Add optional docs link to config field messages (#23569)

* add optional docs link to config field messages

* docs tweaks

* add field messages for model dimensions

docs/docs/configuration/object_detectors.md

@@ -73,6 +73,22 @@ This does not affect using hardware for accelerating other tasks such as [semant
 
 :::
 
+### Choosing a model size
+
+Along with picking a detector for your hardware, you will choose a model's **input resolution** (such as `320x320` or `640x640`) and, for model families like YOLOv9, a **variant size** (`tiny`, `small`, etc.). Both affect the balance between accuracy and the inference time your hardware can sustain.
+
+**Resolution (320x320 vs 640x640):** Frigate is optimized for `320x320` models, and `320x320` is the best choice for the vast majority of setups. Frigate is specifically designed to compensate for the smaller model by cropping a region of motion from the full frame and zooming into it before running detection, so a `320x320` model is actually _better_ at small and distant objects — not worse. A `640x640` model is slower and uses more resources, and its main benefit is fitting more objects into a single inference when many objects are spread across a large area. Recent versions of Frigate have improved support for `640x640` models, but `320x320` remains the recommended starting point for nearly all setups.
+
+**Variant size (tiny/small/medium):** Larger variants are gradually more accurate but slower. Whether the difference is noticeable depends on your specific cameras and scenes. A good rule of thumb is to use the largest model your hardware can run without skipping detections, which you can monitor on the <NavPath path="System > Metrics > Cameras" /> page in the UI — better accuracy only helps if your detector keeps up with the detection load across all cameras.
+
+**Acceptable inference time depends on your hardware.** Inference time alone does not tell the whole story, because different hardware has different capacity. A GPU can run multiple instances of the same model concurrently, so an inference time around 30ms can still keep up with several cameras. A Google Coral runs only a single instance of the model, so it needs a much lower inference time (around 10ms) to keep up.
+
+:::tip
+
+The best detection accuracy comes from a model trained on images that look like what Frigate actually sees — security camera footage cropped to regions of interest. You can train or fine-tune your own model on images like this and run it as a custom model (see the per-detector sections below), but [Frigate+](/plus) makes this much easier by handling the training for you on images submitted from your own cameras. For YOLOv9, the `s` (small) variant at `320x320` resolution is a good place to start.
+
+:::
+
 # Officially Supported Detectors
 
 Frigate provides a number of builtin detector types. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.

docs/docs/usage/history.md

@@ -29,7 +29,7 @@ If you see **"No recordings found for this time"**, the most common causes are:
 
 A toggle (a drawer on mobile) switches the side panel between three modes:
 
-- **Timeline** — a scrubbable vertical timeline of the selected camera, annotated with a motion line, review-item markers, and gaps where no recording exists.
+- **Timeline** — a scrubbable vertical timeline of the selected camera. Horizontal lines down the center represent motion, with longer lines indicating more motion at that moment. Review items are marked as shaded areas (**red** for alerts, **orange** for detections), and sections with no colored background are times when no recording exists.
 - **Events** — a scrollable list of the camera's review items for the time range; clicking one seeks the player to it.
 - **Detail** — the [tracking details inspector](#the-detail-view) for the objects in view.