8.1.1.7.1.2.1.1. blueoil.networks.keypoint_detection.base¶
8.1.1.7.1.2.1.1.1. Module Contents¶
8.1.1.7.1.2.1.1.1.1. Classes¶
base network for keypoint detection |
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class
blueoil.networks.keypoint_detection.base.Base(*args, **kwargs)¶ Bases:
blueoil.networks.base.BaseNetworkbase network for keypoint detection
This base network is for keypoint detection. Each keypoint detection network class should extend this class.
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placeholders(self)¶ Placeholders.
Return placeholders.
- Returns
Placeholders.
- Return type
tf.compat.v1.placeholder
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inference(self, images, is_training)¶ Inference.
- Parameters
images – images tensor. shape is (batch_num, height, width, channel)
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_colored_heatmaps(self, heatmaps, color, name='')¶ Visualize heatmaps with given color.
- Parameters
heatmaps – a Tensor of shape (batch_size, height, width, num_joints).
color – a numpy array of shape (batch_size, 1, 1, num_joints, 3).
name – str, name to display on tensorboard.
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static
py_post_process(heatmaps, num_dimensions=2, stride=2)¶ Convert from heatmaps to joints, it is mainly used for visualization and metrics in training time.
- Parameters
heatmaps – a numpy array of shape (batch_size, height, width, num_joints).
num_dimensions – int.
stride – int, stride = image_height / heatmap_height.
- Returns
a numpy array of shape (batch_size, num_joints, 3).
- Return type
batch_joints
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post_process(self, output)¶ Tensorflow mirror method for py_post_process(), it is mainly used for visualization and metrics in training time.
- Parameters
output – a Tensor of shape (batch_size, height, width, num_joints).
- Returns
a Tensor of shape (batch_size, num_joints, 3).
- Return type
joints
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static
py_visualize_output(images, heatmaps, stride=2)¶ Visualize pose estimation, it is mainly used for visualization in training time.
- Parameters
images – a numpy array of shape (batch_size, height, width, 3).
heatmaps – a numpy array of shape (batch_size, height, width, num_joints).
stride – int, stride = image_height / heatmap_height.
- Returns
a numpy array of shape (batch_size, height, width, 3).
- Return type
drawed_images
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_visualize_output(self, images, output, name='visualize_output')¶ A tensorflow mirror method for py_visualize_output().
- Parameters
images – a Tensor of shape (batch_size, height, width, 3).
output – a Tensor of shape (batch_size, height, width, num_joints).
name – str, name to display on tensorboard.
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_compute_oks(self, output, labels)¶ Compute object keypoint similarity between output and labels.
- Parameters
output – a Tensor of shape (batch_size, height, width, num_joints).
labels – a Tensor of shape (batch_size, height, width, num_joints).
- Returns
a Tensor represents object keypoint similarity.
- Return type
oks
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summary(self, output, labels=None)¶ Summary for tensorboard.
- Parameters
output – a Tensor of shape (batch_size, height, width, num_joints).
labels – a Tensor of shape (batch_size, height, width, num_joints).
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metrics(self, output, labels)¶ Compute metrics for single-person pose estimation task.
- Parameters
output – a Tensor of shape (batch_size, height, width, num_joints).
labels – a Tensor of shape (batch_size, height, width, num_joints).
- Returns
a dict, {metric_name: metric_tensor}. updates_op: an operation that increments the total and count variables appropriately.
- Return type
results
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