alexnet_object_recognition.py

What is this?

../../../../_images/alexnet_object_recognition1.png

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 or alex_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