From 6ec075b9bfe0b5eb291ffca32fce1bb1e8180aae Mon Sep 17 00:00:00 2001 From: sudolulo Date: Sun, 14 Jun 2026 13:15:20 -0400 Subject: [PATCH 1/2] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 3e607c9..942f0bb 100644 --- a/README.md +++ b/README.md @@ -11,7 +11,7 @@ `winnow` pulls photos from your [Immich](https://immich.app) library, selects the most diverse and highest-quality subset using AI embeddings, and delivers them as training data for [Frigate](https://frigate.video)'s face recognition and object classification models. -The best Frigate training data is images you curate manually — photos taken specifically for recognition, in controlled conditions, uploaded directly through Frigate's UI. For people you can do that for, do it. winnow is for everyone else: people in your library you want Frigate to recognise but don't have dedicated training photos for. It mines your existing Immich library for the most diverse spread of real-world appearances and fills the gap. +The best Frigate training data is images you curate manually — photos taken specifically for recognition, in controlled conditions, uploaded directly through Frigate's UI. Winnow is meant to people in your library, not replace manual training. In some cases one has people they would like to recognize that do not occur in detections enough to train a diverse dataset. This is meant to fill that gap. > **winnow only touches files it uploaded.** Faces added to Frigate manually through its UI are never deleted, replaced, or modified — not by quality replacement, not by `RESET_PERSON`, not by stale cleanup. Your manually curated images are always the primary dataset; winnow only adds to it. From 3e030b361e389dc5828c6e8f63b06db895aa7529 Mon Sep 17 00:00:00 2001 From: sudolulo Date: Sun, 14 Jun 2026 13:15:57 -0400 Subject: [PATCH 2/2] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 942f0bb..e035d47 100644 --- a/README.md +++ b/README.md @@ -11,7 +11,7 @@ `winnow` pulls photos from your [Immich](https://immich.app) library, selects the most diverse and highest-quality subset using AI embeddings, and delivers them as training data for [Frigate](https://frigate.video)'s face recognition and object classification models. -The best Frigate training data is images you curate manually — photos taken specifically for recognition, in controlled conditions, uploaded directly through Frigate's UI. Winnow is meant to people in your library, not replace manual training. In some cases one has people they would like to recognize that do not occur in detections enough to train a diverse dataset. This is meant to fill that gap. +The best Frigate training data is images you curate manually — photos taken specifically for recognition, in controlled conditions, uploaded directly through Frigate's UI. Winnow is meant to supplement people in your library, not replace manual training. In some cases one has people they would like to recognize that do not occur in detections often enough to train a diverse dataset. This is meant to fill that gap. > **winnow only touches files it uploaded.** Faces added to Frigate manually through its UI are never deleted, replaced, or modified — not by quality replacement, not by `RESET_PERSON`, not by stale cleanup. Your manually curated images are always the primary dataset; winnow only adds to it.