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)

ezvezdov/Dataset-Wrapper