def transcode(filename):
tmpname = test_utils.temporary_filename(suffix=os.path.splitext(filename)[1])
tmpnam_ = test_utils.temporary_filename(suffix=os.path.splitext(filename)[1])
try:
# complete transcoding test
image = load(filename)
# save with the same extension
write(image, tmpname)
# reload the image from the file
image2 = load(tmpname)
assert numpy.array_equal(image, image2)
# test getting part of the image as well
if len(image.shape) == 3:
subsample = image[:,::2,::2]
else:
subsample = image[::2,::2]
assert not subsample.flags.contiguous
write(subsample, tmpnam_)
image3 = load(tmpnam_)
assert numpy.array_equal(subsample, image3)
finally:
if os.path.exists(tmpname):
os.unlink(tmpname)
if os.path.exists(tmpnam_):
os.unlink(tmpnam_)
def test_image_load():
# test that the generic bob.io.image.load function works as expected
for filename in (
"test.jpg",
"cmyk.jpg",
"test.pbm",
"test_corrupted.pbm",
"test.pgm",
"test_corrupted.pgm",
"test.ppm",
"test_corrupted.ppm",
"test.gif",
):
full_file = datafile(filename, __name__)
# load with just image name
i1 = load(full_file)
assert i1.shape == (6, 4)
# Loading the last pgm file
full_file = datafile("test_spaces.pgm", __name__)
load(full_file).shape == (100, 100)
# Testing exception
with pytest.raises(RuntimeError):
load(os.path.splitext(full_file)[0] + ".unknown")
def transcode(filename):
tmpname = test_utils.temporary_filename(
suffix=os.path.splitext(filename)[1])
tmpnam_ = test_utils.temporary_filename(
suffix=os.path.splitext(filename)[1])
try:
# complete transcoding test
image = load(filename)
# save with the same extension
write(image, tmpname)
# reload the image from the file
image2 = load(tmpname)
assert numpy.array_equal(image, image2)
# test getting part of the image as well
if len(image.shape) == 3:
subsample = image[:, ::2, ::2]
else:
subsample = image[::2, ::2]
assert not subsample.flags.contiguous
write(subsample, tmpnam_)
image3 = load(tmpnam_)
assert numpy.array_equal(subsample, image3)
finally:
if os.path.exists(tmpname):
os.unlink(tmpname)
if os.path.exists(tmpnam_):
os.unlink(tmpnam_)
def test_open_file_leak():
import psutil
import tempfile
import gc
from . import reader
from bob.io.base import save
my_video = numpy.random.random_integers(0, 255, (10, 3, 256 * 4, 256 * 4))
process = psutil.Process()
def open_files_count(path):
return len([f for f in process.open_files() if f.path == path])
with tempfile.NamedTemporaryFile(suffix='.avi') as f:
path = f.name
save(my_video.astype('uint8'), path)
# Get a count before doing anything. This following count is 1 because
# NamedTemporaryFile keeps a pointer to this file. We will check if the
# count goes to 0 in the end!
last_count = open_files_count(path)
# load the video at once and see if the count is constant
load(path)
gc.collect()
new_count = open_files_count(path)
assert new_count == last_count, \
('We did not close all the files when loading the video at once. '
'old count: {}, new count: {}'.format(last_count, new_count))
# iterate over all frames and see if the count is constant
for frame in reader(path):
pass
gc.collect()
new_count = open_files_count(path)
assert new_count == last_count, \
('We did not close all the files when iterating over all frames. '
'old count: {}, new count: {}'.format(last_count, new_count))
# iterate over one frame and see if the count is constant
for frame in reader(path):
break
gc.collect()
new_count = open_files_count(path)
assert new_count == last_count, \
('We did not close all the files when iterating over one frame. '
'old count: {}, new count: {}'.format(last_count, new_count))
count = open_files_count(path)
assert count == 0, 'The temporary file was not closed! {}'.format(count)
def test_png_rgba_color(): # Read an indexed color PNG image, and compared with hardcoded values img = load(PNG_RGBA_COLOR) assert img.shape == (3, 22, 32) assert img[0, 0, 0] == 255 assert img[0, 17, 17] == 117
def test_png_rgba_color():
# Read an indexed color PNG image, and compared with hardcoded values
img = load(PNG_RGBA_COLOR)
assert img.shape == (3, 22, 32)
assert img[0, 0, 0] == 255
assert img[0, 17, 17] == 117
def test_get_skin_pixels():
"""
Test the skin colored pixels detection
"""
# to run face detection
import bob.ip.facedetect
mod = sys.modules.get(__name__) or loader.load_module(__name__)
# load face image
face = load(datafile('001.jpg', 'bob.rppg.base'))
from bob.rppg.ssr.ssr_utils import get_skin_pixels
# zero threshold -> the number of skin pixels is the number of pixels in the cropped face
skin_pixels = get_skin_pixels(face, 0, True, 0.0)
bbox, quality = bob.ip.facedetect.detect_single_face(face)
assert skin_pixels.shape[1] == (bbox.size[0] - 1) * bbox.size[1] # -1 because of the cropping
# same as before, but with provided bbox
bounding_boxes = [bbox]
skin_pixels = get_skin_pixels(face, 0, True, 0, bounding_boxes)
assert skin_pixels.shape[1] == (bbox.size[0] - 1) * bbox.size[1] # -1 because of the cropping
# threshold of 1.0 -> zero skin pixels
skin_pixels = get_skin_pixels(face, 0, True, 1, bounding_boxes)
assert skin_pixels.shape[1] == 0
def test_can_use_array_interface():
from . import reader
array = load(INPUT_VIDEO)
iv = reader(INPUT_VIDEO)
for frame_id, frame in zip(range(array.shape[0]), iv.__iter__()):
assert numpy.array_equal(array[frame_id, :, :, :], frame)
def test_slicing_0():
from . import reader
f = reader(INPUT_VIDEO)
objs = f[:]
for i, k in enumerate(load(INPUT_VIDEO)):
assert numpy.allclose(k, objs[i])
def test_png_gray_alpha():
# Read a gray+alpha PNG image, and compared with hardcoded values
img = load(PNG_GRAY_ALPHA)
assert img.shape == (22, 32)
assert img[0, 0] == 255
assert img[17, 17] == 51
def test_slicing_0():
from . import reader
f = reader(INPUT_VIDEO)
objs = f[:]
for i, k in enumerate(load(INPUT_VIDEO)):
assert numpy.allclose(k, objs[i])
def test_can_use_array_interface():
from . import reader
array = load(INPUT_VIDEO)
iv = reader(INPUT_VIDEO)
for frame_id, frame in zip(range(array.shape[0]), iv.__iter__()):
assert numpy.array_equal(array[frame_id,:,:,:], frame)
def test_iteration():
from . import reader
f = reader(INPUT_VIDEO)
objs = load(INPUT_VIDEO)
nose.tools.eq_(len(f), len(objs))
for l, i in zip(objs, f):
assert numpy.allclose(l, i)
def transcode(filename):
tmpname = test_utils.temporary_filename(suffix=os.path.splitext(filename)[1])
try:
# complete transcoding test
image = load(filename)
# save with the same extension
write(image, tmpname)
# reload the image from the file
image2 = load(tmpname)
assert numpy.array_equal(image, image2)
finally:
if os.path.exists(tmpname): os.unlink(tmpname)
def test_iteration():
from . import reader
f = reader(INPUT_VIDEO)
objs = load(INPUT_VIDEO)
nose.tools.eq_(len(f), len(objs))
for l, i in zip(objs, f):
assert numpy.allclose(l, i)
def read_write_check(data, numpy_assert=True):
"""Testing loading and save different file types"""
with tempfile.NamedTemporaryFile(prefix="bobtest_", suffix=".hdf5") as f:
save(data, f.name)
data2 = load(f.name)
if numpy_assert:
assert np.allclose(data, data2, atol=10e-5, rtol=10e-5)
else:
assert data == data2
def transcode(filename):
tmpname = test_utils.temporary_filename(
suffix=os.path.splitext(filename)[1])
try:
# complete transcoding test
image = load(filename)
# save with the same extension
write(image, tmpname)
# reload the image from the file
image2 = load(tmpname)
assert numpy.array_equal(image, image2)
finally:
if os.path.exists(tmpname):
os.unlink(tmpname)
def test_base_load_on_unicode():
try:
# Writing temp file for testing
tmpname = write_unicode_temp_file()
from . import reader
f = reader(tmpname)
objs = load(tmpname)
nose.tools.eq_(len(f), len(objs))
for l, i in zip(objs, f):
assert numpy.allclose(l.shape, i.shape)
finally:
if os.path.exists(tmpname): os.unlink(tmpname)
from bob.ip.draw import box, cross
from bob.ip.color import rgb_to_gray
from bob.ip.facedetect import detect_single_face
from bob.io.base import load
import bob.io.image
import matplotlib.pyplot as plt
def get_data(f):
from os.path import join
from pkg_resources import resource_filename
from bob.io.base import load
return load(resource_filename('bob.ip.flandmark', join('data', f)))
lena = load("Aaron_Eckhart_0001.jpg")
lena_gray = rgb_to_gray(lena)
bounding_box, quality = detect_single_face(lena)
bounding_box = bounding_box.scale(1.2, True)
y, x = bounding_box.topleft
height, width = bounding_box.size
width = height
# x, y, width, height = [214, 202, 183, 183] # Manual annotations
localizer = Flandmark()
keypoints = localizer.locate(lena_gray, y, x, height, width)
for k in keypoints:
print(int(k[0]))
print(int(k[1]))
# draw the keypoints and bounding box
box(lena, (y, x), (height, width), (255, 0, 0)) # red bounding box
print(int(y))
def test_png_indexed_trns():
# Read an tRNS PNG image (without alpha), and compared with hardcoded values
img = load(PNG_tRNS)
assert img.shape == (3, 22, 32)
assert img[0, 0, 0] == 255
assert img[0, 17, 17] == 117
def test_png_indexed_color_alpha():
# Read an indexed color+alpha PNG image, and compared with hardcoded values
img = load(PNG_INDEXED_COLOR_ALPHA)
assert img.shape == (3, 22, 32)
assert img[0, 0, 0] == 255
assert img[0, 17, 17] == 117
def test_mat_file_io_does_not_crash():
data = load(test_utils.datafile('test_cell.mat', __name__))
def test_png_gray_alpha(): # Read a gray+alpha PNG image, and compared with hardcoded values img = load(PNG_GRAY_ALPHA) assert img.shape == (22,32) assert img[0,0] == 255 assert img[17,17] == 51
def test_png_indexed_trns(): # Read an tRNS PNG image (without alpha), and compared with hardcoded values img = load(PNG_tRNS) assert img.shape == (3,22,32) assert img[0,0,0] == 255 assert img[0,17,17] == 117
def test_png_indexed_color_alpha(): # Read an indexed color+alpha PNG image, and compared with hardcoded values img = load(PNG_INDEXED_COLOR_ALPHA) assert img.shape == (3,22,32) assert img[0,0,0] == 255 assert img[0,17,17] == 117
def file_loader(files, original_directory, original_extension):
data = []
for path in files:
d = load(os.path.join(original_directory, path + original_extension))
data.append(d)
return data
def get_data(f):
from os.path import join
from pkg_resources import resource_filename
from bob.io.base import load
import bob.io.image
return load(resource_filename('bob.ip.flandmark', join('data', f)))
def test_mat_file_io_does_not_crash():
data = load(test_utils.datafile('test_cell.mat', __name__))
