def test_import_images_are_ordered_and_unduplicated():
# we know that import_images returns images in path order
imgs = list(mio.import_images(mio.data_dir_path()))
imgs_filenames = [i.path.stem for i in imgs]
print(imgs_filenames)
exp_imgs_filenames = ['breakingbad', 'einstein', 'lenna', 'menpo_thumbnail', 'takeo', 'tongue']
assert exp_imgs_filenames == imgs_filenames
def test_import_lazy_list():
from menpo.base import LazyList
data_path = mio.data_dir_path()
ll = mio.import_images(data_path)
assert isinstance(ll, LazyList)
ll = mio.import_landmark_files(data_path)
assert isinstance(ll, LazyList)
def test_ioinfo():
# choose a random asset (all should have it!)
img = pio.import_builtin_asset('einstein.jpg')
path = pio.data_path_to('einstein.jpg')
assert(img.ioinfo.filepath == path)
assert(img.ioinfo.filename == 'einstein')
assert(img.ioinfo.extension == '.jpg')
assert(img.ioinfo.dir == pio.data_dir_path())
def test_path():
# choose a random asset (all should have it!)
img = mio.import_builtin_asset('einstein.jpg')
path = mio.data_path_to('einstein.jpg')
assert(img.path == path)
assert(img.path.stem == 'einstein')
assert(img.path.suffix == '.jpg')
assert(img.path.parent == mio.data_dir_path())
assert(img.path.name == 'einstein.jpg')
def test_import_images():
imgs_glob = os.path.join(pio.data_dir_path(), '*')
imgs = list(pio.import_images(imgs_glob))
imgs_filenames = set(i.ioinfo.filename for i in imgs)
exp_imgs_filenames = {'einstein', 'takeo', 'breakingbad', 'lenna'}
assert(len(exp_imgs_filenames - imgs_filenames) == 0)
def test_import_image_no_norm():
img_path = os.path.join(mio.data_dir_path(), 'einstein.jpg')
im = mio.import_image(img_path, normalise=False)
assert im.pixels.dtype == np.uint8
def test_import_images_zero_max_images():
# different since the conditional 'if max_assets' is skipped,
# thus all images might be imported.
list(mio.import_images(mio.data_dir_path(), max_images=0))
def test_image_paths():
ls = mio.image_paths(os.path.join(mio.data_dir_path(), '*'))
assert(len(ls) == 5)
def test_import_images():
imgs = list(mio.import_images(mio.data_dir_path()))
imgs_filenames = set(i.path.stem for i in imgs)
exp_imgs_filenames = {'einstein', 'takeo', 'breakingbad', 'lenna'}
assert(len(exp_imgs_filenames - imgs_filenames) == 0)
def test_import_images_zero_max_images():
# different since the conditional 'if max_assets' is skipped,
# thus all images might be imported.
list(mio.import_images(mio.data_dir_path(), max_images=0))
def test_image_paths():
ls = mio.image_paths(mio.data_dir_path())
assert (len(list(ls)) == 6)
def test_shuffle_kwarg_true_calls_shuffle(mock):
list(mio.import_images(mio.data_dir_path(), shuffle=True))
assert mock.called
def test_import_image():
img_path = mio.data_dir_path() / 'einstein.jpg'
im = mio.import_image(img_path)
assert im.pixels.dtype == np.float
assert im.n_channels == 1
def test_import_landmark_file():
lm_path = mio.data_dir_path() / 'einstein.pts'
mio.import_landmark_file(lm_path)
def test_import_landmark_file():
lm_path = mio.data_dir_path() / 'einstein.pts'
mio.import_landmark_file(lm_path)
def test_import_image_no_norm():
img_path = mio.data_dir_path() / 'einstein.jpg'
im = mio.import_image(img_path, normalise=False)
assert im.pixels.dtype == np.uint8
def test_import_image():
img_path = mio.data_dir_path() / 'einstein.jpg'
im = mio.import_image(img_path)
assert im.pixels.dtype == np.float
assert im.n_channels == 1
def test_import_as_generator():
import types
gen = mio.import_images(mio.data_dir_path(), as_generator=True)
assert isinstance(gen, types.GeneratorType)
gen = mio.import_landmark_files(mio.data_dir_path(), as_generator=True)
assert isinstance(gen, types.GeneratorType)
def test_shuffle_kwarg_true_calls_shuffle(mock):
list(mio.import_images(mio.data_dir_path(), shuffle=True))
assert mock.called
def test_import_image_no_norm():
img_path = mio.data_dir_path() / 'einstein.jpg'
im = mio.import_image(img_path, normalize=False)
assert im.pixels.dtype == np.uint8
def test_import_landmark_file():
lm_path = os.path.join(mio.data_dir_path(), 'einstein.pts')
mio.import_landmark_file(lm_path)
def test_import_images():
imgs = list(mio.import_images(mio.data_dir_path()))
imgs_filenames = set(i.path.stem for i in imgs)
exp_imgs_filenames = {'einstein', 'takeo', 'tongue', 'breakingbad', 'lenna',
'menpo_thumbnail'}
assert exp_imgs_filenames == imgs_filenames
def test_import_image():
img_path = os.path.join(mio.data_dir_path(), 'einstein.jpg')
mio.import_images(img_path)
def test_image_paths():
ls = mio.image_paths(mio.data_dir_path())
assert(len(list(ls)) == 6)
def test_import_mesh():
obj_path = os.path.join(mio.data_dir_path(), 'bunny.obj')
mio.import_images(obj_path)
def test_import_as_generator():
import types
gen = mio.import_images(mio.data_dir_path(), as_generator=True)
assert isinstance(gen, types.GeneratorType)
gen = mio.import_landmark_files(mio.data_dir_path(), as_generator=True)
assert isinstance(gen, types.GeneratorType)
def test_import_auto():
assets_glob = os.path.join(mio.data_dir_path(), '*')
assets = list(mio.import_auto(assets_glob))
assert(len(assets) == 6)
def test_import_images_negative_max_images():
list(mio.import_images(mio.data_dir_path(), max_images=-2))
def test_import_auto_max_meshes():
assets_glob = os.path.join(mio.data_dir_path(), '*')
assets = list(mio.import_auto(assets_glob, max_meshes=1))
assert(sum([isinstance(x, TriMesh) for x in assets]) == 1)
def test_mesh_paths():
ls = mio.mesh_paths(os.path.join(mio.data_dir_path(), '*'))
assert(len(ls) == 2)
def test_import_images_negative_max_images():
list(mio.import_images(mio.data_dir_path(), max_images=-2))
