RVMDE

Official implementation of "RVMDE : Radar Validated Monocular Depth Estimation for Robotics", https://arxiv.org/abs/2109.05265v1.

🔧 Dependencies and Installation

• Python >= 3.7 (Recommend to use Anaconda or Miniconda)
• PyTorch >= 1.9

Installation

1. Clone repo

   git clone https://github.com/MI-Hussain/RVMDE

2. Install dependent packages

pypardiso
tensorboardX
nuscenes-devkit

Dataset

Download nuScenes dataset (Full dataset (v1.0)) into data/nuscenes/

Directories

rvmde/
    data/                           							 
        nuscenes/                 		    
                annotations/
                maps/
                samples/
                sweeps/
                v1.0-trainval/
    dataloader/
    list/
    result/
    model/                   				   	        
                   	     				

Dataset Prepration use the externel repos

Please follow external repos (https://github.com/lochenchou/DORN_radar) for Height Extension and (https://github.com/longyunf/rc-pda) for RVMDE with MER's to generte the dataset for training and evaluation.

Evaluation for RVMDE on nuScenes

Download pre-trained weights

Modifying dataset path in valid_loader.py, evalutation list path in data_loader.py, pretrained_weights path in Evalutation_rvmde.py file to evalute.

For evaluation on interms of day,night,rain change the list path first. The evaluation lists are saved in .\list directory.

Evaluate_rvmde.ipynb     #Test

#RVMDE with MER's Evalution

Will be updated soon!!!

Citation

@Article{hussain2021rvmde,
    title={RVMDE : Radar Validated Monocular Depth Estimation for Robotics},
    author={Muhammad Ishfaq Hussain, Muhammad Aasim Rafique and Moongu Jeon},
    journal={arXiv:2109.05265v1},
    year={2021}
}