Unable to use pub_test.py with v1.0-test!

[tianweiy]

Unable to use pub_test.py with v1.0-test!

[tianweiy]

This function is useful to look at to visualize the object in camera view. https://github.com/nutonomy/nuscenes-devkit/blob/274725ae1b3a2d921725016e3f4b383b8b218d3a/python-sdk/nuscenes/nuscenes.py#L903

[YoushaaMurhij]

I can see .pkl and .json in the folder. I zipped .json and submitted to detection task.
for tracking I need the same thing?

Thank you for your response and good luck with your coming work :)

[tianweiy]

Yeah zip the json and submit to the tracking server

[tianweiy]

AssertionError: Error: You are trying to evaluate on the test set but you do not have the annotations!

This is not an error. The test set annotation is not available (need to submit to test server). There is no immediate function to see the visualization result for tracking. To see the detection output, you can comment out the if statement here

CenterPoint/det3d/datasets/nuscenes/nuscenes.py

Line 284 in e14421d

if not testset:

and the devkit will plot some images. Though, the visualization in the devkit is not that good (doesn't really give a sense of your detection quality without gt annotations) so you probably want to use other tools to visualize the detection/tracking in camera view / 3d.

[YoushaaMurhij]

Thanks!

[iamsiddhantsahu]

@tianweiy The predicted bounding boxes co-ordinates are with respect to the lidar frame. Before transforming them to a particular camera, we need to first determine which camera's translation and rotation matrix we should use. The render_annotation() function from the nuScenes devkit takes as input the annotation token token with which the image path is known and the bounding boxes are plotted.

But in our case I was wondering how can we determine to which camera we transform the co-ordinates of the predicted bounding box and plot the bounding boxes after that?

[abhigoku10]

@YoushaaMurhij @iamsiddhantsahu @tianweiy i trying to run a inference code but unable to find a command to run the inference on nuscenes but I found the above mentioned command in which had mentioned about tools/dist_test.py but in configs i am not able to find " nusc_centerpoint_voxelnet_dcn_0075voxel_flip_testset.py" can you please share some insights on this
or can you tell me which command should we use to run inference on nuscenes and waymo dataset
THanks in advance

[tianweiy]

Thanks for the interest. We have some basic updates to the codebase recently. You can replace the original config with

CenterPoint/configs/nusc/voxelnet/nusc_centerpoint_voxelnet_0075voxel_dcn_flip.py

Line 1 in 84fde67

import itertools

The other commands are the same to generate nuScenes results.

For Waymo models, we are not able to share it publicly due to license agreement, you can send me an email to access those models. Please provide the necessay informations mentioned here
https://github.com/tianweiy/CenterPoint/tree/master/configs/waymo

[YoushaaMurhij]

I used tools/dist_test.py to get the predictions.pkl for the validation-set to use them for tracking
python tools/dist_test.py /home/josh94mur/centerpoint/CenterPoint/configs/nusc/pp/nusc_centerpoint_pp_02voxel_two_pfn_10sweep.py --work_dir work_dirs/val --checkpoint working_dir/val/latest.pth --speed_test --testset --gpus 2
Can I use the same script to get the predictions of Test-set? I got an error related to GT KeyError: 'gt_names'
I also want to check mAP. Can I use the resulted .pkl for that? (submit to the server)

[tianweiy]

yeah, to fix the bug, change the config to the following

train_anno = "data/nuScenes/infos_train_10sweeps_withvelo_filter_True.pkl"
val_anno = "data/nuScenes/infos_val_10sweeps_withvelo_filter_True.pkl"
test_anno = "data/nuScenes/infos_test_10sweeps_withvelo_filter_True.pkl"

data = dict(
    samples_per_gpu=4,
    workers_per_gpu=8,
    train=dict(
        type=dataset_type,
        root_path=data_root,
        info_path=train_anno,
        ann_file=train_anno,
        nsweeps=nsweeps,
        class_names=class_names,
        pipeline=train_pipeline,
    ),
    val=dict(
        type=dataset_type,
        root_path=data_root,
        info_path=val_anno,
        test_mode=True,
        ann_file=val_anno,
        nsweeps=nsweeps,
        class_names=class_names,
        pipeline=test_pipeline,
    ),
    test=dict(
        type=dataset_type,
        root_path=data_root,
        info_path=test_anno,
        test_mode=True,
        ann_file=test_anno,
        nsweeps=nsweeps,
        class_names=class_names,
        pipeline=test_pipeline,
        version='v1.0-test'
    ),
)

you need to use the json files and zip it and then submit to the server

[YoushaaMurhij]

Thank you for your fast and clear answer!
The resulted .json file gave me a 0.0 mAP on the server. I used infos_test_10sweeps_withvelo.pkl
I can't figure out what's wrong! Any suggestions?

[tianweiy]

have you first tested the model on val? (dist_test.py without the --testset flag)

[tianweiy]

if val is ok, please send me an email with your generated json file so that I can take a look

[YoushaaMurhij]

The val is OK. I will send you an e-mail!

[YoushaaMurhij]

I tried :
python tools/nusc_tracking/pub_test.py --work_dir working_dir/track --checkpoint working_dir/test/infos_test_10sweeps_withvelo.json --max_age 3 --root data/nuScenes/v1.0-test --version v1.0-test
to get the tracking results on testset but got this error:

    'Error: Requested split {} which is not compatible with NuScenes version {}'.format(eval_split, version)
AssertionError: Error: Requested split val which is not compatible with NuScenes version v1.0-test

@tianweiy Do I need to modify the config for the testset tracking ?

[tianweiy]

I think the file is already generated in the folder. You need to submit to server for evaluation.

[tianweiy]

Otherwise please attach full log. Especially where does this error come from which line of code

[YoushaaMurhij]

Sorry, but submitting the .json to the tracking server is giving a Failed status. The same .json gave normal results on the detection server. What I am doing wrong?

[tianweiy]

is the json file called "tracking_result.json" ?

[tianweiy]

wait that means tracking is not running. Please attach all outputs after you run pub_test.py

[YoushaaMurhij]

I think I found it. the files are there regarding the previous error. Thanks!