本文整理汇总了Python中object_detection.inputs.pad_input_data_to_static_shapes方法的典型用法代码示例。如果您正苦于以下问题：Python inputs.pad_input_data_to_static_shapes方法的具体用法？Python inputs.pad_input_data_to_static_shapes怎么用？Python inputs.pad_input_data_to_static_shapes使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类object_detection.inputs的用法示例。
在下文中一共展示了inputs.pad_input_data_to_static_shapes方法的14个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_images_and_additional_channels
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_images_and_additional_channels(self):
input_tensor_dict = {
fields.InputDataFields.image:
tf.placeholder(tf.float32, [None, None, 3]),
fields.InputDataFields.image_additional_channels:
tf.placeholder(tf.float32, [None, None, 2]),
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
[5, 6, 5])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image_additional_channels]
.shape.as_list(), [5, 6, 2]) 示例2: test_keypoints
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_keypoints(self):
input_tensor_dict = {
fields.InputDataFields.groundtruth_keypoints:
tf.placeholder(tf.float32, [None, 16, 4]),
fields.InputDataFields.groundtruth_keypoint_visibilities:
tf.placeholder(tf.bool, [None, 16]),
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_keypoints]
.shape.as_list(), [3, 16, 4])
self.assertAllEqual(
padded_tensor_dict[
fields.InputDataFields.groundtruth_keypoint_visibilities]
.shape.as_list(), [3, 16]) 示例3: test_clip_boxes_and_classes
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_clip_boxes_and_classes(self):
def graph_fn():
input_tensor_dict = {
fields.InputDataFields.groundtruth_boxes:
tf.random.uniform([5, 4]),
fields.InputDataFields.groundtruth_classes:
tf.random.uniform([2, 3], maxval=10, dtype=tf.int32),
fields.InputDataFields.num_groundtruth_boxes:
tf.constant(5)
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
return (padded_tensor_dict[fields.InputDataFields.groundtruth_boxes],
padded_tensor_dict[fields.InputDataFields.groundtruth_classes],
padded_tensor_dict[fields.InputDataFields.num_groundtruth_boxes])
(groundtruth_boxes, groundtruth_classes,
num_groundtruth_boxes) = self.execute_cpu(graph_fn, [])
self.assertAllEqual(groundtruth_boxes.shape, [3, 4])
self.assertAllEqual(groundtruth_classes.shape, [3, 3])
self.assertEqual(num_groundtruth_boxes, 3) 示例4: test_images_and_additional_channels
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_images_and_additional_channels(self):
input_tensor_dict = {
fields.InputDataFields.image:
test_utils.image_with_dynamic_shape(4, 3, 5),
fields.InputDataFields.image_additional_channels:
test_utils.image_with_dynamic_shape(4, 3, 2),
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
# pad_input_data_to_static_shape assumes that image is already concatenated
# with additional channels.
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
[5, 6, 5])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image_additional_channels]
.shape.as_list(), [5, 6, 2]) 示例5: test_keypoints
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_keypoints(self):
keypoints = test_utils.keypoints_with_dynamic_shape(10, 16, 4)
visibilities = tf.cast(tf.random.uniform(tf.shape(keypoints)[:-1], minval=0,
maxval=2, dtype=tf.int32), tf.bool)
input_tensor_dict = {
fields.InputDataFields.groundtruth_keypoints:
test_utils.keypoints_with_dynamic_shape(10, 16, 4),
fields.InputDataFields.groundtruth_keypoint_visibilities:
visibilities
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_keypoints]
.shape.as_list(), [3, 16, 4])
self.assertAllEqual(
padded_tensor_dict[
fields.InputDataFields.groundtruth_keypoint_visibilities]
.shape.as_list(), [3, 16]) 示例6: test_pad_images_boxes_and_classes
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_pad_images_boxes_and_classes(self):
input_tensor_dict = {
fields.InputDataFields.image:
tf.placeholder(tf.float32, [None, None, 3]),
fields.InputDataFields.groundtruth_boxes:
tf.placeholder(tf.float32, [None, 4]),
fields.InputDataFields.groundtruth_classes:
tf.placeholder(tf.int32, [None, 3]),
fields.InputDataFields.true_image_shape:
tf.placeholder(tf.int32, [3]),
fields.InputDataFields.original_image_spatial_shape:
tf.placeholder(tf.int32, [2])
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
[5, 6, 3])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.true_image_shape]
.shape.as_list(), [3])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.original_image_spatial_shape]
.shape.as_list(), [2])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_boxes]
.shape.as_list(), [3, 4])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_classes]
.shape.as_list(), [3, 3]) 示例7: test_do_not_pad_dynamic_images
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_do_not_pad_dynamic_images(self):
input_tensor_dict = {
fields.InputDataFields.image:
tf.placeholder(tf.float32, [None, None, 3]),
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[None, None])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
[None, None, 3]) 示例8: test_pad_images_boxes_and_classes
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_pad_images_boxes_and_classes(self):
input_tensor_dict = {
fields.InputDataFields.image:
tf.placeholder(tf.float32, [None, None, 3]),
fields.InputDataFields.groundtruth_boxes:
tf.placeholder(tf.float32, [None, 4]),
fields.InputDataFields.groundtruth_classes:
tf.placeholder(tf.int32, [None, 3]),
fields.InputDataFields.true_image_shape: tf.placeholder(tf.int32, [3]),
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
[5, 6, 3])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.true_image_shape]
.shape.as_list(), [3])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_boxes]
.shape.as_list(), [3, 4])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_classes]
.shape.as_list(), [3, 3]) 示例9: test_gray_images
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_gray_images(self):
input_tensor_dict = {
fields.InputDataFields.image:
tf.placeholder(tf.float32, [None, None, 1]),
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
[5, 6, 1]) 示例10: test_pad_images_boxes_and_classes
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_pad_images_boxes_and_classes(self):
input_tensor_dict = {
fields.InputDataFields.image:
tf.random.uniform([3, 3, 3]),
fields.InputDataFields.groundtruth_boxes:
tf.random.uniform([2, 4]),
fields.InputDataFields.groundtruth_classes:
tf.random.uniform([2, 3], minval=0, maxval=2, dtype=tf.int32),
fields.InputDataFields.true_image_shape:
tf.constant([3, 3, 3]),
fields.InputDataFields.original_image_spatial_shape:
tf.constant([3, 3])
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
[5, 6, 3])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.true_image_shape]
.shape.as_list(), [3])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.original_image_spatial_shape]
.shape.as_list(), [2])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_boxes]
.shape.as_list(), [3, 4])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_classes]
.shape.as_list(), [3, 3]) 示例11: test_images_and_additional_channels_errors
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_images_and_additional_channels_errors(self):
input_tensor_dict = {
fields.InputDataFields.image:
test_utils.image_with_dynamic_shape(10, 10, 3),
fields.InputDataFields.image_additional_channels:
test_utils.image_with_dynamic_shape(10, 10, 2),
fields.InputDataFields.original_image:
test_utils.image_with_dynamic_shape(10, 10, 3),
}
with self.assertRaises(ValueError):
_ = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6]) 示例12: test_gray_images
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_gray_images(self):
input_tensor_dict = {
fields.InputDataFields.image:
test_utils.image_with_dynamic_shape(4, 4, 1),
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.image].shape.as_list(),
[5, 6, 1]) 示例13: test_dense_pose
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_dense_pose(self):
input_tensor_dict = {
fields.InputDataFields.groundtruth_dp_num_points:
tf.constant([0, 2], dtype=tf.int32),
fields.InputDataFields.groundtruth_dp_part_ids:
tf.constant([[0, 0], [4, 23]], dtype=tf.int32),
fields.InputDataFields.groundtruth_dp_surface_coords:
tf.constant([[[0., 0., 0., 0.,], [0., 0., 0., 0.,]],
[[0.1, 0.2, 0.3, 0.4,], [0.6, 0.8, 0.6, 0.7,]]],
dtype=tf.float32),
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=1,
spatial_image_shape=[128, 128],
max_dp_points=200)
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_dp_num_points]
.shape.as_list(), [3])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_dp_part_ids]
.shape.as_list(), [3, 200])
self.assertAllEqual(
padded_tensor_dict[fields.InputDataFields.groundtruth_dp_surface_coords]
.shape.as_list(), [3, 200, 4]) 示例14: test_context_features
# 需要导入模块: from object_detection import inputs [as 别名]
# 或者: from object_detection.inputs import pad_input_data_to_static_shapes [as 别名]
def test_context_features(self):
context_memory_size = 8
context_feature_length = 10
max_num_context_features = 20
def graph_fn():
input_tensor_dict = {
fields.InputDataFields.context_features:
tf.ones([context_memory_size, context_feature_length]),
fields.InputDataFields.context_feature_length:
tf.constant(context_feature_length)
}
padded_tensor_dict = inputs.pad_input_data_to_static_shapes(
tensor_dict=input_tensor_dict,
max_num_boxes=3,
num_classes=3,
spatial_image_shape=[5, 6],
max_num_context_features=max_num_context_features,
context_feature_length=context_feature_length)
self.assertAllEqual(
padded_tensor_dict[
fields.InputDataFields.context_features].shape.as_list(),
[max_num_context_features, context_feature_length])
return padded_tensor_dict[fields.InputDataFields.valid_context_size]
valid_context_size = self.execute_cpu(graph_fn, [])
self.assertEqual(valid_context_size, context_memory_size)