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

Baseline implementation: https://github.com/vvanirudh/social-lstm-pytorch
Paper: http://cvgl.stanford.edu/papers/CVPR16_Social_LSTM.pdf
Made improvements: Please see attached presentation

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

Fork the repository
Start train a model >>> python train/olstm_train/vlstm.train.py - -[Parameter set]
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
Enjoy!

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