How to test in the overlap region？

[feifei-Liu]

The paper compares FCOS3D and Detr3D in the overlap region. How to test the nuscenes only in the overlap region？Thank you very much！

[a1600012888]

To test in the overlap region, I suggest you modify the code of the official evluation code here: https://github.com/nutonomy/nuscenes-devkit/blob/master/python-sdk/nuscenes/eval/detection/evaluate.py#L98

You should add some code here to filter out boxes.

[a1600012888]

Some sample code to test if a box is repeated in several images.

from nuscenes.eval.detection.data_classes import DetectionBox
from nuscenes.utils.geometry_utils import view_points, box_in_image, BoxVisibility
from pyquaternion import Quaternion
from nuscenes.utils.data_classes import Box
import numpy as np
from copy import deepcopy

def box_center_in_image(box, cam_intrinsic, imsize, vis_level=None):
    center3d = box.center
    center3d = center3d[:, np.newaxis]
    center_img = view_points(center3d, cam_intrinsic, normalize=True)[:2, :]

    visible = np.logical_and(center_img[0, :] > 0, center_img[0, :] < imsize[0])
    visible = np.logical_and(visible, center_img[1, :] < imsize[1])
    visible = np.logical_and(visible, center_img[1, :] > 0)
    visible = np.logical_and(visible, center3d[2, :] > 1)

    in_front = center3d[2, :] > 0.1

    return all(visible) and all(in_front)

def is_box_repeated(nusc, box: DetectionBox):
    cams = ['CAM_FRONT_LEFT', 'CAM_FRONT', 'CAM_FRONT_RIGHT','CAM_BACK_LEFT', 'CAM_BACK', 'CAM_BACK_RIGHT']
    box_vis_level = BoxVisibility.ANY
    sample_token = box.sample_token
    rec = nusc.get('sample', sample_token)

    if isinstance(box, DetectionBox):
        box = Box(box.translation, box.size, Quaternion(box.rotation))

    box_backup = deepcopy(box)

    num_repeat = 0
    for cam_name in cams:
        box = deepcopy(box_backup)
        cam_token = rec['data'][cam_name]
        sample_data_token = cam_token

        sd_record = nusc.get('sample_data', sample_data_token)

        cs_record = nusc.get('calibrated_sensor', sd_record['calibrated_sensor_token'])
        sensor_record = nusc.get('sensor', cs_record['sensor_token'])
        pose_record = nusc.get('ego_pose', sd_record['ego_pose_token'])

        # move box to ego vehicle coord system
        box.translate(-np.array(pose_record['translation']))
        box.rotate(Quaternion(pose_record['rotation']).inverse)

        #  Move box to sensor coord system.
        box.translate(-np.array(cs_record['translation']))
        box.rotate(Quaternion(cs_record['rotation']).inverse)

        cam_intrinsic = np.array(cs_record['camera_intrinsic'])
        imsize = (sd_record['width'], sd_record['height'])

        #if box_in_image(box, cam_intrinsic, imsize, vis_level=box_vis_level):
        if box_center_in_image(box, cam_intrinsic, imsize, vis_level=box_vis_level):
            num_repeat += 1

    #assert num_repeat > 0, 'box never occur on any images!'

    if num_repeat > 1:
        return True
    return False

[quanh1990]

seems similar to function filter_eval_boxes_by_overlap in script projects/mmdet3d_plugin/datasets/nuscnes_eval.py