Installing needed packages

pip install -U nuscenes-devkit lyft_dataset_sdk numpy pyquaternion tensorflow==2.6.0 waymo-open-dataset-tf-2-6-0 keras==2.6.0 open3d

Using Manual

Import

import dataset_wrapper as dw

Initialisation

NuScenes

dawr = dw.DatasetWrapper(dw.NUSCENES_NAME, "global_path_to_dataset")

In NuScenes case path should be to "nuscenes" folder which contains data same as at right side of screenshot

Level5

dawr = dw.DatasetWrapper(dw.LYFT_NAME, "global_path_to_dataset")

In Level5 case path should be to "lyft" folder which contains data same as at right side of screenshot

A2D2

dawr = dw.DatasetWrapper(dw.A2D2_NAME, "global_path_to_dataset")

In a2d2 case path should be to "a2d2" folder which contains data same as at right side of screenshot

Waymo

dawr = dw.DatasetWrapper(dw.WAYMO_NAME, "global_path_to_dataset")

In Waymo case path should be to "waymo" folder which contains data same as at right side of screenshot ( .tfrecords )

Using

get_item(int,int)

Main method, which returns data of frame

dawr.get_item(scene_number: int, frame_number: int) -> dict('dataset_type': str, 'coordinates': np.array,'transformation_matrix': np.array,'boxes': list, 'labels' : list)

'dataset_type' values:

• 'unrecognized' - unrecognized type
• 'train' — training type
• 'valid' — validation type
• 'test' — testing type

'coordinates': np.array[num][x]

• num — number of point
• dim — dimension, list [x,y,z]

'motion_flow_annotation': np.array[num][dim]

• num — number of point
• If scene doesn't have previous frame (current frame is first) all values of list is None
• If point is out of the box or isn't previous annotation of the box, it's motion flow annotation is None
• Right point annotation is in format [vx, vy, vz]. Velocity of x,y,z coordinate (m/s).
• About Motion Flow annotation

'transformation_matrix' — 4x4 transformation matrix to 3D coordinates

'boxes' — list of dicts [dict('category_id': int, 'size': list,'center': list, 'orientation': real),...]. Returns empty list if frame don't have boxes.

• 'category_id' — id of boxcategory ( check Categories_documentation.md )
• 'size' — [length, width, height], length, width, height of box
• 'center' — coordinates of box center [x,y,z]
• 'orientation' — box yaw angle [-pi, pi)

'labels' — labels[num], list of categories corresponding to num point in coordinates list. Returns empty list if frame don't have label segmentation.

• num — number of point in coordinates array

visualization_sample(item)

Visualize sample points and boxes via open3d

    item = dawr.get_item(1,1)
    dawr.visualization_sample(item)

get_map()

Check documentation in Maps_documentation.md

dawr.get_map()

get_dataset_categories()

Return local dataset categories list with description (different format)

dawr.get_dataset_categories()

get_unificated_categories()

Returns unificated categories dictionary in format {id: 'name',...}

dawr.get_unificated_categories()

get_category_by_id()

Returns unificated category name (string) by id

dawr.get_category_by_id(id: int)