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One single model for all classes

See original GitHub issue

Hi, I want to train a single model for all classes (cars/pedestrians/cyclists or maybe trucks and vans). I changed the config file but when I run the code it says it cannot find some files: FileNotFoundError: /home/isaac/python/avod/avod/data/mini_batches/iou_2d/kitti/train/lidar/All[ 0.5 0.5 0.5]/000580.npy not found for sample 000580 in /home/isaac/python/avod/avod/data/mini_batches/iou_2d/kitti/train/lidar, run the preprocessing script first

I check the folder and found some folders such as cars[0.5], people[0.5, 0.5], but no all[0.5, 0.5, 0.5]. So I have two question:

  • Did you train a single network for all classes and the performance was bad and just don’t want to release it? Cuz you mentioned different configs for your different networks for cars and people. I think because of different sizes cause these different configs.
  • If I want to train a single network, which files do I need to modify.

I think training one single network with a single config and pre-defined 3d anchors can cause lower accuracy and higher inference time. Correct me if I’m wrong, please.

Do you suggest to do this or not.

Thank you.

Issue Analytics

  • State:closed
  • Created 5 years ago
  • Comments:6

github_iconTop GitHub Comments

Fredrik00commented, Mar 4, 2019

You need to create a preprocessing config, such as those in mb_preprocessing that includes the classes Car Pedestrian and Cyclist. After that you need to set up preprocessing in to process All using the config you set up. If you want more classes you will at least also have to modify as it is hardcoded to name joint detection of Pedestrian and Cyclist as ‘People’ and Pedestrian, Cyclist and Car as ‘All’, but I haven’t tested expanding this yet.

I have forked the repo and done some work of my own, you can see examples of the two first files I mentioned at and

Keep in mind that results on pedestrians and cyclists will not be very good out of the box, likely due to the poor balancing of the classes in the dataset.

Jiachenyin1commented, Dec 16, 2021


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