def main():
'''
An example of a join. We filter pairs based on time overlap, and merge
surviving pairs by taking the intersection over the time bounds and the
span of the spatial bounds (and adding the payloads).
'''
is1 = IntervalSet([
Interval(Bounds3D(0, 1, 0, 1, 0, 1), 1),
Interval(Bounds3D(0, 0.5, 0.5, 1, 0, 0.5), 2),
])
is2 = IntervalSet([
Interval(Bounds3D(0.5, 1, 0, 1, 0, 1), 4),
Interval(Bounds3D(0, 1, 0, 1, 0, 1), 8),
])
is3 = is1.join(
is2, Bounds3D.T(overlaps()), lambda i1, i2: Interval(
i1['bounds'].intersect_time_span_space(i2['bounds']), i1['payload']
+ i2['payload']))
print('is1:')
print(is1)
print('is2:')
print(is2)
print('is1 joined with is2:')
print(is3)
def main():
'''
An example of using IntervalSetMapping to handle annotations from multiple
videos.
'''
# Annotations for one video
is1 = IntervalSet([
Interval(Bounds3D(1, 10, 0.3, 0.4, 0.5, 0.6), 1),
Interval(Bounds3D(2, 5, 0.2, 0.8, 0.2, 0.3), 1),
Interval(Bounds3D(10, 11, 0.2, 0.7, 0.3, 0.5), 1),
Interval(Bounds3D(13, 15, 0.5, 1, 0, 0.5), 1),
Interval(Bounds3D(15, 19, 0.5, 1, 0, 0.5), 1),
Interval(Bounds3D(20, 20), payload=1),
Interval(Bounds3D(22, 22), payload=1),
Interval(Bounds3D(22, 23), payload=1),
])
# Annotations for a second video
is2 = IntervalSet([
Interval(Bounds3D(2, 5, 0.2, 0.8, 0.2, 0.4), 1),
Interval(Bounds3D(1, 10, 0.3, 0.4, 0.3, 0.6), 1),
Interval(Bounds3D(9, 11, 0.16, 0.17, 0.3, 0.5), 1),
Interval(Bounds3D(13, 15, 0.5, 1, 0, 0.5), 1),
Interval(Bounds3D(14, 19, 0.5, 1, 0, 0.5), 1),
])
# An IntervalSetMapping can store both
ism = IntervalSetMapping({1: is1, 2: is2})
# An IntervalSetMapping reflects IntervalSet operations
ism_coalesced = ism.coalesce(('t1', 't2'), Bounds3D.span, payload_plus)
other_ism = IntervalSetMapping({
1:
IntervalSet([Interval(Bounds3D(1, 5, 0, 1, 0, 1))]),
2:
IntervalSet([Interval(Bounds3D(10, 15, 0, 1, 0, 1))])
})
# For binary operations, IntervalSetMapping sends the operations to the
# correct underlying IntervalSets
isms_joined = ism.join(
other_ism, Bounds3D.T(overlaps()),
lambda i1, i2: Interval(i1['bounds'].combine_per_axis(
i2['bounds'], utils.bounds_intersect, utils.bounds_intersect, utils
.bounds_intersect)))
print('ism:')
print(ism)
print()
print('ism coalesced:')
print(ism_coalesced)
print()
print('other_ism:')
print(other_ism)
print()
print('ism joined with other_ism:')
print(isms_joined)