def test_completeness(
tmpdir,
extra_args,
exp_encoder,
exp_decoder,
expected_files,
):
with alternative_real_pictures():
assert (
main(
[CODEC_FEATURES_CSV, "--output", str(tmpdir), "--codecs", "minimal"]
+ extra_args
)
== 0
)
generated_files = set(
# Get relative paths within output dir
os.path.abspath(os.path.join(root, filename))[
len(os.path.abspath(str(tmpdir))) + 1 :
]
for root, dirs, files in os.walk(str(tmpdir))
for filename in files
)
if exp_encoder:
assert expected_files[0].issubset(generated_files)
else:
assert expected_files[0].isdisjoint(generated_files)
if exp_decoder:
assert expected_files[1].issubset(generated_files)
else:
assert expected_files[1].isdisjoint(generated_files)
def test_real_pictures(codec_features):
picture, video_parameters, picture_coding_mode = file_format.read(
LOVELL_IMAGE_PATH, )
codec_features["wavelet_index"] = WaveletFilters.le_gall_5_3
codec_features["wavelet_index_ho"] = WaveletFilters.le_gall_5_3
codec_features["dwt_depth"] = 2
codec_features["dwt_depth_ho"] = 0
codec_features["slices_x"] = 8
codec_features["slices_y"] = 16
codec_features["lossless"] = False
codec_features["picture_bytes"] = (64 * 64 * 2) // 2 # ~2:1 compression
codec_features["video_parameters"] = video_parameters
with alternative_real_pictures([LOVELL_IMAGE_PATH]):
stream = real_pictures(codec_features)
coded_pictures = encode_and_decode(stream)
assert len(coded_pictures) == 1
coded_picture = coded_pictures[0]
for component in ["Y", "C1", "C2"]:
before = np.array(picture[component])
after = np.array(coded_picture[component])
# Coding should be lossy
assert not np.array_equal(before, after)
# PSNR should be reasonable
error = after - before
square_error = error * error
mean_square_error = np.mean(square_error)
max_value = 255.0
peak_signal_to_noise_ratio = (20 * np.log(max_value) / np.log(10)) - (
10 * np.log(mean_square_error) / np.log(10))
# NB: This is a pretty low PSNR threshold but appropriate here since
# we're encoding a very small (and, for its size, very detailed) image.
assert peak_signal_to_noise_ratio > 45.0
def test_force(
tmpdir,
extra_args,
exp_fail,
):
with alternative_real_pictures():
fn = partial(
main,
[CODEC_FEATURES_CSV, "--output", str(tmpdir), "--codecs", "minimal"]
+ extra_args,
)
# First time should always work
fn()
if exp_fail:
with pytest.raises(SystemExit):
fn()
else:
fn()
from vc2_conformance.codec_features import CodecFeatures
from vc2_conformance.pseudocode.video_parameters import VideoParameters
from vc2_conformance.test_cases import ENCODER_TEST_CASE_GENERATOR_REGISTRY
from vc2_conformance.dimensions_and_depths import compute_dimensions_and_depths
from vc2_data_tables import PictureCodingModes
from sample_codec_features import MINIMAL_CODEC_FEATURES
from smaller_real_pictures import alternative_real_pictures
# NB: Test case generators run during test collection so we must replace the
# pictures with smaller ones (for performance reasons) during tests
with alternative_real_pictures():
ALL_TEST_CASES = [
(
codec_features,
list(
ENCODER_TEST_CASE_GENERATOR_REGISTRY.generate_test_cases(
codec_features, )),
) for codec_features in [
# Both picture coding modes
CodecFeatures(
MINIMAL_CODEC_FEATURES,
picture_coding_mode=PictureCodingModes.pictures_are_frames,
),
CodecFeatures(
MINIMAL_CODEC_FEATURES,
picture_coding_mode=PictureCodingModes.pictures_are_fields,
def expected_files():
"""
The (minimum) expected filenames which demonstrates all test cases were
tried.
"""
codec_feature_sets = {
"minimal": MINIMAL_CODEC_FEATURES,
}
encoder_test_files = set()
decoder_test_files = set()
with alternative_real_pictures():
for name, codec_features in codec_feature_sets.items():
for test_case in ENCODER_TEST_CASE_GENERATOR_REGISTRY.generate_test_cases(
codec_features
):
encoder_test_files.add(
os.path.join(
name,
"encoder",
test_case.name,
"picture_0.raw",
)
)
if test_case.metadata is not None:
encoder_test_files.add(
os.path.join(
name,
"encoder",
"{}_metadata.json".format(test_case.name),
)
)
for test_case in DECODER_TEST_CASE_GENERATOR_REGISTRY.generate_test_cases(
codec_features
):
decoder_test_files.add(
os.path.join(
name,
"decoder",
"{}.vc2".format(test_case.name),
)
)
decoder_test_files.add(
os.path.join(
name,
"decoder",
"{}_expected".format(test_case.name),
"picture_0.raw",
)
)
if test_case.metadata is not None:
decoder_test_files.add(
os.path.join(
name,
"decoder",
"{}_metadata.json".format(test_case.name),
)
)
return (encoder_test_files, decoder_test_files)