OTAnalytics
OTAnalytics is a core module of the OpenTrafficCam framework designed to perform traffic analysis on trajectories of road users tracked by OTVision or other tools in videos recorded by OTCamera or other camera systems.
Overview
OTAnalytics provides tools for analyzing traffic data, including:
- Processing trajectory data of road users
- Defining and analyzing traffic flows
- Counting vehicles/road users assigned to flows
- Generating event lists and statistics
- Visualizing traffic data
The application offers multiple user interfaces:
- A graphical desktop interface (using CustomTkinter)
- A command-line interface for automation and batch processing
Installation
Requirements
- Python 3.12
- Dependencies listed in requirements.txt
Installation from GitHub Releases (Recommended)
The easiest way to install OTAnalytics is to download the latest release from the GitHub Releases page.
- Go to the OTAnalytics Releases page
- Download the latest release for your operating system
- Extract the downloaded archive
- Run the application using the instructions in the Usage section
Installation from Source (Linux/macOS)
If you prefer to install from source:
-
Clone the repository:
git clone https://github.com/OpenTrafficCam/OTAnalytics.git cd OTAnalytics
-
Run the installation script:
./install.sh
Installation from Source (Windows)
If you prefer to install from source:
-
Clone the repository:
git clone https://github.com/OpenTrafficCam/OTAnalytics.git cd OTAnalytics
-
Run the installation script:
install.cmd
Usage
Starting the Application
Desktop GUI (Default)
On Linux/macOS:
./start_gui.sh
On Windows:
start_gui.cmd
Command Line Interface
On Linux/macOS:
./start_gui.sh --cli
On Windows:
start_gui.cmd --cli
Configuration
OTAnalytics can be configured using:
- Command-line arguments
- Configuration files (YAML format)
Example configuration options:
- Specify track files for analysis
- Define flow and section configurations using otflow files
- Configure export formats and counting intervals
- Control parallelization with multiple processes
- Include or exclude specific road user classes
Features
- Track Analysis: Process and analyze trajectory data from various sources
- Flow Definition: Define and analyze traffic flows between sections
- Counting: Count road users assgined to flows with configurable time intervals
- Event Detection: Generate event lists when road users cross defined sections
- Visualization: Visualize tracks, flows, and sections
- Export: Export analysis results in various formats
- Filtering: Filter tracks by road user class and time
- Parallelization: Process data using multiple CPU cores
Documentation
For detailed instructions on how to install and use OTAnalytics, please refer to the official documentation.
Contributing
We appreciate your support in the form of both code and comments. Please have a look at the contribute section of the OpenTrafficCam documentation for guidelines on how to contribute to this project.
License
This software is licensed under the GPL-3.0 License
Contact
- GitHub: https://github.com/OpenTrafficCam
- Email: team@opentrafficcam.org
Metadata
Release files for OTAnalytics 0.7.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| otanalytics-0.7.5.tar.gz | 11.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| otanalytics-0.7.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 12.1 MB
Release files / otanalytics-0.7.5.tar.gz
| Download URL | otanalytics-0.7.5.tar.gz |
|---|---|
| Size | 11.5 MB |
| Tags | Source |
|
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Yes |
| Uploaded via |
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Transparency logRelease files / otanalytics-0.7.5-py3-none-any.whl
| Download URL | otanalytics-0.7.5-py3-none-any.whl |
|---|---|
| Size | 647.4 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 30, 2026.
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