![]() When a match is found a new MQTT topic is published with the results. To improve the chances of finding a match, the processing of the images will repeat until the amount of retries is exhausted or a match is found. These images are passed from the API to the detector(s) specified until a match is found above the defined confidence level. When a Frigate event is received the API begins to process the snapshot.jpg and latest.jpg images from Frigate’s API. When the container starts it subscribes to Frigate’s MQTT events topic and looks for events that contain a person. Being a developer I decided to move my Node-Red logic over to it’s own API, which I then containerized and named Double Take.ĭouble Take is a proxy between Frigate and any of the facial detection projects listed above. I tried using Node-Red and built a pretty complicated flow with retry logic, but it quickly became painful to manage and fine-tune. All of these projects provide RESTful APIs for training and recognizing faces from images, but there was no easy way to send the information directly form Frigate to the detector’s API. This led me to looking at Facebox, CompreFace, and DeepStack. I recently started using Frigate which allowed me to detect when people were in a room, but what if I had friends or family over? I needed a way to distinguish each person from the images Frigate was processing. In a perfect world, the user wouldn’t have wear or do anything, right? Well what about facial recognition? These methods did not produce the results I was looking for or required the user to have their phone or some other device on them. Prior to my solution I’ve tried using beacons, BLE, and a few other options. I’ve been trying to come up with a room presence solution for the past few months and recently created a project that’s working very well for me. If a match is found the image is saved to /.storage/matches/$'Īvailability_topic: 'double-take/available' It is recommended to increase the MQTT snapshot size in the Frigate camera config. When the frigate/+/person/snapshot topic is updated the API will process that image with the configured detector(s). ![]() These images are passed from the API to the configured detector(s) until a match is found that meets the configured requirements. When the frigate/events topic is updated the API begins to process the snapshot.jpg and latest.jpg images from Frigate’s API. Subscribe to Frigate’s MQTT topics and process images for analysis. REST API can be invoked by other applications.Responsive UI and API bundled into single Docker image.Double Take was created to abstract the complexities of the detection services and combine them into an easy to use UI and API. ![]() There’s a lot of great open source software to perform facial recognition, but each of them behave differently.
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