Hello, I am a beginner. When I run python experiments/place_recogination/online_relocalization.py -c config/experiment_tracking.yaml -g 1 -s results/ -d /media/jixingwu/datasetj/KITTI/Odom/data_odometry_color/sequences -m models/, points_model.pth file is needed. So how can I get it? Thank you!

Hi, I want to run object tracking on KITTI tracking datasets with only CPU using the following terminal prompt:

  python experiments/object_tracking/object_tracking.py -c config/experiment_tracking.yaml -g 1 -s ./results -d /data/datasets/SLAM_dataset/training/ -m ./weights

with configuration in object_tracking.py updated with

configs['use_gpu'] = 0

However, when running with the configuration above with gcn_model.pth, maskrcnn_model.pth, points_model.pth model files in release v2.0.0, the following error occurs:

(aircode) [email protected]:~/workspace/AirCode$ python experiments/object_tracking/object_tracking.py -c config/experiment_tracking.yaml -g 1 -s ./results -d /data/datasets/SLAM_dataset/training/ -m ./weights
experiments/object_tracking/object_tracking.py:371: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
  configs = yaml.load(configs)
Traceback (most recent call last):
  File "experiments/object_tracking/object_tracking.py", line 384, in <module>
    main()
  File "experiments/object_tracking/object_tracking.py", line 381, in main
    show_object_tracking(configs)
  File "experiments/object_tracking/object_tracking.py", line 272, in show_object_tracking
    superpoint_model = build_superpoint_model(configs, requires_grad=False)
  File "./model/build_model.py", line 101, in build_superpoint_model
    model.load_state_dict(model_dict)
  File "/home/yutianc/minicondas/envs/aircode/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1052, in load_state_dict
    self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for VggLike:
        Unexpected key(s) in state_dict: "module.pretrained_net.features.0.weight", "module.pretrained_net.features.0.bias", "module.pretrained_net.features.2.weight", "module.pretrained_net.features.2.bias", "module.pretrained_net.features.5.weight", "module.pretrained_net.features.5.bias", "module.pretrained_net.features.7.weight", "module.pretrained_net.features.7.bias", "module.pretrained_net.features.10.weight", "module.pretrained_net.features.10.bias", "module.pretrained_net.features.12.weight", "module.pretrained_net.features.12.bias", "module.pretrained_net.features.14.weight", "module.pretrained_net.features.14.bias", "module.pretrained_net.features.17.weight", "module.pretrained_net.features.17.bias", "module.pretrained_net.features.19.weight", "module.pretrained_net.features.19.bias", "module.pretrained_net.features.21.weight", "module.pretrained_net.features.21.bias", "module.pretrained_net.features.24.weight", "module.pretrained_net.features.24.bias", "module.pretrained_net.features.26.weight", "module.pretrained_net.features.26.bias", "module.pretrained_net.features.28.weight", "module.pretrained_net.features.28.bias", "module.convPa.weight", "module.convPa.bias", "module.bnPa.weight", "module.bnPa.bias", "module.bnPa.running_mean", "module.bnPa.running_var", "module.bnPa.num_batches_tracked", "module.convPb.weight", "module.convPb.bias", "module.bnPb.weight", "module.bnPb.bias", "module.bnPb.running_mean", "module.bnPb.running_var", "module.bnPb.num_batches_tracked", "module.convDa.weight", "module.convDa.bias", "module.bnDa.weight", "module.bnDa.bias", "module.bnDa.running_mean", "module.bnDa.running_var", "module.bnDa.num_batches_tracked", "module.convDb.weight", "module.convDb.bias", "module.bnDb.weight", "module.bnDb.bias", "module.bnDb.running_mean", "module.bnDb.running_var", "module.bnDb.num_batches_tracked".

Running object_tracking.py with CUDA seems to load models successfully. Is there something wrong with the model loading when GPU is disabled?

Hi, I'm trying to use AirCode to do object matching on complete KITTI sequences and I'm reading the code in experiments/show_object_matching.py.

While reading the code, I noticed that the current code is reading RGB image sequence, convert it into grayscale image, and then duplicate the image into 3-channel each with same value (as following):

https://github.com/wang-chen/AirCode/blob/5e23e9f5322d2e4ee119d5326a6b6112cef0e6bd/experiments/show_object_matching/show_object_matching.py#L172-L176

I'm a bit unsure about the reason why this operation is performed here as the original RGB image should contain more information about the object comparing to grayscale image. For instance, it should be easier to distinguish objects with different color but similar shape if the RGB value is preserved.