depth_estimation

executable demonstration of TensorFlow implementation for depth estimation using the model proposed in:

HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation Xiaoyang Lyu, Liang Liu, Mengmeng Wang, Xin Kong, Lina Liu, Yong Liu*, Xinxin Chen and Yi Yuan

official implementation repository

Installation

can be installed from PyPI using pip or your package manager of choice:

pip install git+https://github.com/AbdullahMu/depth_estimation

Usage

3.A. HR-Depth with ONNX Runtime in Python

To prepare the downloaded ONNX models, execute the following command:

python onnx_merge.py

the following output should be printed to console upon successful execution

graph1 outputs: ['317a', '852a', '870a', '897a', '836a']
graph2 inputs: ['0b', 'input.1b', 'input.13b', 'input.25b', 'input.37b']
Constructing the io_match list from your input and output

CLI

This Tensorflow implemention is executable as a CLI tool using the depth_estimation command. The trained model is downloaded and saved automatically, then is run using the privided video sample.

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