Merge ab59fdf570 into 5f2536dcd8

Co-authored-by: Shay Collings <shay.collings@gmail.com>

.github/workflows/build-rk.yml

@@ -0,0 +1,66 @@
+name: Build Rockchip
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - dev
+      - fix-rk3588s-support
+
+concurrency:
+  group: ${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  rockchip_build:
+    runs-on: ubuntu-latest
+    name: Build Rockchip Image
+    permissions:
+      contents: read
+      packages: write
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+      
+      - id: lowercaseRepo
+        uses: ASzc/change-string-case-action@v6
+        with:
+          string: ${{ github.repository }}
+      
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v3
+      
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+      
+      - name: Log in to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+      
+      - name: Create version file
+        run: make version
+      
+      - name: Create short sha
+        id: sha
+        run: echo "SHORT_SHA=${GITHUB_SHA::7}" >> $GITHUB_OUTPUT
+      
+      - name: Build and push Rockchip image
+        uses: docker/bake-action@v5
+        with:
+          push: true
+          targets: rk
+          files: docker/rockchip/rk.hcl
+          set: |
+            rk.tags=ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ steps.sha.outputs.SHORT_SHA }}-rk
+            rk.tags=ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:latest-rk
+            *.cache-from=type=gha
+            *.cache-to=type=gha,mode=max
+      
+      - name: Show image tags
+        run: |
+          echo "Images published:"
+          echo "  ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ steps.sha.outputs.SHORT_SHA }}-rk"
+          echo "  ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:latest-rk"

docs/docs/configuration/object_detectors.md

@@ -1352,7 +1352,7 @@ To convert a onnx model to the rknn format using the [rknn-toolkit2](https://git
 This is an example configuration file that you need to adjust to your specific onnx model:
 
 ```yaml
-soc: ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588"]
+soc: ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588", "rk3588s"]
 quantization: false
 
 output_name: "{input_basename}"

docs/docs/frigate/hardware.md

@@ -273,6 +273,7 @@ Frigate supports hardware video processing on all Rockchip boards. However, hard
 - RK3568
 - RK3576
 - RK3588
+- RK3588S
 
 | Name           | YOLOv9 Inference Time | YOLO-NAS Inference Time     | YOLOx Inference Time    |
 | -------------- | --------------------- | --------------------------- | ----------------------- |

docs/docs/frigate/installation.md

@@ -689,3 +689,42 @@ docker run \
 ```
 
 Log into QNAP, open Container Station. Frigate docker container should be listed under 'Overview' and running. Visit Frigate Web UI by clicking Frigate docker, and then clicking the URL shown at the top of the detail page.
+
+## macOS - Apple Silicon
+
+:::warning
+
+macOS uses port 5000 for its Airplay Receiver service.  If you want to expose port 5000 in Frigate for local app and API access the port will need to be mapped to another port on the host e.g. 5001
+
+Failure to remap port 5000 on the host will result in the WebUI and all API endpoints on port 5000 being unreachable, even if port 5000 is exposed correctly in Docker.
+
+:::
+
+Docker containers on macOS can be orchestrated by either [Docker Desktop](https://docs.docker.com/desktop/setup/install/mac-install/) or [OrbStack](https://orbstack.dev) (native swift app). The difference in inference speeds is negligable, however CPU, power consumption and container start times will be lower on OrbStack because it is a native Swift application. 
+
+To allow Frigate to use the Apple Silicon Neural Engine / Processing Unit (NPU) the host must be running [Apple Silicon Detector](../configuration/object_detectors.md#apple-silicon-detector) on the host (outside Docker)
+
+#### Docker Compose example
+```yaml
+services:
+  frigate:
+    container_name: frigate
+    image: ghcr.io/blakeblackshear/frigate:stable-arm64
+    restart: unless-stopped
+    shm_size: "512mb" # update for your cameras based on calculation above
+    volumes:
+      - /etc/localtime:/etc/localtime:ro
+      - /path/to/your/config:/config
+      - /path/to/your/recordings:/recordings
+    ports:
+      - "8971:8971"
+      # If exposing on macOS map to a diffent host port like 5001 or any orher port with no conflicts
+      # - "5001:5000" # Internal unauthenticated access. Expose carefully. 
+      - "8554:8554" # RTSP feeds
+    extra_hosts:
+      # This is very important
+      # It allows frigate access to the NPU on Apple Silicon via Apple Silicon Detector
+      - "host.docker.internal:host-gateway" # Required to talk to the NPU detector
+    environment:
+      - FRIGATE_RTSP_PASSWORD: "password"
+```

frigate/const.py

@@ -78,7 +78,7 @@ FFMPEG_HWACCEL_AMF = "preset-amd-amf"
 FFMPEG_HVC1_ARGS = ["-tag:v", "hvc1"]
 
 # RKNN constants
-SUPPORTED_RK_SOCS = ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588"]
+SUPPORTED_RK_SOCS = ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588", "rk3588s"]
 
 # Regex constants
 

frigate/detectors/plugins/rknn.py

@@ -90,6 +90,9 @@ class Rknn(DetectionApi):
     def parse_model_input(self, model_path, soc):
         model_props = {}
 
+        # Map rk3588s to rk3588 for model compatibility
+        model_soc = "rk3588" if soc == "rk3588s" else soc
+
         # find out if user provides his own model
         # user provided models should be a path and contain a "/"
         if "/" in model_path:
@@ -146,7 +149,7 @@ class Rknn(DetectionApi):
                     model_props["model_type"] = model_type
 
             if model_matched:
-                model_props["filename"] = model_path + f"-{soc}-v2.3.2-2.rknn"
+                model_props["filename"] = model_path + f"-{model_soc}-v2.3.2-2.rknn"
 
                 model_props["path"] = model_cache_dir + model_props["filename"]
 

frigate/util/rknn_converter.py

@@ -189,13 +189,16 @@ def convert_onnx_to_rknn(
             logger.debug("Could not determine SoC type")
             return False
 
+    # Map rk3588s to rk3588 for RKNN toolkit compatibility
+    target_soc = "rk3588" if soc == "rk3588s" else soc
+
     # Get model config for the specified type
     if model_type not in MODEL_TYPE_CONFIGS:
         logger.debug(f"Unsupported model type: {model_type}")
         return False
 
     config = MODEL_TYPE_CONFIGS[model_type].copy()
-    config["target_platform"] = soc
+    config["target_platform"] = target_soc
 
     # RKNN toolkit requires .onnx extension, create temporary copy if needed
     temp_onnx_path = None