
@pytest.mark.parametrize("pcm", PictureCodingModes)
def test_produces_whole_number_of_frames(self, picture_generator, vp, ssm,
pcm):
vp["source_sampling"] = ssm
pictures = list(picture_generator(vp, pcm))
if pcm == PictureCodingModes.pictures_are_frames:
assert len(pictures) >= 1
else:
# Must have even number of frames
assert len(pictures) >= 2
assert (len(pictures) % 2) == 0
# Even/odd fields must have even/odd picture numbers
for i, picture in enumerate(pictures):
assert (picture["pic_num"] % 2) == (i % 2)
# Picture numbers must be consecutive
last_num = pictures[0]["pic_num"]
for picture in pictures[1:]:
assert picture["pic_num"] == last_num + 1
last_num += 1
@pytest.mark.parametrize("ssm", SourceSamplingModes)
@pytest.mark.parametrize("pcm", PictureCodingModes)
@pytest.mark.parametrize("cds", ColorDifferenceSamplingFormats)
def test_produces_correct_picture_sizes(self, picture_generator, vp, ssm,
pcm, cds):
vp["source_sampling"] = ssm
vp["color_diff_format_index"] = cds
picture = list(picture_generator(vp, pcm))[0]
y = np.array(picture["Y"])
c1 = np.array(picture["C1"])
c2 = np.array(picture["C2"])
dd = compute_dimensions_and_depths(vp, pcm)
assert y.shape == (dd["Y"].height, dd["Y"].width)
assert c1.shape == (dd["C1"].height, dd["C1"].width)
assert c2.shape == (dd["C2"].height, dd["C2"].width)
@pytest.mark.parametrize("width,height", [(1, 1), (1, 10), (10, 1)])
def test_supports_absurd_video_sizes(self, picture_generator, vp, width,
height):
# Should produce a couple of frames for multi-frame generators
vp["frame_rate_numer"] = 2
vp["frame_rate_denom"] = 1
vp["frame_width"] = width
vp["frame_height"] = height
pcm = PictureCodingModes.pictures_are_frames
# Mustn't crash...
list(picture_generator(vp, pcm))
def test_one_repeat(self, pictures):
assert list(repeat_pictures(iter(pictures), 1)) == pictures
def test_zero_repeats(self, pictures):
assert list(repeat_pictures(iter(pictures), 0)) == []
def signal_range(codec_features):
"""
**Tests that a decoder has sufficient numerical dynamic range.**
These test cases contain a series of pictures containing test patterns
designed to produce extreme signals within decoders. During these test
cases, no integer clamping (except for final output clamping) or integer
overflows must occur.
A test case is produced for each picture component:
``signal_range[Y]``
Luma component test patterns.
``signal_range[C1]``
Color difference 1 component test patterns.
``signal_range[C2]``
Color difference 2 component test patterns.
These test cases are produced by encoding pictures consisting test patterns
made up of entirely of legal (in range) signal values. Nevertheless, the
resulting bitstreams produce large intermediate values within a decoder,
though these are not guaranteed to be worst-case.
.. note::
For informational purposes, an example of a set of test patterns before
and after encoding and quantisation is shown below:
.. image:: /_static/user_guide/signal_range_decoder.svg
.. note::
The quantization indices used for lossy codecs are chosen to maximise
the peak signal range produced by the test patterns. These are often
higher than a typical VC-2 encoder might pick for a given bit rate but
are nevertheless valid.
An informative metadata file is provided along side each test case which
gives, for each picture in the bitstream, the parts of a decoder which are
being tested by the test patterns. See
:py:class:`vc2_bit_widths.helpers.TestPoint` for details.
"""
try:
(
analysis_luma_pictures,
synthesis_luma_pictures,
analysis_color_diff_pictures,
synthesis_color_diff_pictures,
) = get_test_pictures(codec_features)
except MissingStaticAnalysisError:
logging.warning(
(
"No static analysis available for the wavelet "
"used by codec '%s'. Signal range test cases cannot "
"be generated."
),
codec_features["name"],
)
return
for component, analysis_test_pictures, synthesis_test_pictures in [
("Y", analysis_luma_pictures, synthesis_luma_pictures),
("C1", analysis_color_diff_pictures, synthesis_color_diff_pictures),
("C2", analysis_color_diff_pictures, synthesis_color_diff_pictures),
]:
# For lossless codecs we use the analysis test patterns since no
# quantisation takes place
if codec_features["lossless"]:
test_pictures = analysis_test_pictures
else:
test_pictures = synthesis_test_pictures
# Generate an initially empty set of mid-gray pictures
one_gray_frame = list(
mid_gray(
codec_features["video_parameters"],
codec_features["picture_coding_mode"],
)
)
pictures = list(
repeat_pictures(
one_gray_frame,
((len(test_pictures) + len(one_gray_frame) - 1) // len(one_gray_frame)),
)
)
# Fill-in the test patterns
minimum_qindices = []
for test_picture, picture in zip(test_pictures, pictures):
picture[component] = test_picture.picture.tolist()
if codec_features["lossless"]:
minimum_qindices.append(0)
else:
minimum_qindices.append(test_picture.quantisation_index)
while len(minimum_qindices) < len(pictures):
minimum_qindices.append(0)
# Extract the testpoints in JSON-serialisable form
metadata = [[tp._asdict() for tp in p.test_points] for p in test_pictures]
# Encode
sequence = make_sequence(
codec_features,
pictures,
minimum_qindex=minimum_qindices,
)
# Check the desired qindex could be used (should only ever fail for
# absurdly low bitrate configurations).
num_unexpected_qindices = 0
expected_qindex = None
expected_qindex_iter = iter(minimum_qindices)
for _, sx, sy, slice in iter_slices_in_sequence(codec_features, sequence):
if sx == 0 and sy == 0:
expected_qindex = next(expected_qindex_iter, 0)
if slice["qindex"] != expected_qindex:
num_unexpected_qindices += 1
if num_unexpected_qindices > 0:
logging.warning(
"Could not assign the required qindex to %d picture slices "
"for signal range test case due to a small picture_bytes value. "
"Peak signal levels might be reduced.",
num_unexpected_qindices,
)
yield TestCase(
Stream(sequences=[sequence]),
component,
metadata=metadata,
)