Python object_detection.core.box_list_ops.prune_outside_window() Examples
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code examples of object_detection.core.box_list_ops.prune_outside_window().
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Example #1
| Source File: box_list_ops_test.py From object_detection_with_tensorflow with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #2
| Source File: box_list_ops_test.py From tensorflow with BSD 2-Clause "Simplified" License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #3
| Source File: box_list_ops_test.py From Gun-Detector with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #4
| Source File: box_list_ops_test.py From ros_tensorflow with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #5
| Source File: box_list_ops_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #6
| Source File: box_list_ops_test.py From moveo_ros with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #7
| Source File: box_list_ops_test.py From hands-detection with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #8
| Source File: box_list_ops_test.py From object_detection_kitti with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #9
| Source File: box_list_ops_test.py From MBMD with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #10
| Source File: box_list_ops_test.py From Elphas with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #11
| Source File: box_list_ops_test.py From DOTA_models with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #12
| Source File: box_list_ops_test.py From object_detection_with_tensorflow with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #13
| Source File: box_list_ops_test.py From AniSeg with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #14
| Source File: box_list_ops_test.py From MAX-Object-Detector with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #15
| Source File: box_list_ops_test.py From Accident-Detection-on-Indian-Roads with GNU Affero General Public License v3.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #16
| Source File: box_list_ops_test.py From g-tensorflow-models with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #17
| Source File: box_list_ops_test.py From models with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
def graph_fn():
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
return pruned.get(), pruned.get_field('extra_data'), keep_indices
pruned_output, extra_data_out, keep_indices_out = self.execute_cpu(graph_fn,
[])
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
self.assertAllClose(pruned_output, exp_output)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #18
| Source File: box_list_ops_test.py From motion-rcnn with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #19
| Source File: box_list_ops_test.py From mtl-ssl with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #20
| Source File: box_list_ops_test.py From multilabel-image-classification-tensorflow with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #21
| Source File: box_list_ops_test.py From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #22
| Source File: box_list_ops_test.py From Person-Detection-and-Tracking with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #23
| Source File: box_list_ops_test.py From garbage-object-detection-tensorflow with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #24
| Source File: box_list_ops_test.py From ros_people_object_detection_tensorflow with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #25
| Source File: box_list_ops_test.py From HereIsWally with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #26
| Source File: box_list_ops_test.py From vehicle_counting_tensorflow with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #27
| Source File: box_list_ops_test.py From yolo_v2 with Apache License 2.0 | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #28
| Source File: box_list_ops_test.py From object_detector_app with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #29
| Source File: box_list_ops_test.py From Traffic-Rule-Violation-Detection-System with MIT License | 6 votes |
|
def test_prune_outside_window_filters_boxes_which_fall_outside_the_window(
self):
window = tf.constant([0, 0, 9, 14], tf.float32)
corners = tf.constant([[5.0, 5.0, 6.0, 6.0],
[-1.0, -2.0, 4.0, 5.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0],
[-10.0, -10.0, -9.0, -9.0],
[-100.0, -100.0, 300.0, 600.0]])
boxes = box_list.BoxList(corners)
boxes.add_field('extra_data', tf.constant([[1], [2], [3], [4], [5], [6]]))
exp_output = [[5.0, 5.0, 6.0, 6.0],
[2.0, 3.0, 5.0, 9.0],
[0.0, 0.0, 9.0, 14.0]]
pruned, keep_indices = box_list_ops.prune_outside_window(boxes, window)
with self.test_session() as sess:
pruned_output = sess.run(pruned.get())
self.assertAllClose(pruned_output, exp_output)
keep_indices_out = sess.run(keep_indices)
self.assertAllEqual(keep_indices_out, [0, 2, 3])
extra_data_out = sess.run(pruned.get_field('extra_data'))
self.assertAllEqual(extra_data_out, [[1], [3], [4]])
Example #30
| Source File: faster_rcnn_meta_arch.py From motion-rcnn with MIT License | 4 votes |
|
def _remove_invalid_anchors_and_predictions(
self,
box_encodings,
objectness_predictions_with_background,
anchors_boxlist,
clip_window):
"""Removes anchors that (partially) fall outside an image.
Also removes associated box encodings and objectness predictions.
Args:
box_encodings: 3-D float tensor of shape
[batch_size, num_anchors, self._box_coder.code_size] containing
predicted boxes.
objectness_predictions_with_background: 3-D float tensor of shape
[batch_size, num_anchors, 2] containing class
predictions (logits) for each of the anchors. Note that this
tensor *includes* background class predictions (at class index 0).
anchors_boxlist: A BoxList representing num_anchors anchors (for the RPN)
in absolute coordinates.
clip_window: a 1-D tensor representing the [ymin, xmin, ymax, xmax]
extent of the window to clip/prune to.
Returns:
box_encodings: 4-D float tensor of shape
[batch_size, num_valid_anchors, self._box_coder.code_size] containing
predicted boxes, where num_valid_anchors <= num_anchors
objectness_predictions_with_background: 2-D float tensor of shape
[batch_size, num_valid_anchors, 2] containing class
predictions (logits) for each of the anchors, where
num_valid_anchors <= num_anchors. Note that this
tensor *includes* background class predictions (at class index 0).
anchors: A BoxList representing num_valid_anchors anchors (for the RPN) in
absolute coordinates.
"""
pruned_anchors_boxlist, keep_indices = box_list_ops.prune_outside_window(
anchors_boxlist, clip_window)
def _batch_gather_kept_indices(predictions_tensor):
return tf.map_fn(
partial(tf.gather, indices=keep_indices),
elems=predictions_tensor,
dtype=tf.float32,
parallel_iterations=self._parallel_iterations,
back_prop=True)
return (_batch_gather_kept_indices(box_encodings),
_batch_gather_kept_indices(objectness_predictions_with_background),
pruned_anchors_boxlist)
