Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/snototter/vitocpp
C++/Python 3 utilities for common vision tasks, e.g. streaming, visualization or image manipulation.
https://github.com/snototter/vitocpp
computer-vision-tools data-visualization image-processing utility-library
Last synced: 2 days ago
JSON representation
C++/Python 3 utilities for common vision tasks, e.g. streaming, visualization or image manipulation.
- Host: GitHub
- URL: https://github.com/snototter/vitocpp
- Owner: snototter
- License: gpl-3.0
- Created: 2020-01-12T10:26:09.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2024-03-21T16:46:00.000Z (8 months ago)
- Last Synced: 2024-03-21T17:55:10.078Z (8 months ago)
- Topics: computer-vision-tools, data-visualization, image-processing, utility-library
- Language: C++
- Homepage:
- Size: 9.28 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# vitocpp/vcp
C++/Python 3 utilities for common vision tasks, _e.g._ streaming, visualization or image manipulation.
Note: As of 01/2020 this repository is WIP, I'm rewriting my utilities (especially simplifying the streaming module) over the next couple of months.
```
Current status (12/2020):
cloc --exclude-dir=.venv3,build,cmake,third-party,gen,doc,generated --exclude-lang=make,XML .
-------------------------------------------------------------------------------
Language files blank comment code
-------------------------------------------------------------------------------
C++ 64 4305 2306 23566
C/C++ Header 56 1600 1827 4435
Python 25 841 1030 3172
CMake 12 270 248 1179
Markdown 3 97 0 389
Bourne Shell 3 41 77 251
-------------------------------------------------------------------------------
SUM: 163 7154 5488 32992
-------------------------------------------------------------------------------
```
## What is it good for?
Some of `vcp`'s highlights:
* Best effort multiple device streaming with the `vcp::best` module. Useful for quick camera tests and whenever (guaranteed) synchronisation isn't crucial. The goal of this module is to stream from multiple devices simultaneously, without having the ROS overhead. A simple libconfig++-style configuration file allows you to process all streams both in C++ and python. For more details, see the [separate BESt.md documentation](BESt.md).
* Background subtraction is provided by the `vcp::bgm` module, for example:
* Visualization utilities are provided by the `vcp::imvis` module, for example:
* Pseudocoloring for data visualization/analysis is also provided by the `vcp::imvis` module.
Back when I started working on this library, OpenCV didn't provide pseudocoloring capabilities. The `vcp::imvis` module allows visualization via common color maps (you might remember these from such frameworks as MATLAB, matplotlib, and whatnot).
* Math utilities - besides enabling most of the fancy visualizations within `vcp::imvis`, you can also do basic geometry tasks with the `vcp::math` module (_e.g._ computing tangents of circles, line (segment) intersection, and quite a lot more).
* C++ utilities - for basic file/path and string manipulation, sorting, and more (if you want to avoid heavier dependencies, such as Boost).
## Repository Contents
* `./build-scripts` - shell scripts to prepare the build system, build the libraries, etc.
* `./cmake` - CMake utilities (incl. custom `Find.cmake` scripts).
* `./examples` - example usage of these utilities.
* `./src` - source code for all C++ modules and python bindings.
* `./third-party` - third party dependencies (which are not part of default system packages).
## Installation
* If you want to build the C++ library and Python3 bindings, simply run `./build-scripts/build-ubuntu-18.04.sh`, this will:
* Check and ask you to install missing system packages.
* Configure the build (depending on which optional packages you installed, _e.g._ `libk4a` to stream from Azure Kinect).
* Build the C++ `vcp` libraries and corresponding Python3 bindings.
* Build the example applications and prepare the virtual environment for Python demos.
* If you prefer to do it on your own, crank up CMake:
```bash
$ cd
$ mkdir build && cd build
$ cmake -DVCP_BUILD_PYTHON=ON ..
$ make -j install
```
* The default install location (for `make install`) of `vcp` is `/gen`.
* Public C++ headers are inside `/gen/include`.
* `vcp` library files are inside `/gen/lib`.
* The Python3 package is located at `/gen/vcp`.
## Tools
This repository comes with a few "tools", _i.e._ standalone applications that go beyond simple demos/examples.
Currently (as of Jan/2020), there are only python applications available, which you can find at `/examples/python3/tools`.
* Set up the virtual environment. If you didn't use the `./build-scripts/build-X.sh` script to prepare the library, you should run:
```bash
$ cd /examples/python3
$ ./prepare_environment_py3.sh
$ source .venv3/bin/activate
$ cd tools
```
* Extrinsic multi-camera calibration. For partially overlapping multi-camera setups, you can use the `calibrate-extrinsics.py` UI to estimate the camera poses using [AprilTags](https://april.eecs.umich.edu/software/apriltag).
For example, calibrating two Azure Kinects via `python tools/calibrate-extrinsics.py ../data/data-best/kinects.cfg 225 --max-depth 10000 --max-ir 255` looks like this (depth measurements are visualized as surface normals, reflectivity of the infrared stream is shown as heatmap, TODO explain (?)):
* 3D image plots. Plot a single image (`plot-image.py`) or an image sequence (`plot-image-sequence.py`) by interactively adjusting the camera extrinsics.
* Image abstraction: cartoonification, pixelation, etc. can be experimented with via `cartoonify.py`.
## Examples
Besides the more complex `tools`, there are also simple demos showcasing the library capabilities.
### C++
* The C++ applications at `/examples/cpp` demonstrate how you can use `vcp` from your own CMake projects. After building the vcp library, building these examples is as easy as:
```bash
$ cd /examples
$ mkdir build && cd build
$ cmake ..
$ make -j
```
* Highly recommended examples (best/well documented, useful functionality):
* `best_demo`
### Python
* You can find Python3 examples for all modules at `/examples/python3`.
```bash
$ cd /examples/python3
# Set up the virtual environment
$ ./prepare_environment_py3.sh
$ source .venv3/bin/activate
$ python imvis_demo.py
```
* Highly recommended examples (best/well documented, useful functionality):
* `bgm_demo.py` - Usage example of the background subtraction module.
* `geometry_demoy.py` - Usage example of the `math2d` and `math3d` modules.
* `imutils_demo.py` - Usage example of the `imutils` (image manipulation) module.
* `imvis_demo.py` - Usage example for visualization utilities within the `imvis` module.
## Tests
While all of vcp has been tested "in-the-wild", unit tests are rather sparse, unfortunately.
Especially for the "best effort streaming" module, tests become quite difficult to automate (threading + the need for the specific hardware connected to the test server).
### C++
* Testing the C++ core library requires `gtest`:
```bash
$ sudo apt-get install libgtest-dev
# This package does not provide binaries, so look for the installed
# source at /usr/src. It should be (Ubuntu 18.04) at /usr/src/googletest.
$ cd /usr/src/googletest
$ sudo cmake CMakeLists.txt
$ sudo make
# Copy or symlink googlemock/gtest/libgtest.a
# and googlemock/gtest/libgtest_main.a to your /usr/lib folder
$ sudo cp googlemock/gtest/*.a /usr/lib
```
* Now `vcp` can be tested:
```bash
$ cd /build
# Enable tests and link the gtest libraries
$ cmake -DVCP_BUILD_TESTS=ON ..
$ make test
# Or, if you prefer:
$ ctest -V
```
### Python
* You can find the Python3 tests at `/examples/python3`, _i.e._ all files following the pattern `test_*.py`.
* Testing requires `pytest`:
```bash
$ cd /examples/python3
$ source .venv3/bin/activate
$ pip install pytest
$ pytest
```
## TODOs
* [ ] Additional tools/examples
* [ ] C++ Viewer (resize streams and use liveview)
* [ ] Qt Viewer
* [ ] Capturing tool
* [ ] Camera calibration (nice-to-have)
* [ ] Intrinsic calibration
* [x] Extrinsic calibration