Revolutionizing Face Recognition with This New Breakthrough!

Revolutionizing Face Recognition with This New Breakthrough!

Table of Contents:

  1. Introduction
  2. What is Double Take
  3. Features and Benefits of Double Take
  4. Setting Up Double Take 4.1 Installing the Home Assistant Add-on 4.2 Configuring MQTT, Frigate, and DeepStack 4.3 Training Faces 4.4 Creating Automations
  5. Conclusion

Introduction

In this article, we will explore Double Take, an open-source project designed to be a unified interface for processing and training facial recognition images. We will discuss its features, benefits, and how to set it up using Home Assistant. Additionally, we will cover the process of training faces using Double Take and creating automations for notifications. So let's dive in and learn more about this powerful tool.

What is Double Take

Double Take is an open-source project created by David Yakuwenko. It combines the powers of object detection and face recognition in one unified interface. With Double Take, users can easily process and train facial recognition images, making it more accessible and user-friendly than ever before. It integrates with Home Assistant and MQTT, and supports popular face detection models such as DeepStack, ComproFace, and Facebox.

Features and Benefits of Double Take

Double Take offers several features and benefits that make it a powerful tool for facial recognition:

  1. Unified Interface: Double Take provides a centralized platform for processing and training facial recognition images, eliminating the need for manual intervention and disconnected systems.
  2. Easy Training: Users can train facial recognition images in seconds directly from the UI, making it simple and accessible for anyone to use.
  3. Automatic Facial Detection: Double Take handles the process of running facial detection automatically after a person is detected, streamlining the entire process.
  4. Support for Different Detectors: Double Take supports three different face detection models - DeepStack, ComproFace, and Facebox, providing flexibility for users to choose the best option for their needs.
  5. Integration with Frigate: Double Take works seamlessly with Frigate as the NVR, handling the recording of footage snapshots and object detection.

Setting Up Double Take

To set up Double Take, follow these steps:

4.1 Installing the Home Assistant Add-on

Installing Double Take as a Home Assistant add-on is the recommended method. Here's how to do it:

  1. Open the Home Assistant Supervisor and navigate to the Add-on Store.
  2. Click on the three dots in the top right-HAND corner and select "Repositories."
  3. Add the repository for the Double Take add-on by pasting the provided link.
  4. Find the "Double Take" entry in the add-on list and click "Install."
  5. Configure the add-on options and start the add-on.

4.2 Configuring MQTT, Frigate, and DeepStack

Once Double Take is installed, You need to configure MQTT, Frigate, and DeepStack. Here's how:

  1. Open the Double Take UI and go to the "Config" tab.
  2. Enter the MQTT broker details, including the IP address, username, and password.
  3. Specify the URL of your Frigate server and the DeepStack URL.
  4. Save the config and restart Double Take.

4.3 Training Faces

With Double Take set up, you can start training faces. Here are two ways to do it:

  1. Upload Images: Use the Double Take UI to upload images for training. DeepStack will start training a model Based on the uploaded images.
  2. Use Detected Images: Optionally, you can train faces using the images detected by Frigate. Select the images from the camera matches page and associate them with a person's name.

4.4 Creating Automations

Double Take integrates with Home Assistant, allowing you to Create automations for notifications. Here's how to do it:

  1. Use the exposed sensors in Home Assistant to trigger automations based on detected faces or unrecognized individuals.
  2. Create an automation in Home Assistant's configuration using the state triggers from Double Take's sensors.
  3. Specify the actions to be taken when a match or an unknown face is detected. You can use the notification service to receive notifications on your preferred devices.

Conclusion

Double Take is a powerful tool that combines object detection and face recognition into a unified interface. Its user-friendly UI and seamless integration with Home Assistant make it accessible to all users. By following the installation process and training faces with Double Take, you can enhance the security and automation capabilities of your smart home. So give it a try and experience the benefits of this innovative facial recognition solution.

Highlights:

  • Double Take is an open-source project that combines object detection and face recognition in a unified interface.
  • It simplifies the process of processing and training facial recognition images.
  • Double Take integrates with Home Assistant, MQTT, and popular face detection models.
  • It provides automatic facial detection and supports different detectors.
  • Setting up Double Take involves installing the Home Assistant add-on and configuring MQTT, Frigate, and DeepStack.
  • Users can train faces by uploading images or using detected images from Frigate.
  • Double Take allows for the creation of automations for notifications based on detected or unrecognized individuals.

FAQ

Q: What is Double Take? A: Double Take is an open-source project that combines object detection and face recognition in a unified interface.

Q: How do I install Double Take? A: You can install Double Take as a Home Assistant add-on through the Supervisor's Add-on Store.

Q: Does Double Take support different face detection models? A: Yes, Double Take supports DeepStack, ComproFace, and Facebox as face detection models.

Q: Can I train faces using images from my camera? A: Yes, Double Take allows you to train faces using images captured by your camera.

Q: How can I create automations with Double Take? A: You can create automations using the exposed sensors in Home Assistant that trigger based on detected faces or unknown individuals.

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