From 8aef5670f6ef715cfd8408e32dff46c017b12ea7 Mon Sep 17 00:00:00 2001 From: Michael Mayer Date: Wed, 10 Aug 2022 17:24:32 +0200 Subject: [PATCH] Commands: Update face options formatting in show_options.go Signed-off-by: Michael Mayer --- internal/commands/show_options.go | 9 +-------- 1 file changed, 1 insertion(+), 8 deletions(-) diff --git a/internal/commands/show_options.go b/internal/commands/show_options.go index d19c6f858..04611e3c6 100644 --- a/internal/commands/show_options.go +++ b/internal/commands/show_options.go @@ -20,14 +20,7 @@ var ShowOptionsCommand = cli.Command{ } var faceOptionsInfo = `!!! info "" - To [recognize faces](https://docs.photoprism.app/user-guide/organize/people/), PhotoPrism first extracts crops from your images using a - [library](https://github.com/esimov/pigo) based on [pixel intensity comparisons](https://dl.photoprism.app/pdf/20140820-Pixel_Intensity_Comparisons.pdf). - These are then fed into TensorFlow to compute [512-dimensional vectors](https://dl.photoprism.app/pdf/20150101_FaceNet.pdf) - for characterization. In the final step, the [DBSCAN algorithm](https://en.wikipedia.org/wiki/DBSCAN) - attempts to cluster these so-called face embeddings, so they can be matched to persons with just a few clicks. - A reasonable range for the similarity distance between face embeddings is between 0.60 and 0.70, with a higher - value being more aggressive and leading to larger clusters with more false positives. - To cluster a smaller number of faces, you can reduce the core to 3 or 2 similar faces. + To [recognize faces](https://docs.photoprism.app/user-guide/organize/people/), PhotoPrism first extracts crops from your images using a [library](https://github.com/esimov/pigo) based on [pixel intensity comparisons](https://dl.photoprism.app/pdf/20140820-Pixel_Intensity_Comparisons.pdf). These are then fed into TensorFlow to compute [512-dimensional vectors](https://dl.photoprism.app/pdf/20150101_FaceNet.pdf) for characterization. In the final step, the [DBSCAN algorithm](https://en.wikipedia.org/wiki/DBSCAN) attempts to cluster these so-called face embeddings, so they can be matched to persons with just a few clicks. A reasonable range for the similarity distance between face embeddings is between 0.60 and 0.70, with a higher value being more aggressive and leading to larger clusters with more false positives. To cluster a smaller number of faces, you can reduce the core to 3 or 2 similar faces. We recommend that only advanced users change these parameters:`