<div align="center">
<img src="https://raw.githubusercontent.com/oruscam/RIVeR/main/river/docs/_static/river_logo.svg" width="350px">
<br />
<br />
<p>
<strong>Modern LSPIV toolkit for water-surface velocity analysis and flow discharge measurements</strong>
</div>
[]()
[](https://www.gnu.org/licenses/agpl-3.0)
[](https://www.python.org/downloads/)
[](https://reactjs.org/)
[](https://pypi.org/project/river-cli/)
[](https://doi.org/10.1016/j.cageo.2017.07.009)
---
# RIVeR: Rectification of Image Velocity Results
**RIVeR** (Rectification of Image Velocity Results) is a modern, open-source toolkit for Large Scale Particle Image Velocimetry (**LSPIV**) distributed by [ORUS](https://orus.cam). Built with **Python** and **React**, it provides a user-friendly interface for water-surface velocity analysis and flow discharge measurements in rivers and large-scale hydraulic models.
<figure>
<img src="https://raw.githubusercontent.com/oruscam/RIVeR/main/river/docs/_static/screenshot_results.png" width=500>
<p ><i>Example of RIVeR velocimetry analysis of river flow</i></p>
</figure>
---
## 💧 Overview
RIVeR is a specialized tool for applying Large Scale Particle Image Velocimetry (LSPIV) techniques as a non-contact method to estimate discharge in rivers and channels from video footage. The software guides the process through intuitive defaults and pre-configured settings, enabling users to generate discharge calculations without extensive prior knowledge of the technique. The workflow guides users through a series of straightforward steps culminating in comprehensive visual reports.
Originally developed in MATLAB in 2015 and well-received by the hydrology community, RIVeR has now been reimplemented in Python and JavaScript to improve accessibility, performance, and cross-platform compatibility.
<figure>
<img src="https://raw.githubusercontent.com/oruscam/RIVeR/main/river/docs/_static/oblique_rectification.gif" width=500>
<p><i>Demonstration of interactive oblique image rectification process in RIVeR</i></p>
</figure>
---
## 📖 User Manual
For a detailed step-by-step guide on using RIVeR's GUI (Graphical User Interface),
please refer to the **[User Manual](user-manual.md)**.
---
## ✨ Key Features
* Process footage from multiple sources:
* UAV/drone aerial imagery
* Oblique view camera (from riverbank)
* Fixed station cameras (contiunous monitoring)
* Frame extraction from videos with customizable parameters
* FFT-based PIV analysis with multi-pass support for increased accuracy
* Interactive result visualization with customizable vector fields
* Georeferencing and coordinate transformations
* Multi Cross-sectional flow analysis
* Automated beautiful report generation ([like this one !](https://oruscam.github.io/RIVeR/sample_report.html))
* Multi-platform support (**Windows**, **macOS**, **Linux**)
---
## 🌍 Multi-Language Support
- RIVeR available in multiple languages!
- English 🇺🇸
- Spanish 🇦🇷
- French 🇫🇷
- Italian 🇮🇹
- Portuguese 🇧🇷
- German 🇩🇪
- [More coming soon!]
---
## 📥 Download Compiled Releases
If you don't want to bother with code at all (we get it, sometimes you just want things to work!), pre-compiled standalone versions are available:
| ⊞ Windows | ⌘ macOS | ◆ Linux |
|:---:|:---:|:---:|
| [EXE](https://github.com/oruscam/RIVeR/releases/download/v3.2.0/RIVeR-Windows-3.2.0-Setup.exe) | [DMG](https://github.com/oruscam/RIVeR/releases/download/v3.2.0/RIVeR-Mac-3.2.0-Installer.dmg) | [DEB](https://github.com/oruscam/RIVeR/releases/download/v3.2.0/RIVeR-Linux-3.2.0.deb) [RPM](https://github.com/oruscam/RIVeR/releases/download/v3.2.0/RIVeR-Linux-3.2.0.rpm) |
These packages include both the GUI and CLI tools in a ready-to-use application. No Python or JavaScript knowledge required!
These packages include both the GUI and CLI tools in a ready-to-use application. Simply download, extract (if needed), and run the application - no Python or JavaScript knowledge required!
---
## 🧑💻 Developer Installation & Usage
For those who prefer to work with the source code or contribute to RIVeR's development, here's how to get started:
### Prerequisites
- Python 3.12+
- pip package manager
- Git (for cloning the repository)
### Development Installation
```bash
git clone https://github.com/oruscam/RIVeR.git
cd RIVeR
pip install -e .
```
### CLI Installation
RIVeR CLI provides a comprehensive set of commands for performing LSPIV analysis through the command line.
```bash
pip install river-cli
```
#### Basic Usage
```bash
river-cli [OPTIONS] COMMAND [ARGS]...
```
To see all available commands and options:
```bash
river-cli --help
```
#### Example Workflow
```bash
# 1. Extract frames from video
river-cli video-to-frames river_video.mp4 ./frames --every 2
# 2. Generate transformation matrix
river-cli get-uav-transformation-matrix 100 200 300 400 0 0 10 10 --image-path ./frames/frame_001.jpg
# 3. Create masks for PIV analysis
river-cli create-mask-and-bbox 3 ./frames/frame_001.jpg ./xsections.json ./transformation_matrix.json --save-png-mask
# 4. Run PIV analysis
river-cli piv-analyze ./frames --mask ./mask.json --workdir ./results
# 5. Calculate discharge
river-cli update-xsection ./xsections.json ./results/piv_results.json ./transformation_matrix.json --step 2 --fps 30 --id-section 0
```
### Graphical User Interface (GUI)
RIVeR also provides a user-friendly graphical interface built with React. The GUI offers an intuitive way to perform LSPIV analysis without using command-line tools.
Key GUI features include:
- Interactive workflow interface
- Visual cross-section creation
- Real-time PIV analysis visualization
- Result export capabilities
For detailed information about installation, usage, and features of the GUI, please see the dedicated [GUI documentation](gui/README.md).
---
## 📂 Project Structure
```
river/
.
├── LICENSE
├── examples # Jupyter examples
│ ├── 00_introduction.ipynb
│ ├── 01_video_to_frames.ipynb
│ ├── 02a_nadir_transformation.ipynb
│ ├── 02b_oblique_transformation.ipynb
│ ├── 02c_fixed_station_transformation.ipynb
│ ├── 03_cross_sections.ipynb
│ ├── 04_piv_analysis.ipynb
│ ├── 05_discharge_calculation.ipynb
│ ├── data
│ ├── results
│ └── utils
├── gui
├── pyproject.toml
├── readme.md
├── requirements.txt
└── river
├── cli
├── core
│ ├── compute_section.py # Section computation utilities
│ ├── coordinate_transform.py # Coordinate system transformations
│ ├── define_roi_masks.py # ROI and mask definitions
│ ├── exceptions.py # Custom exceptions
│ ├── image_preprocessing.py # Image preparation tools
│ ├── matlab_smoothn.py # Smoothing algorithms
│ ├── piv_fftmulti.py # FFT-based PIV processing
│ ├── piv_loop.py # PIV processing loop
│ ├── piv_pipeline.py # Main PIV pipeline
│ └── video_to_frames.py # Video frame extraction
└── docs
```
---
## 📚 Jupyter Examples
Browse through our collection of Jupyter Notebook examples to learn how to use RIVeR for various analyses (requires development installation):
- [Introduction to RIVeR](examples/00_introduction.ipynb)
- [Video Frame Extraction](examples/01_video_to_frames.ipynb)
- [UAV/Drone Transformations](examples/02a_nadir_transformation.ipynb)
- [Oblique View Transformations](examples/02b_oblique_transformation.ipynb)
- [Fixed Station Transformations](examples/02c_fixed_station_transformation.ipynb)
- [Cross Section Analysis](examples/03_cross_sections.ipynb)
- [PIV Analysis Workflow](examples/04_piv_analysis.ipynb)
- [Discharge Calculation](examples/05_discharge_calculation.ipynb)
These interactive examples provide step-by-step guidance for common RIVeR workflows. To run them, make sure you've completed the development installation described above.
## 🔬 Citation
If you use RIVeR in your research, please cite:
```bibtex
@article{patalano2017river,
title={Rectification of Image Velocity Results (RIVeR): A simple and user-friendly toolbox
for large scale water surface Particle Image Velocimetry (PIV) and
Particle Tracking Velocimetry (PTV)},
author={Patalano, Antoine and García, Carlos Marcelo and Rodríguez, Andrés},
journal={Computers \& Geosciences},
volume={105},
pages={103--114},
year={2017},
publisher={Elsevier}
}
```
---
## 👥 Authors
### Core Team
- **Antoine Patalano** - *Project Lead, Feature Development* - [UNC/ORUS]
- **Leandro Massó** - *Feature Development* - [UNC/ORUS]
### Development Team
- **Nicolas Stefani** - *CLI & Backend Development*
- **Tomas Stefani** - *Frontend Development*
---
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please [open an issue](https://github.com/oruscam/RIVeR/issues) first to discuss what you would like to change.
---
## 📜 License
RIVeR is licensed under the [GNU Affero General Public License v3.0](LICENSE) (AGPL-3.0).
---
## 💭Acknowledgments
- Contributing organizations:
- [UNC (National University of Córdoba)](https://www.unc.edu.ar/) - [Faculty of Exact, Physical and Natural Sciences](https://fcefyn.unc.edu.ar/)
- [INA (National Institute of Water, Argentina)](https://www.argentina.gob.ar/ina)
- [CONICET (National Scientific and Technical Research Council)](https://www.conicet.gov.ar/)
- [WMO HydroHub](https://wmo.int/media/update/winner-of-wmo-hydrohub-innovation-call-latin-america-and-caribbean?book=21576): For funding the development of RIVeR 3 (2024-2025)
- [PIVlab project](https://la.mathworks.com/matlabcentral/fileexchange/27659-pivlab-particle-image-velocimetry-piv-tool-with-gui): The pioneering PIV analysis tool that inspired aspects of RIVeR's development
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"description": "\n<div align=\"center\">\n <img src=\"https://raw.githubusercontent.com/oruscam/RIVeR/main/river/docs/_static/river_logo.svg\" width=\"350px\">\n <br />\n <br />\n\n <p>\n <strong>Modern LSPIV toolkit for water-surface velocity analysis and flow discharge measurements</strong>\n</div>\n\n[]()\n[](https://www.gnu.org/licenses/agpl-3.0)\n[](https://www.python.org/downloads/)\n[](https://reactjs.org/)\n[](https://pypi.org/project/river-cli/)\n[](https://doi.org/10.1016/j.cageo.2017.07.009)\n\n---\n\n# RIVeR: Rectification of Image Velocity Results\n\n**RIVeR** (Rectification of Image Velocity Results) is a modern, open-source toolkit for Large Scale Particle Image Velocimetry (**LSPIV**) distributed by [ORUS](https://orus.cam). Built with **Python** and **React**, it provides a user-friendly interface for water-surface velocity analysis and flow discharge measurements in rivers and large-scale hydraulic models.\n\n\n<figure>\n <img src=\"https://raw.githubusercontent.com/oruscam/RIVeR/main/river/docs/_static/screenshot_results.png\" width=500>\n <p ><i>Example of RIVeR velocimetry analysis of river flow</i></p>\n</figure>\n\n---\n\n## \ud83d\udca7 Overview\nRIVeR is a specialized tool for applying Large Scale Particle Image Velocimetry (LSPIV) techniques as a non-contact method to estimate discharge in rivers and channels from video footage. The software guides the process through intuitive defaults and pre-configured settings, enabling users to generate discharge calculations without extensive prior knowledge of the technique. The workflow guides users through a series of straightforward steps culminating in comprehensive visual reports.\n\nOriginally developed in MATLAB in 2015 and well-received by the hydrology community, RIVeR has now been reimplemented in Python and JavaScript to improve accessibility, performance, and cross-platform compatibility.\n<figure>\n <img src=\"https://raw.githubusercontent.com/oruscam/RIVeR/main/river/docs/_static/oblique_rectification.gif\" width=500>\n <p><i>Demonstration of interactive oblique image rectification process in RIVeR</i></p>\n</figure>\n\n---\n\n\n## \ud83d\udcd6 User Manual\n\nFor a detailed step-by-step guide on using RIVeR's GUI (Graphical User Interface),\nplease refer to the **[User Manual](user-manual.md)**.\n\n---\n\n\n## \u2728 Key Features\n\n* Process footage from multiple sources:\n * UAV/drone aerial imagery\n * Oblique view camera (from riverbank)\n * Fixed station cameras (contiunous monitoring)\n* Frame extraction from videos with customizable parameters\n* FFT-based PIV analysis with multi-pass support for increased accuracy\n* Interactive result visualization with customizable vector fields\n* Georeferencing and coordinate transformations\n* Multi Cross-sectional flow analysis\n* Automated beautiful report generation ([like this one !](https://oruscam.github.io/RIVeR/sample_report.html))\n* Multi-platform support (**Windows**, **macOS**, **Linux**)\n\n\n---\n\n## \ud83c\udf0d Multi-Language Support\n\n- RIVeR available in multiple languages!\n - English \ud83c\uddfa\ud83c\uddf8\n - Spanish \ud83c\udde6\ud83c\uddf7\n - French \ud83c\uddeb\ud83c\uddf7\n - Italian \ud83c\uddee\ud83c\uddf9\n - Portuguese \ud83c\udde7\ud83c\uddf7\n - German \ud83c\udde9\ud83c\uddea\n - [More coming soon!]\n\n---\n## \ud83d\udce5 Download Compiled Releases\n\nIf you don't want to bother with code at all (we get it, sometimes you just want things to work!), pre-compiled standalone versions are available:\n\n| \u229e Windows | \u2318 macOS | \u25c6 Linux |\n|:---:|:---:|:---:|\n| [EXE](https://github.com/oruscam/RIVeR/releases/download/v3.2.0/RIVeR-Windows-3.2.0-Setup.exe) | [DMG](https://github.com/oruscam/RIVeR/releases/download/v3.2.0/RIVeR-Mac-3.2.0-Installer.dmg) | [DEB](https://github.com/oruscam/RIVeR/releases/download/v3.2.0/RIVeR-Linux-3.2.0.deb) [RPM](https://github.com/oruscam/RIVeR/releases/download/v3.2.0/RIVeR-Linux-3.2.0.rpm) |\n\n\nThese packages include both the GUI and CLI tools in a ready-to-use application. No Python or JavaScript knowledge required!\n\n\nThese packages include both the GUI and CLI tools in a ready-to-use application. Simply download, extract (if needed), and run the application - no Python or JavaScript knowledge required!\n\n---\n## \ud83e\uddd1\u200d\ud83d\udcbb Developer Installation & Usage\n\nFor those who prefer to work with the source code or contribute to RIVeR's development, here's how to get started:\n\n### Prerequisites\n\n- Python 3.12+\n- pip package manager\n- Git (for cloning the repository)\n\n### Development Installation\n```bash\ngit clone https://github.com/oruscam/RIVeR.git\ncd RIVeR\npip install -e .\n```\n### CLI Installation\nRIVeR CLI provides a comprehensive set of commands for performing LSPIV analysis through the command line.\n\n```bash\npip install river-cli\n```\n#### Basic Usage\n```bash\nriver-cli [OPTIONS] COMMAND [ARGS]...\n```\nTo see all available commands and options:\n```bash\nriver-cli --help\n```\n#### Example Workflow\n```bash\n# 1. Extract frames from video\nriver-cli video-to-frames river_video.mp4 ./frames --every 2\n\n# 2. Generate transformation matrix\nriver-cli get-uav-transformation-matrix 100 200 300 400 0 0 10 10 --image-path ./frames/frame_001.jpg\n\n# 3. Create masks for PIV analysis\nriver-cli create-mask-and-bbox 3 ./frames/frame_001.jpg ./xsections.json ./transformation_matrix.json --save-png-mask\n\n# 4. Run PIV analysis\nriver-cli piv-analyze ./frames --mask ./mask.json --workdir ./results\n\n# 5. Calculate discharge\nriver-cli update-xsection ./xsections.json ./results/piv_results.json ./transformation_matrix.json --step 2 --fps 30 --id-section 0\n```\n\n### Graphical User Interface (GUI)\n\nRIVeR also provides a user-friendly graphical interface built with React. The GUI offers an intuitive way to perform LSPIV analysis without using command-line tools.\n\nKey GUI features include:\n- Interactive workflow interface\n- Visual cross-section creation\n- Real-time PIV analysis visualization\n- Result export capabilities\n\nFor detailed information about installation, usage, and features of the GUI, please see the dedicated [GUI documentation](gui/README.md).\n\n---\n\n## \ud83d\udcc2 Project Structure\n\n```\nriver/\n.\n\u251c\u2500\u2500 LICENSE\n\u251c\u2500\u2500 examples # Jupyter examples\n\u2502 \u251c\u2500\u2500 00_introduction.ipynb\n\u2502 \u251c\u2500\u2500 01_video_to_frames.ipynb\n\u2502 \u251c\u2500\u2500 02a_nadir_transformation.ipynb\n\u2502 \u251c\u2500\u2500 02b_oblique_transformation.ipynb\n\u2502 \u251c\u2500\u2500 02c_fixed_station_transformation.ipynb\n\u2502 \u251c\u2500\u2500 03_cross_sections.ipynb\n\u2502 \u251c\u2500\u2500 04_piv_analysis.ipynb\n\u2502 \u251c\u2500\u2500 05_discharge_calculation.ipynb\n\u2502 \u251c\u2500\u2500 data\n\u2502 \u251c\u2500\u2500 results\n\u2502 \u2514\u2500\u2500 utils\n\u251c\u2500\u2500 gui\n\u251c\u2500\u2500 pyproject.toml\n\u251c\u2500\u2500 readme.md\n\u251c\u2500\u2500 requirements.txt\n\u2514\u2500\u2500 river\n \u251c\u2500\u2500 cli\n \u251c\u2500\u2500 core\n \u2502 \u251c\u2500\u2500 compute_section.py # Section computation utilities\n \u2502 \u251c\u2500\u2500 coordinate_transform.py # Coordinate system transformations\n \u2502 \u251c\u2500\u2500 define_roi_masks.py # ROI and mask definitions\n \u2502 \u251c\u2500\u2500 exceptions.py # Custom exceptions\n \u2502 \u251c\u2500\u2500 image_preprocessing.py # Image preparation tools\n \u2502 \u251c\u2500\u2500 matlab_smoothn.py # Smoothing algorithms\n \u2502 \u251c\u2500\u2500 piv_fftmulti.py # FFT-based PIV processing\n \u2502 \u251c\u2500\u2500 piv_loop.py # PIV processing loop\n \u2502 \u251c\u2500\u2500 piv_pipeline.py # Main PIV pipeline\n \u2502 \u2514\u2500\u2500 video_to_frames.py # Video frame extraction\n \u2514\u2500\u2500 docs\n```\n---\n\n## \ud83d\udcda Jupyter Examples\n\nBrowse through our collection of Jupyter Notebook examples to learn how to use RIVeR for various analyses (requires development installation):\n\n- [Introduction to RIVeR](examples/00_introduction.ipynb)\n- [Video Frame Extraction](examples/01_video_to_frames.ipynb)\n- [UAV/Drone Transformations](examples/02a_nadir_transformation.ipynb)\n- [Oblique View Transformations](examples/02b_oblique_transformation.ipynb)\n- [Fixed Station Transformations](examples/02c_fixed_station_transformation.ipynb)\n- [Cross Section Analysis](examples/03_cross_sections.ipynb)\n- [PIV Analysis Workflow](examples/04_piv_analysis.ipynb)\n- [Discharge Calculation](examples/05_discharge_calculation.ipynb)\n\nThese interactive examples provide step-by-step guidance for common RIVeR workflows. To run them, make sure you've completed the development installation described above.\n## \ud83d\udd2c Citation\n\nIf you use RIVeR in your research, please cite:\n\n```bibtex\n@article{patalano2017river,\n title={Rectification of Image Velocity Results (RIVeR): A simple and user-friendly toolbox\n for large scale water surface Particle Image Velocimetry (PIV) and\n Particle Tracking Velocimetry (PTV)},\n author={Patalano, Antoine and Garc\u00eda, Carlos Marcelo and Rodr\u00edguez, Andr\u00e9s},\n journal={Computers \\& Geosciences},\n volume={105},\n pages={103--114},\n year={2017},\n publisher={Elsevier}\n}\n```\n---\n## \ud83d\udc65 Authors\n\n### Core Team\n- **Antoine Patalano** - *Project Lead, Feature Development* - [UNC/ORUS]\n- **Leandro Mass\u00f3** - *Feature Development* - [UNC/ORUS]\n\n### Development Team\n- **Nicolas Stefani** - *CLI & Backend Development*\n- **Tomas Stefani** - *Frontend Development*\n\n---\n\n## \ud83e\udd1d Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request. For major changes, please [open an issue](https://github.com/oruscam/RIVeR/issues) first to discuss what you would like to change.\n\n---\n\n## \ud83d\udcdc License\nRIVeR is licensed under the [GNU Affero General Public License v3.0](LICENSE) (AGPL-3.0).\n\n---\n\n## \ud83d\udcadAcknowledgments\n- Contributing organizations:\n - [UNC (National University of C\u00f3rdoba)](https://www.unc.edu.ar/) - [Faculty of Exact, Physical and Natural Sciences](https://fcefyn.unc.edu.ar/)\n - [INA (National Institute of Water, Argentina)](https://www.argentina.gob.ar/ina)\n - [CONICET (National Scientific and Technical Research Council)](https://www.conicet.gov.ar/)\n\n\n- [WMO HydroHub](https://wmo.int/media/update/winner-of-wmo-hydrohub-innovation-call-latin-america-and-caribbean?book=21576): For funding the development of RIVeR 3 (2024-2025)\n- [PIVlab project](https://la.mathworks.com/matlabcentral/fileexchange/27659-pivlab-particle-image-velocimetry-piv-tool-with-gui): The pioneering PIV analysis tool that inspired aspects of RIVeR's development\n",
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JSON
