alexnet_object_recognition.py¶
What is this?¶

Recognize object with Alex net by resizing input image to 227 x 227. This node requires pretrained chainer model. For training Alex net, please refer to chainer imagenet example
Subscribing Topic¶
~input
(sensor_msgs/Image
)Input image.
Publishing Topic¶
~output
(jsk_recognition_msgs/ClassificationResult
)Classification result of input image.
~debug/net_input
(sensor_msgs/Image
)Resized image to 227 x 227.
Parameters¶
~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
alex
oralex_batch_normalization
is only supported. See models in$(rospack find jsk_recognition_utils)/python/jsk_recognition_utils/chainermodels
.~model_file
(String, Required)Trained model file.
use_mask
(Bool, Default:False
)If true, topic
~input/mask
is enabled.~approximate_sync
(Bool, Default:False
)Use approximate synchronization policy.
~queue_size
(Int, Default:10
)Queue size for synchronization.
~slop
(Float, Default:0.1
)Slop for approximate sync.
Example¶
roslaunch jsk_perception sample_alexnet_object_recognition.launch