fcn_depth_prediction.py¶
What is this?¶

Predict depth of transparent object in pixel-wise with Fully Convolutional Networks.
Subscribing Topic¶
~input
(sensor_msgs/Image
)Raw RGB image.
~input/depth
(sensor_msgs/Image
)Raw depth image.
Publishing Topic¶
~output
(sensor_msgs/Image
)Output depth image. The value of each pixel is equal to
~output/depth_pred_raw
in the region labeled as transparent, otherwise equal to~input/depth
. The image encoding is 32FC1.~output/label
(sensor_msgs/Image
)Output label image. Each object is segmented according to param
~target_names
.~output/proba_image
(sensor_msgs/Image
)Probability image of each object predicted according to param
~target_names
. If the number of classes including background is XX, then the image encoding is 32FCXX.~output/depth_pred_raw
(sensor_msgs/Image
)Predicted whole depth image. This is used for generating
~output
. The image encoding is 32FC1.
Parameters¶
~backend
(String, Default:chainer
)Framework for neural networks. Currently, only
chainer
is supported.~gpu
(Int, Default:-1
)GPU id.
-1
represents CPU mode.~target_names
(List of String, Required)Target names for classification.
~model_name
(String, Required)Currently,
fcn8s_depth_prediction
andfcn8s_depth_prediction_concat_first
are supported.~model_file
(String, Required)Saved .npz file for trained model.
~bg_label
(Int, default:0
)Label value for background. This is used with rosparam
~proba_threshold
~proba_threshold
(Float, default:0.0
)Threshold for labeling pixels as uncertain, and the uncertain region will be labeled as background with rosparam
~bg_label
.~queue_size
(Int, default:10
)How many messages you allow about the subscriber to keep in the queue. This should be big when there is much difference about delay between two input topics.
~approximate_sync
(Bool, default:False
)Whether to use approximate for input topics.
~slop
(Float, default:0.1
)How many seconds you allow about the difference of timestamp. This is used only when param
~approximate_sync
istrue
.
Sample¶
roslaunch jsk_perception sample_fcn_depth_prediction.launch