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quancore
219 Stars 172 Forks 23 Commits 16 Opened issues

Description

Social LSTM implementation in PyTorch

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Social LSTM implementation in PyTorch

Project details

Semester project of Master of Computer Science in EPFL
Student name : Baran Nama
Advisor: Alexandre Alahi
Presentation : https://drive.google.com/file/d/1biC23s1tbsyDETKKBW8PFXWYyyhNEAuI/view?usp=sharing

Implementation details

Baseline implementation: https://github.com/vvanirudh/social-lstm-pytorch
Paper: http://cvgl.stanford.edu/papers/CVPR16SocialLSTM.pdf
Detailed info about challange and datasets: https://www.aicrowd.com/challenges/trajnet-a-trajectory-forecasting-challenge Made improvements: Please see attached presentation

Documentation

  • generator.py : Python script for generating artifical datasets
  • helper.py: Python script includes various helper methods
  • hyperparameter.py: Pyton script for random best parameter selection for a model
  • make_directories.sh: Bash script for creation of file structure
  • model.py: Python file includes Social LSTM model definition
  • olstm_model.py: Python file includes Occupancy LSTM model definition
  • olstm_train.py: Python script for training Occupancy LSTM model
  • test.py: Python script for model testing and getting output txt file for submission
  • train.py: Python script for training Social LSTM model
  • utils.py: Python script for handling input train/test/validation data and batching it
  • validation.py: Python script for externally evaluate a trained model by getting validation error
  • visualize.py: Python script for visualizing predicted trajectories during train/test/validation sessions
  • vlstm_model.py: Python file includes Vanilla LSTM model definition
  • vlstm_train: Python script for training Vanilla LSTM model

How to deploy

  1. Fork the repository
  2. Start train a model >>> python train/olstm_train/vlstm.train.py - -[Parameter set]
  3. If necesarry file structure is not exist (which is the initial situation), train script will run make_directories.sh and this command will automatically create file structure
  4. Enjoy!

Results

| Model name | Avarage error | Final error | Mean error | | :---: | :---: | :---: | :---: | | Social LSTM | 1.3865 | 2.098 | 0.675 | | Occupancy LSTM | 2.1105 | 3.12 | 1.101 | | Vanilla LSTM | 2.107 | 3.114 | 1.1 |

Reference: http://trajnet.stanford.edu/result.php?cid=1

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