MDE

Version 1.0.0 (18.9 MB) by Brian Park
Monocular Depth Estimation for indoor environment with MATLAB
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Updated 28 Jul 2023
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Monocular-Depth-Estimation

View MDE(Monocular Depth Estimation) on File Exchange

Monocular Depth Estimation for indoor environment with MATLAB

This repository contains the MATLAB project which computes depth map from a single image and transforms into point cloud.

Installation

Download ZIP file and run main script

    run('main.mlx');

Run training script only for training network

    run('train_net.mlx');

Dataset not included. Download NYU v2 dataset

Dependencies

MATLAB

  • Deep Learning Toolbox
  • Computer Vision Toolbox

Simulink

  • Robotics System Toolbox
  • Automated Driving Toolbox
  • PackageGazeboPlugin (from Gazebo Simulation Environment Requirements and Limitations )

Device

  • Ubuntu® Ubuntu 20.04.3 LTS (Focal Fossa)
  • CMake 3.16.3, Gazebo 11, and the Gazebo plugin

Usage

  1. Load downloaded dataset and Check
  2. Design the network using DeepNetworkDesigner
  3. Train the network using training option in DeepNetwrokDesigner, and then Save the trained network in the directory.
  4. Load the trained network and test in MATLAB
  5. Load the network in Simulink and Connect the simulation with Gazebo

Cite As

Brian Park (2024). MDE (https://github.com/robot-park/Monocular-Depth-Estimation/releases/tag/v1.0.0), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2023b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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dataset

function/postprocess

function/preprocess

function/training

function/visualize

_simulation

model/net_MDE

Version Published Release Notes
1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.