Refactor Trajectron++ to work as module and expose training command

pyproject.toml

@@ -1,9 +1,17 @@
 [tool.poetry]
 name = "Trajectron-plus-plus"
-version = "0.1.0"
-description = "Predict trajectories for anomaly detection"
+version = "0.1.1"
+description = "This repository contains the code for Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution)."
 authors = ["Ruben van de Ven <git@rubenvandeven.com>"]
 readme = "README.md"
+license = "MIT"
+
+packages = [
+    { include = "trajectron" },
+]
+
+[tool.poetry.scripts]
+trajectron_train = "trajectron.train:main"
 
 [tool.poetry.dependencies]
 python = "^3.9,<3.12"
@@ -28,8 +36,6 @@ matplotlib = "^3.5"
 #scikit-learn = "0.22.1"
 #filterpy = "^1.4.5"
 tqdm = "^4.65.0"
-#ipywidgets = "^8.0.6"
-#deep-sort-realtime = "^1.3.2"
 scipy = "^1.11.3"
 pandas = "^2.1.1"
 orjson = "^3.9.7"
@@ -41,7 +47,7 @@ notebook = "^7.0.4"
 scikit-learn = "^1.3.1"
 seaborn = "^0.13.0"
 setuptools = "^68.2.2"
-tensorboard = "1.14"
+tensorboard = "^2.11"
 tensorboardx = "^2.6.2.2"
 
 

trajectron/argument_parser.py

@@ -4,7 +4,7 @@ parser = argparse.ArgumentParser()
 parser.add_argument("--conf",
                     help="path to json config file for hyperparameters",
                     type=str,
-                    default='../config/config.json')
+                    default='./config/config.json')
 
 parser.add_argument("--debug",
                     help="disable all disk writing processes.",
@@ -97,7 +97,7 @@ parser.add_argument('--no_edge_encoding',
 parser.add_argument("--data_dir",
                     help="what dir to look in for data",
                     type=str,
-                    default='../experiments/processed')
+                    default='./experiments/processed')
 
 parser.add_argument("--train_data_dict",
                     help="what file to load for training data",

trajectron/evaluation/evaluation.py

@@ -3,7 +3,7 @@ from scipy.interpolate import RectBivariateSpline
 from scipy.ndimage import binary_dilation
 from scipy.stats import gaussian_kde
 from trajectron.utils import prediction_output_to_trajectories
-import trajectron.visualization
+import trajectron.visualization as visualization
 from matplotlib import pyplot as plt
 
 

trajectron/train.py

@@ -9,14 +9,14 @@ import random
 import pathlib
 import warnings
 from tqdm import tqdm
-import visualization
-import evaluation
+import trajectron.visualization as visualization
+import trajectron.evaluation as evaluation
 import matplotlib.pyplot as plt
-from argument_parser import args
-from model.trajectron import Trajectron
-from model.model_registrar import ModelRegistrar
-from model.model_utils import cyclical_lr
-from model.dataset import EnvironmentDataset, collate
+from trajectron.argument_parser import args
+from trajectron.model.trajectron import Trajectron
+from trajectron.model.model_registrar import ModelRegistrar
+from trajectron.model.model_utils import cyclical_lr
+from trajectron.model.dataset import EnvironmentDataset, collate
 from tensorboardX import SummaryWriter
 # torch.autograd.set_detect_anomaly(True)