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| """Tests for object_detection.box_coder.faster_rcnn_box_coder.""" |
|
|
| import tensorflow as tf |
|
|
| from object_detection.box_coders import faster_rcnn_box_coder |
| from object_detection.core import box_list |
|
|
|
|
| class FasterRcnnBoxCoderTest(tf.test.TestCase): |
|
|
| def test_get_correct_relative_codes_after_encoding(self): |
| boxes = [[10.0, 10.0, 20.0, 15.0], [0.2, 0.1, 0.5, 0.4]] |
| anchors = [[15.0, 12.0, 30.0, 18.0], [0.1, 0.0, 0.7, 0.9]] |
| expected_rel_codes = [[-0.5, -0.416666, -0.405465, -0.182321], |
| [-0.083333, -0.222222, -0.693147, -1.098612]] |
| boxes = box_list.BoxList(tf.constant(boxes)) |
| anchors = box_list.BoxList(tf.constant(anchors)) |
| coder = faster_rcnn_box_coder.FasterRcnnBoxCoder() |
| rel_codes = coder.encode(boxes, anchors) |
| with self.test_session() as sess: |
| rel_codes_out, = sess.run([rel_codes]) |
| self.assertAllClose(rel_codes_out, expected_rel_codes) |
|
|
| def test_get_correct_relative_codes_after_encoding_with_scaling(self): |
| boxes = [[10.0, 10.0, 20.0, 15.0], [0.2, 0.1, 0.5, 0.4]] |
| anchors = [[15.0, 12.0, 30.0, 18.0], [0.1, 0.0, 0.7, 0.9]] |
| scale_factors = [2, 3, 4, 5] |
| expected_rel_codes = [[-1., -1.25, -1.62186, -0.911608], |
| [-0.166667, -0.666667, -2.772588, -5.493062]] |
| boxes = box_list.BoxList(tf.constant(boxes)) |
| anchors = box_list.BoxList(tf.constant(anchors)) |
| coder = faster_rcnn_box_coder.FasterRcnnBoxCoder( |
| scale_factors=scale_factors) |
| rel_codes = coder.encode(boxes, anchors) |
| with self.test_session() as sess: |
| rel_codes_out, = sess.run([rel_codes]) |
| self.assertAllClose(rel_codes_out, expected_rel_codes) |
|
|
| def test_get_correct_boxes_after_decoding(self): |
| anchors = [[15.0, 12.0, 30.0, 18.0], [0.1, 0.0, 0.7, 0.9]] |
| rel_codes = [[-0.5, -0.416666, -0.405465, -0.182321], |
| [-0.083333, -0.222222, -0.693147, -1.098612]] |
| expected_boxes = [[10.0, 10.0, 20.0, 15.0], [0.2, 0.1, 0.5, 0.4]] |
| anchors = box_list.BoxList(tf.constant(anchors)) |
| coder = faster_rcnn_box_coder.FasterRcnnBoxCoder() |
| boxes = coder.decode(rel_codes, anchors) |
| with self.test_session() as sess: |
| boxes_out, = sess.run([boxes.get()]) |
| self.assertAllClose(boxes_out, expected_boxes) |
|
|
| def test_get_correct_boxes_after_decoding_with_scaling(self): |
| anchors = [[15.0, 12.0, 30.0, 18.0], [0.1, 0.0, 0.7, 0.9]] |
| rel_codes = [[-1., -1.25, -1.62186, -0.911608], |
| [-0.166667, -0.666667, -2.772588, -5.493062]] |
| scale_factors = [2, 3, 4, 5] |
| expected_boxes = [[10.0, 10.0, 20.0, 15.0], [0.2, 0.1, 0.5, 0.4]] |
| anchors = box_list.BoxList(tf.constant(anchors)) |
| coder = faster_rcnn_box_coder.FasterRcnnBoxCoder( |
| scale_factors=scale_factors) |
| boxes = coder.decode(rel_codes, anchors) |
| with self.test_session() as sess: |
| boxes_out, = sess.run([boxes.get()]) |
| self.assertAllClose(boxes_out, expected_boxes) |
|
|
| def test_very_small_Width_nan_after_encoding(self): |
| boxes = [[10.0, 10.0, 10.0000001, 20.0]] |
| anchors = [[15.0, 12.0, 30.0, 18.0]] |
| expected_rel_codes = [[-0.833333, 0., -21.128731, 0.510826]] |
| boxes = box_list.BoxList(tf.constant(boxes)) |
| anchors = box_list.BoxList(tf.constant(anchors)) |
| coder = faster_rcnn_box_coder.FasterRcnnBoxCoder() |
| rel_codes = coder.encode(boxes, anchors) |
| with self.test_session() as sess: |
| rel_codes_out, = sess.run([rel_codes]) |
| self.assertAllClose(rel_codes_out, expected_rel_codes) |
|
|
|
|
| if __name__ == '__main__': |
| tf.test.main() |
|
|
