GETTING_STARTED.md

Getting Started with CLOUDS

This document provides a brief intro of the usage of CLOUDS.

Please see Getting Started with Detectron2 for full usage.

Training & Evaluation in Command Line

We provide a script train_net.py, that is made to train all the configs provided in CLOUDS.

To train a model with "train_net.py", first setup the corresponding datasets following datasets/README.md.

Below is an example of how to train CLOUDS on GTA5 :

Warmup on GTA5 (using ConvNext-L)

python train_net.py --num-gpus 2 \
--config-file configs/warmup/gta/train_gta.yaml OUTPUT_DIR /path/to/output_directory

Joint Training on GTA5 and generated dataset (using ConvNext-L)

python train_net.py --num-gpus 2 \
--config-file configs/joint_training/gta/train_jt_gta.yaml OUTPUT_DIR /path/to/output_directory

You can do the same thing for SYNTHIA and Cityscapes using ConvNext-L, ResNet-50 and ResNet-101.

Evaluation of the model's performance

python train_net.py --eval-only --config-file /path/to/config_file \
MODEL.WEIGHTS /path/to/checkpoint_file

For more options, see python train_net.py -h.