From 15472274ee0dc02211c42340ba8034f1194517b8 Mon Sep 17 00:00:00 2001 From: Nicolas Mowen Date: Fri, 7 Feb 2025 13:12:44 -0700 Subject: [PATCH] Update docs sidebar name (#16370) * Clarify classification * Fix face hierarchy as well --- docs/docs/configuration/face_recognition.md | 2 +- docs/docs/configuration/semantic_search.md | 2 +- docs/sidebars.ts | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/docs/configuration/face_recognition.md b/docs/docs/configuration/face_recognition.md index 2e5ba564a..22968762a 100644 --- a/docs/docs/configuration/face_recognition.md +++ b/docs/docs/configuration/face_recognition.md @@ -54,6 +54,6 @@ When first enabling face recognition it is important to build a foundation of st Then it is recommended to use the `Face Library` tab in Frigate to select and train images for each person as they are detected. When building a strong foundation it is strongly recommended to only train on images that are straight-on. Ignore images from cameras that recognize faces from an angle. Once a person starts to be consistently recognized correctly on images that are straight-on, it is time to move on to the next step. -# Step 2 - Expanding The Dataset +### Step 2 - Expanding The Dataset Once straight-on images are performing well, start choosing slightly off-angle images to include for training. It is important to still choose images where enough face detail is visible to recognize someone. \ No newline at end of file diff --git a/docs/docs/configuration/semantic_search.md b/docs/docs/configuration/semantic_search.md index ab3937c53..bd3d79cae 100644 --- a/docs/docs/configuration/semantic_search.md +++ b/docs/docs/configuration/semantic_search.md @@ -1,6 +1,6 @@ --- id: semantic_search -title: Using Semantic Search +title: Semantic Search --- Semantic Search in Frigate allows you to find tracked objects within your review items using either the image itself, a user-defined text description, or an automatically generated one. This feature works by creating _embeddings_ — numerical vector representations — for both the images and text descriptions of your tracked objects. By comparing these embeddings, Frigate assesses their similarities to deliver relevant search results. diff --git a/docs/sidebars.ts b/docs/sidebars.ts index b0b8cdf48..ebd6af033 100644 --- a/docs/sidebars.ts +++ b/docs/sidebars.ts @@ -33,7 +33,7 @@ const sidebars: SidebarsConfig = { 'configuration/object_detectors', 'configuration/audio_detectors', ], - 'Semantic Search': [ + Classifiers: [ 'configuration/semantic_search', 'configuration/genai', 'configuration/face_recognition',