gqcnn/cfg/examples/replication/dex-net_4.0_suction.yaml at a3eccff2ee75eaaf090e2af7c00fdf8760bebc8e · BerkeleyAutomation/gqcnn · GitHub

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# Copyright ©2017. The Regents of the University of California (Regents).
# All Rights Reserved. Permission to use, copy, modify, and distribute this
# software and its documentation for educational, research, and not-for-profit
# purposes, without fee and without a signed licensing agreement, is hereby
# granted, provided that the above copyright notice, this paragraph and the
# following two paragraphs appear in all copies, modifications, and
# distributions. Contact The Office of Technology Licensing, UC Berkeley, 2150
# Shattuck Avenue, Suite 510, Berkeley, CA 94720-1620, (510) 643-7201,
# otl@berkeley.edu,
# http://ipira.berkeley.edu/industry-info for commercial licensing opportunities.

# IN NO EVENT SHALL REGENTS BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL,
# INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF
# THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF REGENTS HAS BEEN
# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

# REGENTS SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE. THE SOFTWARE AND ACCOMPANYING DOCUMENTATION, IF ANY, PROVIDED
# HEREUNDER IS PROVIDED "AS IS". REGENTS HAS NO OBLIGATION TO PROVIDE
# MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.

policy:
  # optimization params
  num_seed_samples: 200
  num_gmm_samples: 50
  num_iters: 3
  gmm_refit_p: 0.25
  gmm_component_frac: 0.4
  gmm_reg_covar: 0.01

  # general params
  deterministic: 1
  gripper_width: 0.05
  crop_height: 96
  crop_width: 96

  # sampling params
  sampling:
    # type
    type: suction

    # params
    max_suction_dir_optical_axis_angle: 30
    delta_theta: 5
    delta_phi: 5
    sigma_depth: 0.0025
    min_suction_dist: 1.0
    angle_dist_weight: 5.0
    depth_gaussian_sigma: 1.0
    num_grasp_samples: 1000

    max_dist_from_center: 260
    max_num_samples: 10000

  # metric params
  metric:
    type: gqcnn
    gqcnn_model: models/GQCNN-4.0-SUCTION
    # openvino: OFF|CPU|GPU|MYRIAD
    openvino: OFF

    crop_height: 96
    crop_width: 96

  # visualization
  vis:
    grasp_sampling : 0
    tf_images: 0
    plane: 0
    grasp_candidates: 0
    elite_grasps: 0
    grasp_ranking: 0
    grasp_plan: 0
    grasp_affordance_map: 0
    final_grasp: 1

    vmin: 0.0
    vmax: 1.0

    k: 25

# image proc params
inpaint_rescale_factor: 0.5

# detection params
detection:
  type: point_cloud_box

  foreground_mask_tolerance: 60
  min_pt:
    - 0.205
    - -0.3
    - 0.01

  max_pt:
    - 0.65
    - 0.3
    - 0.15

  selection_policy: min
  focus: 0

  min_contour_area: 250.0
  max_contour_area: 1000000.0
  min_box_area: 250.0
  max_box_area: 1000000.0
  box_padding_px: 15

  rescale_factor: 1.0
  interpolation: bilinear
  depth_grad_thresh: 10.0
  contour_dist_thresh: 2.5

  point_cloud_mask_only: 1

  image_width: 640
  image_height: 480

  filter_dim: 1