Python object_detection.utils.ops.normalized_to_image_coordinates() Examples
The following are 30
code examples of object_detection.utils.ops.normalized_to_image_coordinates().
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Example #1
| Source File: ops_test.py From hands-detection with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #2
| Source File: ops_test.py From multilabel-image-classification-tensorflow with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #3
| Source File: ops_test.py From mtl-ssl with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #4
| Source File: ops_test.py From motion-rcnn with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #5
| Source File: ops_test.py From g-tensorflow-models with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #6
| Source File: ops_test.py From open-solution-googleai-object-detection with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #7
| Source File: ops_test.py From MAX-Object-Detector with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #8
| Source File: ops_test.py From AniSeg with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #9
| Source File: ops_test.py From monopsr with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #10
| Source File: ops_test.py From object_detection_with_tensorflow with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #11
| Source File: ops_test.py From object_detection_with_tensorflow with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #12
| Source File: ops_test.py From Elphas with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #13
| Source File: ops_test.py From MBMD with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #14
| Source File: ops_test.py From object_detection_kitti with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #15
| Source File: ops_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #16
| Source File: ops_test.py From DOTA_models with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #17
| Source File: ops_test.py From moveo_ros with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #18
| Source File: ops_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #19
| Source File: ops_test.py From ros_tensorflow with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #20
| Source File: ops_test.py From Gun-Detector with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #21
| Source File: ops_test.py From tensorflow with BSD 2-Clause "Simplified" License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #22
| Source File: ops_test.py From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #23
| Source File: ops_test.py From Traffic-Rule-Violation-Detection-System with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #24
| Source File: ops_test.py From yolo_v2 with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #25
| Source File: ops_test.py From HereIsWally with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #26
| Source File: ops_test.py From garbage-object-detection-tensorflow with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #27
| Source File: ops_test.py From Person-Detection-and-Tracking with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #28
| Source File: ops_test.py From ros_people_object_detection_tensorflow with Apache License 2.0 | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #29
| Source File: ops_test.py From vehicle_counting_tensorflow with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
Example #30
| Source File: ops_test.py From object_detector_app with MIT License | 6 votes |
|
def test_normalized_to_image_coordinates(self):
normalized_boxes = tf.placeholder(tf.float32, shape=(None, 1, 4))
normalized_boxes_np = np.array([[[0.0, 0.0, 1.0, 1.0]],
[[0.5, 0.5, 1.0, 1.0]]])
image_shape = tf.convert_to_tensor([1, 4, 4, 3], dtype=tf.int32)
absolute_boxes = ops.normalized_to_image_coordinates(normalized_boxes,
image_shape,
parallel_iterations=2)
expected_boxes = np.array([[[0, 0, 4, 4]],
[[2, 2, 4, 4]]])
with self.test_session() as sess:
absolute_boxes = sess.run(absolute_boxes,
feed_dict={normalized_boxes:
normalized_boxes_np})
self.assertAllEqual(absolute_boxes, expected_boxes)
