How to run

pip install the requirements.txt file

pip install -r requirements.txt

Download the labeled dataset from this page: https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html

and put it in data/nyu_depth_v2_labeled.mat

Clone this repository: https://github.com/AndrewAtanov/simclr-pytorch

add an init.py file in the main directory of that repository

In simclr-pytorch/models/resnet.py modify the code at line 49 to:

if not self.hparams.return_feature_map:
    x = self.avgpool(x)
    x = torch.flatten(x, 1)

Download their pretrained models and make sure there is a .pth file at pretrained_models/resnet50_imagenet_bs2k_epochs600.pth.tar

In simclr-pytorch/models/ssl.py make the following adjustments

# add to line 297
parser.add_argument('--return_feature_map', default=False, type=bool, help='If the 7x7x2048 feature map is returned from the encoder')

# add to line 310
ckpt['hparams'].return_feature_map = hparams.return_feature_map

You may also have to git clone this repository https://github.com/GabrielMajeri/nyuv2-python-toolbox , but I'm not sure if I ever use it. If it complains you can probably comment out the imports.

How to train

Run the training_commands.sh file - This requires like 10GB of VRAM Reduce the batch size if that is inaccessible and you just want to see it run.

How to test

Run the notebooks in src/testing