Tools¶
visualize_gqcnn_dataset.py¶
Visualizes point clouds from a generated GQ-CNN training dataset, optionally filtering by the grasp robustness metrics.
Author¶
Jeff Mahler
-
visualize_gqcnn_dataset.
visualize_tensor_dataset
(dataset, config)¶ Visualizes a Tensor dataset.
Parameters: - dataset (
TensorDataset
) – dataset to visualize - config (
autolab_core.YamlConfig
) – parameters for visualization
Notes
Required parameters of config are specified in Other Parameters
Other Parameters: - field_name (str) – name of the field in the TensorDataset to visualize (defaults to depth_ims_tf_table, which is a single view point cloud of the object on a table)
- field_type (str) – type of image that the field name correspondes to (defaults to depth, can also be segmask if using the field object_masks)
- print_fields (
list
of str) – names of additiona fields to print to the command line - filter (
dict
mapping str todict
) – contraints that all displayed datapoints must satisfy (supports any univariate field name as a key and numeric thresholds) - gripper_width_px (float) – width of the gripper to plot in pixels
- font_size (int) – size of font on the rendered images
- dataset (