# monodepth-cpp

**Repository Path**: aszkj/monodepth-cpp

## Basic Information

- **Project Name**: monodepth-cpp
- **Description**: Tensorflow C++ implementation for single-image depth estimation (Monodepth)
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2022-04-16
- **Last Updated**: 2022-04-16

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# monodepth-cpp
Tensorflow C++ implementation for single image depth estimation
<p align="center">
 <img src="https://github.com/yan99033/monodepth-cpp/blob/master/preview/monodepth_preview.gif" width="612" height="370">
</p>

The original work is implemented in Python, [click here](https://github.com/mrharicot/monodepth) to go to their repo. Please cite their work if your find it helpful.

It is using pointer-to-implementation technique, so that you can use it in your project without worrying the actual implementation. Refer to [src/inference_monodepth.cpp](https://github.com/yan99033/monodepth-cpp/tree/master/src/inference_monodepth.cpp) for more information

The C++ version is about 28fps, in comparison with Python's 13fps, tested with i7 processor and NVidia 1070 graphics laptop

## Personal projects that use monodepth-cpp
1. [CNN-SVO](https://github.com/yan99033/CNN-SVO)
<p align="center">
 <img src="https://github.com/yan99033/monodepth-cpp/blob/master/preview/kitti_preview.gif" width="723" height="224">
 <img src="https://github.com/yan99033/monodepth-cpp/blob/master/preview/robotcar_preview.gif" width="723" height="224">
</p>

2. Reproducing [Deep virtual stereo odometry](https://vision.in.tum.de/research/vslam/dvso)

<p align="center">
 <img src="https://github.com/yan99033/monodepth-cpp/blob/master/preview/dvso_kitti_preview.gif" width="723" height="281">
 <img src="https://github.com/yan99033/monodepth-cpp/blob/master/preview/dvso_final_map.gif" width="723" height="334">
</p>

**NOTE:** Because DVSO uses both the left disparity and the right disparity outputs (for left-right consistency check), it requires some modifications in the source code to enable the disparities outputs.



## Requirements
1. You are required to build Tensorflow library from source, [see here](https://github.com/yan99033/monodepth-cpp/tree/master/Tensorflow_build_instructions)
2. [Freeze the Tensorflow graph](https://github.com/yan99033/monodepth-cpp/tree/master/freeze_graph) (with known input and output names)


## Configure CMake project
* Make sure you have the compatible versions of Eigen, Protobuf, and Tensorflow (Mine: Eigen 3.3.4; Protobuf 2.6.1-1.3; Tensorflow 1.6)
* You will also notice some hard-coded paths to include directories and libraries, modify them accordingly
  * CMakeLists.txt (local built Eigen library)
  * CMakeModules.cmake (path to '.so' file and 'include' directories; make sure your program source the library and header files)


## Build (static/shared) library

```
mkdir build && mkdir install
cd build
cmake -DCMAKE_INSTALL_PREFIX=/path/to/monodepth-cpp/install ..
make && make install
```

You will be seeing 'include' and 'lib' folders in the 'install' folder, import them in your project

To test if Monodepth C++ is working properly,
```
cd build
./inference_monodepth
```

**NOTE:** Select either static or shared library in CMakeLists.txt, unless you want both of them

## Use (static/shared) library
In your own CMakeLists.txt project, do the following:

```
set(monodepth_INCLUDE_DIRS /path/to/monodepth-cpp/install/include)
INCLUDE_DIRECTORIES(
  ...
  monodepth_INCLUDE_DIRS
  ...
)

TARGET_LINK_LIBRARIES(awesome_exe /path/to/tensorflow/library/libtensorflow_all.so) # Only if you are using the provided instructions
TARGET_LINK_LIBRARIES(awesome_exe /path/to/monodepth-cpp/install/lib/libmonodepth_static.a) # if you are using static library

```