def create_test_camera() -> Tuple[Path, UUID]:
""" Helper function to create a test camera folder structure with images.
"""
testing.needs_internet()
# Get a temporary folder
path, id = testing.get_tmp_folder()
try:
# Create folder structure
for folder in FOLDERS:
try:
(path / folder).mkdir()
except FileExistsError:
pass
img_file = testing.get_remote_file(TEST_IMG_FILENAME)
img = imageio.imread(img_file)
# Mosaic
img = mosaic(img)
# Save test image, rotated image and BW image
imageio.imsave(path / FILES[0], img)
imageio.imsave(path / FILES[1], np.flipud(img))
imageio.imsave(path / FILES[2], (255 * img).astype(np.uint8))
imageio.imsave(path / FILES[3], img)
imageio.imsave(path / FILES[4], np.flipud(img))
imageio.imsave(path / FILES[5], (255 * img).astype(np.uint8))
except:
delete_test_camera(path, id)
return path, id
def test_from_mat():
testing.needs_internet()
# Get a temporary folder
path, id = testing.get_tmp_folder()
try:
path = path / "test_hsi.mat"
hsi_file = testing.get_remote_file(TEST_HSI_FILENAME)
hsi = np.load(hsi_file)
mdict = dict(data=hsi)
scipy.io.savemat(path, mdict)
# Try loading with and without key
for key in [None, 'data']:
tmp = SpectralImage.from_mat_file(path=path, key=key)
assert np.allclose(hsi, tmp)
finally:
# Cleanup temporary folder
testing.remove_tmp_folder(id)
return
def test_rgb_camera():
testing.needs_internet()
try:
# Create camera folder structure
path, id = create_test_camera()
test_camera = RgbCamera(path, bayer_pattern=PATTERN)
img_file = testing.get_remote_file(TEST_IMG_FILENAME)
img = imageio.imread(img_file)
img = mosaic(img)
img = demosaic.get_demosaiced(img,
pattern=PATTERN,
method='malvar2004')
img = np.clip(img, 0, 255) / 255.0
assert test_camera._bayerPattern == PATTERN
test_camera.load_sensor_image(0)
test_camera.decode_sensor_image(0)
tmp = test_camera.get_decoded_image(0)
# Test that demosaiced image is close to original
assert img.shape == tmp.shape
assert np.allclose(img, tmp, atol=0.05)
finally:
# Always clean up
delete_test_camera(path, id)
return
def test_get_rgb_image():
"""Test conversion of true RGB from multispectral image"""
testing.needs_internet()
hsi_file = testing.get_remote_file(TEST_HSI_FILENAME)
hsi = SpectralArray(np.load(hsi_file), dtype=np.float32)
rgb_file = testing.get_remote_file(TEST_RGB_FILENAME)
rgb = (imageio.imread(rgb_file) / 255.0).astype(np.float64)
grey_file = testing.get_remote_file(TEST_GREY_FILENAME)
grey = (imageio.imread(grey_file) / 255.0).astype(np.float64)[..., np.newaxis]
assert np.allclose(rgb, hsi.get_rgb(), atol=0.01)
# Test 1D real spectrum conversion
for x, y in zip([0, 10, 20], [10, 100, 200]):
spectrum = hsi[x, y, :]
rgb_point = rgb[x, y, :]
assert np.allclose(rgb_point, spectrum.get_rgb(), atol=0.01)
# Calculate black and white from rgb
grey_from_hsi = hsi.get_grey(weighted=True)
grey_from_rgb = SpectralArray(rgb, dtype=np.float32).get_grey(weighted=True)
grey_from_grey = SpectralArray(grey, dtype=np.float32).get_grey(weighted=True)
assert np.allclose(grey, grey_from_grey, atol=0.01)
assert np.allclose(grey, grey_from_rgb, atol=0.01)
assert np.allclose(grey, grey_from_hsi, atol=0.01)
return
def test_get_edges():
"""This only tests for failure, not for correct edge detection..."""
testing.needs_internet()
im_file = testing.get_remote_file(TEST_GREY_FILENAME)
im = imageio.imread(im_file)
methods = ["scharr", "sobel", "dog", "log", "gradient"]
for method in methods:
edge = images.get_edges(im, method=method)
# Test kwargs options for DOG, LOG
edge = images.get_edges(im, method='log', sigma=4)
edge = images.get_edges(im, method='dog', sigma=4)
# Color input
im_file = testing.get_remote_file(TEST_RGB_FILENAME)
im = imageio.imread(im_file)
with raises(ValueError) as cm:
images.get_gradients(im, method='scharr')
assert "Gradient calculation only works on 2D images right now. " \
"For multi-dimensional arrays, use numpy's gradient() instead." == str(cm.value)
return
def create_test_camera():
"""Download the Raytracer test camera, if not already present."""
testing.needs_internet()
for ext in [".png", ".json"]:
testing.get_remote_file("cameras/RayTracerSmall/Calibration/cal_img" + ext)
testing.get_remote_file("cameras/RayTracerSmall/Images/example_img" + ext)
return
def create_test_lytro_camera_small():
"""Download the Lytro test camera, if not already present."""
testing.needs_internet()
for file in ["MOD_0001", "MOD_0016", "MOD_0033"]:
testing.get_remote_file("cameras/LytroIllumSmall/Calibration/" + file + ".bsdf")
testing.get_remote_file("cameras/LytroIllumSmall/Images/IIIT.bsdf")
return
def create_test_lytro_camera():
"""Download the Lytro test camera, if not already present."""
testing.needs_internet()
for file in ["MOD_0033"]:
testing.get_remote_file("cameras/LytroIllum/Calibration/" + file + ".RAW")
testing.get_remote_file("cameras/LytroIllum/Calibration/" + file + ".TXT")
testing.get_remote_file("cameras/LytroIllum/Images/IIIT.LFR")
return
def test_from_file_collection():
testing.needs_internet()
for i in range(1, 32):
fname = TEST_FILE_COLLECTION + f"balloons_ms_{i:02d}.png"
testing.get_remote_file(fname)
# Read from file collection
path = testing.appdata_dir(APPNAME) / TEST_FILE_COLLECTION
tmp = SpectralImage.from_file_collection(path=path)
hsi_file = testing.get_remote_file(TEST_HSI_FILENAME)
hsi = np.load(hsi_file)
assert np.allclose(hsi, tmp)
return
def test_from_file():
"""Test from_file() classmethod. Read RGB image."""
testing.needs_internet()
rgb_file = testing.get_remote_file(TEST_RGB_FILENAME)
rgb = (imageio.imread(rgb_file) / 255.0).astype(np.float32)
tmp = SpectralImage.from_file(rgb_file, format='PNG', dtype=np.float32)
assert np.allclose(rgb, tmp)
grey_file = testing.get_remote_file(TEST_GREY_FILENAME)
grey = (imageio.imread(grey_file) / 255.0).astype(np.float32)
assert grey.ndim == 2
tmp = SpectralImage.from_file(grey_file, format='PNG', dtype=np.float32)
assert tmp.ndim == 3
return
def test_band_info_envi():
"""Test ``from_envi`` class method.
"""
testing.needs_internet()
envi_file = testing.get_remote_file(TEST_ENVI_HDR)
d = SpectralArray.read_envi_header(envi_file)
band_info = BandInfo.from_envi_header(d)
centers_exp = np.asarray([400.6, 450.3, 500, 551.7, 600.666, 760.9])
bandwiths_exp = np.asarray([1.1, 1.2, 1.3, 1.4, 1.5, 1.6])
assert 6 == band_info.num_channels
assert band_info.type is None
assert band_info.centers_std is None
assert band_info.bandwidths_std is None
assert np.array_equal(centers_exp, band_info.centers)
assert np.array_equal(bandwiths_exp, band_info.bandwidths)
return
def create_test_camera() -> Tuple[Path, UUID]:
""" Helper function to create a test camera folder structure with images.
"""
testing.needs_internet()
# Get a temporary folder
path, id = testing.get_tmp_folder()
try:
# Create folder structure
for folder in FOLDERS:
try:
(path / folder).mkdir()
except FileExistsError:
pass
img_file = testing.get_remote_file(TEST_IMG_FILENAME)
img = imread(img_file)
# Save test image
imsave(path / FILES[0], img)
# Create greyscale whiteimages
whiteimg_1 = (255 * np.ones(
(img.shape[0], img.shape[1]))).astype(np.uint8)
whiteimg_2 = (127 * np.ones(
(img.shape[0], img.shape[1]))).astype(np.uint8)
# Save whiteimages
imsave(path / FILES[1], whiteimg_1)
imsave(path / FILES[2], whiteimg_2)
except:
delete_test_camera(path, id)
return path, id