Python object_detection.utils.np_box_ops.iou() Examples
The following are 30
code examples of object_detection.utils.np_box_ops.iou().
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Example #1
| Source File: np_box_list_ops.py From object_detection_with_tensorflow with MIT License | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #2
| Source File: np_box_ops_test.py From open-solution-googleai-object-detection with MIT License | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #3
| Source File: np_box_list_ops.py From MAX-Object-Detector with Apache License 2.0 | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #4
| Source File: np_box_ops_test.py From MAX-Object-Detector with Apache License 2.0 | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #5
| Source File: np_box_list_ops.py From models with Apache License 2.0 | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #6
| Source File: target_assigner_test.py From models with Apache License 2.0 | 5 votes |
|
def test_max_distance_for_overlap(self):
"""Test that the distance ensures the IoU with random boxes."""
# TODO(vighneshb) remove this after the `_smallest_positive_root`
# function if fixed.
self.skipTest(('Skipping test because we are using an incorrect version of'
'the `max_distance_for_overlap` function to reproduce'
' results.'))
rng = np.random.RandomState(0)
n_samples = 100
width = rng.uniform(1, 100, size=n_samples)
height = rng.uniform(1, 100, size=n_samples)
min_iou = rng.uniform(0.1, 1.0, size=n_samples)
def graph_fn():
max_dist = targetassigner.max_distance_for_overlap(height, width, min_iou)
return max_dist
max_dist = self.execute(graph_fn, [])
xmin1 = np.zeros(n_samples)
ymin1 = np.zeros(n_samples)
xmax1 = np.zeros(n_samples) + width
ymax1 = np.zeros(n_samples) + height
xmin2 = max_dist * np.cos(rng.uniform(0, 2 * np.pi))
ymin2 = max_dist * np.sin(rng.uniform(0, 2 * np.pi))
xmax2 = width + max_dist * np.cos(rng.uniform(0, 2 * np.pi))
ymax2 = height + max_dist * np.sin(rng.uniform(0, 2 * np.pi))
boxes1 = np.vstack([ymin1, xmin1, ymax1, xmax1]).T
boxes2 = np.vstack([ymin2, xmin2, ymax2, xmax2]).T
iou = np.diag(np_box_ops.iou(boxes1, boxes2))
self.assertTrue(np.all(iou >= min_iou))
Example #7
| Source File: np_box_ops_test.py From motion-rcnn with MIT License | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #8
| Source File: np_box_list_ops.py From motion-rcnn with MIT License | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #9
| Source File: np_box_ops_test.py From mtl-ssl with Apache License 2.0 | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #10
| Source File: np_box_list_ops.py From mtl-ssl with Apache License 2.0 | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #11
| Source File: np_box_ops_test.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #12
| Source File: np_box_list_ops.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #13
| Source File: np_box_ops_test.py From models with Apache License 2.0 | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #14
| Source File: np_box_list_ops.py From object_detection_with_tensorflow with MIT License | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #15
| Source File: np_box_ops_test.py From object_detection_with_tensorflow with MIT License | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #16
| Source File: np_box_ops_test.py From AniSeg with Apache License 2.0 | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #17
| Source File: np_box_ops_test.py From object_detection_with_tensorflow with MIT License | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #18
| Source File: np_box_list_ops.py From Elphas with Apache License 2.0 | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #19
| Source File: np_box_ops_test.py From Elphas with Apache License 2.0 | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #20
| Source File: np_box_list_ops.py From MBMD with MIT License | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #21
| Source File: np_box_ops_test.py From MBMD with MIT License | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #22
| Source File: np_box_list_ops.py From object_detection_kitti with Apache License 2.0 | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #23
| Source File: np_box_ops_test.py From object_detection_kitti with Apache License 2.0 | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #24
| Source File: np_box_list_ops.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #25
| Source File: np_box_ops_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #26
| Source File: np_box_list_ops.py From hands-detection with MIT License | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #27
| Source File: np_box_ops_test.py From hands-detection with MIT License | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #28
| Source File: np_box_list_ops.py From moveo_ros with MIT License | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
Example #29
| Source File: np_box_ops_test.py From moveo_ros with MIT License | 5 votes |
|
def testIOU(self):
iou = np_box_ops.iou(self.boxes1, self.boxes2)
expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
[1.0 / 16.0, 0.0, 5.0 / 400.0]],
dtype=float)
self.assertAllClose(iou, expected_iou)
Example #30
| Source File: np_box_list_ops.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 5 votes |
|
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get())
