Include libraries and .rknn models for other Rockchip SoCs (#8649)

* support for other yolov models and config checks

* apply code formatting

* Information about core mask and inference speed

* update rknn postprocess and remove params

* update model selection

* Apply suggestions from code review

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

* support rknn on all socs

* apply changes from review and fix post process bug

* apply code formatting

* update tip in object_detectors docs

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

docs/docs/configuration/object_detectors.md

@@ -295,16 +295,16 @@ To verify that the integration is working correctly, start Frigate and observe t
 ## Rockchip RKNN-Toolkit-Lite2
 
 This detector is only available if one of the following Rockchip SoCs is used:
-- RK3566/RK3568
 - RK3588/RK3588S
-- RV1103/RV1106
+- RK3568
+- RK3566
 - RK3562
 
 These SoCs come with a NPU that will highly speed up detection.
 
 ### Setup
 
-RKNN support is provided using the `-rk` suffix for the docker image. Moreover, privileged mode must be enabled by adding the `--privileged` flag to your docker run command or `privileged: true` to your `docker-compose.yml` file.
+Use a frigate docker image with `-rk` suffix and enable privileged mode by adding the `--privileged` flag to your docker run command or `privileged: true` to your `docker-compose.yml` file.
 
 ### Configuration
 
@@ -376,3 +376,16 @@ $ cat /sys/kernel/debug/rknpu/load
 model:
   path: /config/model_cache/rknn/my-rknn-model.rknn
 ```
+
+:::tip
+
+When you have a multicore NPU, you can enable all cores to reduce inference times. You should consider activating all cores if you use a larger model like yolov8l. If your NPU has 3 cores (like rk3588/S SoCs), you can enable all 3 cores using:
+
+```yaml
+detectors:
+  rknn:
+    type: rknn
+    core_mask: 0b111
+```
+
+:::

docs/docs/frigate/hardware.md

@@ -103,7 +103,7 @@ Frigate supports SBCs with the following Rockchip SoCs:
 - RV1103/RV1106
 - RK3562
 
-Using the yolov8n model and an Orange Pi 5 Plus with RK3588 SoC inference speeds vary between 25-40 ms.
+Using the yolov8n model and an Orange Pi 5 Plus with RK3588 SoC inference speeds vary between 20 - 25 ms.
 
 ## What does Frigate use the CPU for and what does it use a detector for? (ELI5 Version)