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https://github.com/serdaraltin/fusion-vision
This module dedicated to processing and analyzing visual data using advanced computer vision algorithms, primarily leveraging Kinect sensor data and OpenCV for real-time applications.
https://github.com/serdaraltin/fusion-vision
3d-reconstruction computer-vision image-processing kinect motion-tracking opencv
Last synced: 8 days ago
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This module dedicated to processing and analyzing visual data using advanced computer vision algorithms, primarily leveraging Kinect sensor data and OpenCV for real-time applications.
- Host: GitHub
- URL: https://github.com/serdaraltin/fusion-vision
- Owner: serdaraltin
- License: gpl-3.0
- Created: 2024-09-08T23:30:50.000Z (25 days ago)
- Default Branch: dev
- Last Pushed: 2024-09-20T23:14:09.000Z (13 days ago)
- Last Synced: 2024-09-22T03:05:37.657Z (12 days ago)
- Topics: 3d-reconstruction, computer-vision, image-processing, kinect, motion-tracking, opencv
- Language: C++
- Homepage:
- Size: 3.18 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Fusion Vision
## Overview
The Vision application is a sophisticated device management system designed to interface with Kinect v2 sensors using the `libfreenect2` library. This application offers functionalities such as listing available devices, opening specific devices, and selecting devices for use. It incorporates a logging system to facilitate debugging and provide informative output throughout the device management process.
## Features
- **Device Management**: Automatically detect, list, and manage Kinect devices.
- **Singleton Design Pattern**: Ensures a single instance of the `DeviceManager`.
- **Configurable Logging**: Adjustable logging levels for better debugging and monitoring.
- **Error Handling**: Robust status reporting for operations.
## Table of Contents
- [Installation](#installation)
- [Usage](#usage)
- [Architecture](#architecture)
- [File Descriptions](#file-descriptions)
- [Classes and Functions](#classes-and-functions)
- [Logging Levels](#logging-levels)
- [Error Handling](#error-handling)
- [Testing](#testing)
- [Contributing](#contributing)
- [License](#license)
## Installation
### Prerequisites
Ensure you have the following installed:
- CMake
- libfreenect2
- A C++ compiler (e.g., g++, clang)
### Steps
1. **Clone the Repository**:
```bash
git clone https://github.com/yourusername/vision.git
cd vision
```
2. **Install Dependencies**:
Follow the installation instructions for `libfreenect2` on your system.
3. **Build the Project**:
```bash
mkdir build
cd build
cmake ..
make
```
4. **Run the Application**:
```bash
./vision
```
## Usage
Upon execution, the Vision application will automatically enumerate connected Kinect devices and log their information to the console. An example output would be:
```
[Info] [Vision] Console Logger initialized.
[Info] [Vision] Listing Devices
[Info] [Vision] Device 0: SERIAL_NUMBER_1
[Info] [Vision] Device 1: SERIAL_NUMBER_2
[Info] [Vision] Vision Finished.
```
## Architecture
The Vision application consists of several key components:
- **Device Management**: Manages the lifecycle and interactions with Kinect devices.
- **Logging System**: Logs important events and statuses to the console.
- **Status Reporting**: Provides feedback on the outcomes of operations.
### Diagram
```plaintext
+------------------+ +-------------------+
| | | |
| DeviceManager |<-------->| ConsoleLogger |
| | | |
+------------------+ +-------------------+
|
v
+------------------+
| |
| Kinect Device |
| |
+------------------+
```
## File Descriptions
- **config.h**: Contains configuration settings and application constants.
- **device.h**: Defines the `Device` struct for holding device attributes.
- **device_manager.h**: Declares the `DeviceManager` class for device management.
- **console_logger.h**: Defines the `ConsoleLogger` class for logging.
- **logger.h**: Abstract base class for logging utilities.
- **status.h**: Contains definitions for operation statuses and result handling.
- **main.cpp**: The entry point of the application, orchestrating the device management workflow.
## Classes and Functions
### `DeviceManager`
Handles the detection and management of Kinect devices.
#### Key Functions
- **`static DeviceManager* getInstance()`**
- Returns the singleton instance of the `DeviceManager`.
- **`Result listDevices(const std::vector& devices) const`**
- Lists and logs all available devices.
- **`Result openDevices(const std::vector& devices)`**
- Opens specified devices for usage (implementation pending).
- **`Result selectDevices(const std::vector& ids)`**
- Selects devices by their IDs and logs their serial numbers.
### `ConsoleLogger`
Implements logging functionalities to the console.
#### Key Functions
- **`static ConsoleLogger* getInstance()`**
- Returns the singleton instance of the `ConsoleLogger`.
- **`void log(Level level, const std::string& message)`**
- Logs messages at the specified logging level.
### `Logger`
Abstract class defining the logging interface.
#### Key Functions
- **`virtual void log(Level level, const std::string &message) = 0`**
- Abstract logging method to be implemented by derived classes.
### `Status`
An enumeration for operation statuses:
- **Success**
- **Error**
- **InvalidParam**
- **NotFound**
## Logging Levels
The application supports several logging levels to control output verbosity:
- **None**: No logging.
- **Error**: Logs error messages.
- **Warning**: Logs warnings.
- **Info**: Logs general information.
- **Debug**: Logs detailed debug information.
## Error Handling
The application implements a structured error handling mechanism using the `Result` struct, which includes status codes and messages to aid in troubleshooting.
## Testing
Unit tests are included for critical components of the application. To run the tests, use:
```bash
make test
```
Ensure your environment is set up correctly to support testing.
## Contributing
Contributions are welcome! Please follow these steps:
1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Submit a pull request with a clear description of your changes.