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import unittest
from numpy.testing import assert_allclose
from willow.image import JPEGImageFile
from willow.plugins.opencv import OpenCVColorImage, OpenCVGrayscaleImage
from willow.plugins.pillow import PillowImage
class TestOpenCVOperations(unittest.TestCase):
def setUp(self):
with open("tests/images/people.jpg", "rb") as f:
# Open the image via Pillow
pillow_image = PillowImage.open(JPEGImageFile(f))
buffer_rgb = pillow_image.to_buffer_rgb()
colour_image = OpenCVColorImage.from_buffer_rgb(buffer_rgb)
self.image = OpenCVGrayscaleImage.from_color(colour_image)
self.expected_features = [
[41.0, 206.0],
[16.0, 201.0],
[243.0, 208.0],
[79.0, 130.0],
[120.0, 24.0],
[43.0, 119.0],
[40.0, 165.0],
[37.0, 14.0],
[250.0, 59.0],
[98.0, 6.0],
[78.0, 61.0],
[201.0, 93.0],
[8.0, 114.0],
[189.0, 142.0],
[292.0, 188.0],
[201.0, 199.0],
[7.0, 154.0],
[198.0, 247.0],
[235.0, 55.0],
[22.0, 36.0],
]
self.expected_faces = [(272, 89, 364, 181), (91, 165, 187, 261)]
def test_get_size(self):
width, height = self.image.get_size()
self.assertEqual(width, 600)
self.assertEqual(height, 400)
def test_get_frame_count(self):
frames = self.image.get_frame_count()
self.assertEqual(frames, 1)
def test_has_alpha(self):
has_alpha = self.image.has_alpha()
self.assertFalse(has_alpha)
def test_has_animation(self):
has_animation = self.image.has_animation()
self.assertFalse(has_animation)
def test_detect_features(self):
features = self.image.detect_features()
self.assertIsInstance(features, list)
# There are 20 features in the image
self.assertEqual(len(features), 20)
assert_allclose(features, self.expected_features, atol=2)
def test_detect_faces(self):
faces = self.image.detect_faces()
self.assertIsInstance(faces, list)
# There are two faces in the image
self.assertEqual(len(faces), 2)
# Sort out list as there is no preferred order of the faces
assert_allclose(sorted(faces), sorted(self.expected_faces), atol=2)
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