SimpleDepthEstimation - An unified codebase for NN-based monocular depth estimation methods

Overview

SimpleDepthEstimation

Introduction

This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (with a lot of modifications) and supports both supervised and self-supervised monocular depth estimation methods. The main goal for developing this repository is to help understand popular depth estimation papers, I tried my best to keep the code simple.

Environment:

  1. clone this repo
    SDE_ROOT=/path/to/SimpleDepthEstimation
    git clone https://github.com/zzzxxxttt/SimpleDepthEstimation $SDE_ROOT
    cd $SDE_ROOT
  2. create a new conda environment and activate it
    conda create -n sde python=3.6 
    conda activate sde
  3. install torch==1.8.0 and torchvision==0.9.0 follow the official instructions. (I haven't tried other pytorch versions)
  4. install other requirements
    pip install -r requirements.txt

Data preparation

KITTI:

Download and extract KITTI raw dataset, refined KITTI depth groundtruth, and eigen split files, then modify the data path in the config file.

Training

python path/to/project/train.py --num-gpus 2 --cfg path/to/config RUN_NAME run_name

Evaluation

python path/to/project/train.py --num-gpus 2 --cfg path/to/config --eval MODEL.WEIGHTS /path/to/checkpoint_file

Results:

KITTI:

model type config abs rel err sq rel err rms log rms d1 d2 d3
ResNet-18 supervised link 0.076 0.306 3.066 0.116 0.936 0.990 0.998
BTSNet (ResNet-50) supervised link 0.062 0.259 2.859 0.100 0.950 0.992 0.998
MonoDepth2 (ResNet-18) self-supervised link 0.118 0.735 4.517 0.163 0.860 0.974 0.994

Demo:

python tools/demo.py --cfg path/to/config --input path/to/image --output path/to/output_dir MODEL.WEIGHTS /path/to/checkpoint_file

Demo results:

Todo

  • add PackNet (I have added it, performance need verification)
  • add Dynamic Motion Learning (I have implemented it but still buggy, help welcome!)
  • support more datasets

Reference

Owner
Ph.D. student at University of Science and Technology of China.
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