def test_fundamentals():
"""
Tests basic funtionality to identify if the behavior of the class
corresponds to the expected given the inializing data.
"""
shape = (100, 100, 3)
image = np.zeros(shape, dtype=np.uint8)
# Initilized with a box
b = bounding_region.BoundingRegion(shape, box=np.array([10, 20, 15, 45]))
b.draw_box(image, (255, 255, 0))
assert (np.allclose(image[20, 10], np.array([255, 255, 0])))
assert (np.allclose(image[20, 25], np.array([255, 255, 0])))
assert (np.allclose(image[65, 25], np.array([255, 255, 0])))
assert (np.allclose(image[65, 10], np.array([255, 255, 0])))
# Initilized with a contour
image = np.zeros(shape, dtype=np.uint8)
b = bounding_region.BoundingRegion(shape,
contour=np.array([[[10, 20]], [[25,
20]],
[[25, 65]], [[10,
65]]]))
b.draw_box(image, (255, 255, 0))
assert (np.allclose(image[20, 10], np.array([255, 255, 0])))
assert (np.allclose(image[20, 25], np.array([255, 255, 0])))
assert (np.allclose(image[65, 25], np.array([255, 255, 0])))
assert (np.allclose(image[65, 10], np.array([255, 255, 0])))
def test_area():
"""
Tests if the contour being drawn on the picture has the same area as the one
used to initialize the class.
"""
shape = (100, 100, 3)
image = np.zeros(shape, dtype=np.uint8)
# Initilized with a box
b = bounding_region.BoundingRegion(shape, box=np.array([10, 20, 15, 45]))
b.draw_box(image, (255, 255, 255), thickness=-1)
imgray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
contours, hierarchy = cv2.findContours(imgray,
mode=cv2.RETR_TREE,
method=cv2.CHAIN_APPROX_SIMPLE)
assert (len(contours) == 1)
area = cv2.contourArea(contours[0])
assert (area == b.get_area_pixels())
# Initilized with a contour
image = np.zeros(shape, dtype=np.uint8)
b = bounding_region.BoundingRegion(shape,
contour=np.array([[[10, 20]], [[25,
20]],
[[25, 65]], [[10,
65]]]))
b.draw_box(image, (255, 255, 255), thickness=-1)
imgray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
contours, hierarchy = cv2.findContours(imgray,
mode=cv2.RETR_TREE,
method=cv2.CHAIN_APPROX_SIMPLE)
assert (len(contours) == 1)
area = cv2.contourArea(contours[0])
assert (area == b.get_area_pixels())
def test_scaling():
"""
Tests if the scaling functionality result in correct behavior
"""
shape = (100, 100, 3)
# Initilized with a box
image = np.zeros(shape)
b = bounding_region.BoundingRegion(shape, box=np.array([40, 40, 20, 20]))
b.scale(0.5)
b.draw_box(image, (255, 255, 0))
assert (np.allclose(image[45, 45], np.array([255, 255, 0])))
assert (np.allclose(image[45, 55], np.array([255, 255, 0])))
assert (np.allclose(image[55, 55], np.array([255, 255, 0])))
assert (np.allclose(image[55, 45], np.array([255, 255, 0])))
b.scale(2.0)
b.draw_box(image, (0, 255, 0))
assert (np.allclose(image[40, 40], np.array([0, 255, 0])))
assert (np.allclose(image[40, 60], np.array([0, 255, 0])))
assert (np.allclose(image[60, 40], np.array([0, 255, 0])))
assert (np.allclose(image[60, 60], np.array([0, 255, 0])))
b.scale(2.0)
b.draw_box(image, (0, 255, 255))
assert (np.allclose(image[30, 30], np.array([0, 255, 255])))
assert (np.allclose(image[30, 70], np.array([0, 255, 255])))
assert (np.allclose(image[70, 30], np.array([0, 255, 255])))
assert (np.allclose(image[70, 70], np.array([0, 255, 255])))
image = np.zeros(shape)
# Initilized with a contour
b = bounding_region.BoundingRegion(shape,
contour=np.array([[[40, 40]], [[40,
60]],
[[60, 60]], [[60,
40]]]))
b.scale(0.5)
b.draw_box(image, (255, 255, 0))
assert (np.allclose(image[45, 45], np.array([255, 255, 0])))
assert (np.allclose(image[45, 55], np.array([255, 255, 0])))
assert (np.allclose(image[55, 55], np.array([255, 255, 0])))
assert (np.allclose(image[55, 45], np.array([255, 255, 0])))
b.scale(2.0)
b.draw_box(image, (0, 255, 0))
assert (np.allclose(image[40, 40], np.array([0, 255, 0])))
assert (np.allclose(image[40, 60], np.array([0, 255, 0])))
assert (np.allclose(image[60, 40], np.array([0, 255, 0])))
assert (np.allclose(image[60, 60], np.array([0, 255, 0])))
b.scale(2.0)
b.draw_box(image, (0, 255, 255))
assert (np.allclose(image[30, 30], np.array([0, 255, 255])))
assert (np.allclose(image[30, 70], np.array([0, 255, 255])))
assert (np.allclose(image[70, 30], np.array([0, 255, 255])))
assert (np.allclose(image[70, 70], np.array([0, 255, 255])))
def test_box_intersection_randomized():
"""
Deeper test runs 1000 times to verify that the intersection is right each time.
"""
for i in xrange(1000):
shape = (100, 100, 3)
# Initilized with a box
box1 = np.random.randint(low=10, high=30, size=(4, 1))
box2 = np.random.randint(low=10, high=30, size=(4, 1))
b1 = bounding_region.BoundingRegion(image_shape=shape, box=box1)
b2 = bounding_region.BoundingRegion(image_shape=shape, box=box2)
mask1 = b1.get_mask()
mask2 = b2.get_mask()
b3 = b1.get_box_intersection(b2)
b3.set_image_shape(shape=shape)
mask3 = b3.get_mask()
mask4 = cv2.bitwise_and(mask1, mask2)
assert (np.allclose(mask3, mask4))
def test_box_intersection():
"""
Simple static test to verify the intersection is indeed an intersection
"""
shape = (100, 100, 3)
image = np.zeros(shape, dtype=np.uint8)
# Initilized with a box
b1 = bounding_region.BoundingRegion(image_shape=shape,
box=np.array([10, 20, 15, 45]))
b2 = bounding_region.BoundingRegion(image_shape=shape,
box=np.array([20, 60, 15, 25]))
mask1 = b1.get_mask()
mask2 = b2.get_mask()
b3 = b1.get_box_intersection(b2)
b3.set_image_shape(shape=shape)
mask3 = b3.get_mask()
mask4 = cv2.bitwise_and(mask1, mask2)
assert (np.allclose(mask3, mask4))
def test_initialization():
"""
Test if the bounding regions initialized with a box and a corresponding contour
are exactly the same in every possible aspect
"""
shape = (100, 100, 3)
b = bounding_region.BoundingRegion(shape, box=np.array([10, 20, 15, 45]))
c = bounding_region.BoundingRegion(shape,
contour=np.array([[[10, 20]], [[25,
20]],
[[25, 65]], [[10,
65]]]))
assert (np.allclose(b.get_box_pixels(), c.get_box_pixels()))
assert (np.allclose(b.get_contour_pixels(), c.get_contour_pixels()))
assert (np.allclose(b.get_contour_relative(), c.get_contour_relative()))
assert (b.get_box_center_pixels() == c.get_box_center_pixels())
assert (b.get_box_center_relative() == c.get_box_center_relative())
assert (b.get_centroid_pixels() == c.get_centroid_pixels())
assert (b.get_centroid_relative() == c.get_centroid_relative())
assert (b.get_area_pixels() == c.get_area_pixels())
assert (b.get_area_relative() == c.get_area_relative())
assert (b.get_perimeter_pixels() == c.get_perimeter_pixels())
def test_mask_randomized():
"""
Tests that the mask generation from the box work right.
"""
for i in xrange(1000):
shape = (100, 100)
image = np.zeros(shape, dtype=np.uint8)
# Initilized with a box
box1 = np.random.randint(low=10, high=30, size=(4, 1))
cv2.rectangle(image, (box1[0], box1[1]),
(box1[0] + box1[2], box1[1] + box1[3]),
color=255,
thickness=-1)
b1 = bounding_region.BoundingRegion(image_shape=shape, box=box1)
mask1 = b1.get_mask()
assert (np.allclose(image, mask1))