$ conda env create -f environment.yml
$ source activate depthmaps
$ python3 run.py --help
usage: run.py [-h] [--dataset DATASET] [--model MODEL]
[--checkpoint_dir CHECKPOINT_DIR] [--epochs EPOCHS]
[--workers WORKERS] [--cleanup_on_exit]
[--test_split TEST_SPLIT] [--use_custom_test_split]
optional arguments:
-h, --help show this help message and exit
--dataset DATASET Dataset to use. Defaults to Make3D. One of: [Make3D,
Make3D2, Nyu, Merged, Inference]
--model MODEL Model to use. Defaults to Pix2Pix. One of: [Simple,
MultiScale, Pix2Pix, Generator]
--checkpoint_dir CHECKPOINT_DIR
Directory containing a checkpoint to load, has to fit
the model.
--epochs EPOCHS Number of epochs to train for. Defaults to 0 which is
needed when only running inference using a pretrained
model.
--workers WORKERS Number of threads to use. Defaults to the count of
available cores.
--cleanup_on_exit Remove temporary files on exit.
--test_split TEST_SPLIT
Percentage of samples to use for evaluation during
training. Defaults to 10. Only relevant if
use_predefined_split is set to False or when there is
no such predefined split available.
--use_custom_test_split
Whether to not use the dataset's predefined train/test
split even if one is available. Defaults to False.Pretrained models are provided upon request.
To use pretrained models, move a model's files to a designated directory and specify that directory using the --checkpoint_dir argument above. Note that models are trained on specific datasets and will not perform well when applied to others, so set the --model and --dataset argument as fitting for the pretrained model defined.
A model consists of at least a checkpoint file, three model.ckpt-* files (data, index and meta) and a test_files.txt. The test_files.txt file is optional and makes sure that when loading a model it uses the same dataset train/test split as during training -- to ignore that functionality simply delete this file.