def naive_compute_iou_matrix(sorted_detections, ground_truths):
"""Computes the iou scores between all pairs of geometries in a naive fashion.
Args:
sorted_detections (ndarray, list) : A ndarray of detections stored as:
* Bounding boxes for a given class where each row is a detection stored as:
``[BoundingBox, confidence]``
* Polygons for a given class where each row is a detection stored as:
``[Polygon, confidence]``
* Points for a given class where each row is a detection stored as:
``[Point, confidence]``
ground_truths (ndarray,list) : A ndarray of ground truth stored as:
* Bounding boxes for a given class where each row is a ground truth stored as:
``[BoundingBox]``
* Polygons for a given class where each row is a ground truth stored as:
``[Polygon]``
* Points for a given class where each row is a ground truth stored as:
``[Point]``
Returns:
ndarray : An IoU matrix (#detections, #ground truth)
"""
# We prepare the IoU matrix (#detection, #gt)
iou = np.zeros((sorted_detections.shape[0], len(ground_truths)))
# Naive iterative IoU matrix construction (Note: we iterate over the sorted detections)
for k, ground_truth in enumerate(ground_truths):
for m, detection in enumerate(sorted_detections):
iou[m, k] = area(intersection(detection[0], ground_truth[0])) / area(union(detection[0], ground_truth[0]))
return iou
def time_union_prec2(self):
pygeos.union(self.left, self.right, grid_size=2)
def time_union(self):
pygeos.union(self.left, self.right)
def test_union():
poly1, poly2 = pygeos.box(0, 0, 10, 10), pygeos.box(10, 0, 20, 10)
actual = pygeos.union(poly1, poly2)
expected = pygeos.box(0, 0, 20, 10)
assert pygeos.equals(actual, expected)