new services + proxy network rework

Immich/docker-compose.yml

@@ -13,9 +13,9 @@ services:
   immich-server:
     container_name: immich_server
     image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
-    # extends:
-    #   file: hwaccel.transcoding.yml
-    #   service: cpu # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
+    extends:
+      file: hwaccel.transcoding.yml
+      service: quicksync # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
     volumes:
       # Do not edit the next line. If you want to change the media storage location on your system, edit the value of UPLOAD_LOCATION in the .env file
       - ${UPLOAD_LOCATION}:/usr/src/app/upload
@@ -25,8 +25,8 @@ services:
       - /zstore/photos/Album-Maly:/zstore/photos/Album-Maly:ro
     env_file:
       - .env
-    ports:
-      - '2283:2283'
+#    ports:
+#      - '2283:2283'
     depends_on:
       - redis
       - database
@@ -38,10 +38,10 @@ services:
     container_name: immich_machine_learning
     # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
     # Example tag: ${IMMICH_VERSION:-release}-cuda
-    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
-    # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
-    #   file: hwaccel.ml.yml
-    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
+    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}-openvino
+    extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
+      file: hwaccel.ml.yml
+      service: openvino # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
     volumes:
       - model-cache:/cache
     env_file:
@@ -74,3 +74,8 @@ services:
 
 volumes:
   model-cache:
+
+networks:
+  default:
+    external: true
+    name: proxy

Immich/hwaccel.ml.yml

@@ -0,0 +1,57 @@
+# Configurations for hardware-accelerated machine learning
+
+# If using Unraid or another platform that doesn't allow multiple Compose files,
+# you can inline the config for a backend by copying its contents
+# into the immich-machine-learning service in the docker-compose.yml file.
+
+# See https://docs.immich.app/features/ml-hardware-acceleration for info on usage.
+
+services:
+  armnn:
+    devices:
+      - /dev/mali0:/dev/mali0
+    volumes:
+      - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver)
+      - /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)
+  
+  rknn:
+    security_opt:
+      - systempaths=unconfined
+      - apparmor=unconfined
+    devices:
+      - /dev/dri:/dev/dri
+
+  cpu: {}
+
+  cuda:
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities:
+                - gpu
+
+  rocm:
+    group_add:
+      - video
+    devices:
+      - /dev/dri:/dev/dri
+      - /dev/kfd:/dev/kfd
+
+  openvino:
+    device_cgroup_rules:
+      - 'c 189:* rmw'
+    devices:
+      - /dev/dri:/dev/dri
+    volumes:
+      - /dev/bus/usb:/dev/bus/usb
+
+  openvino-wsl:
+    devices:
+      - /dev/dri:/dev/dri
+      - /dev/dxg:/dev/dxg
+    volumes:
+      - /dev/bus/usb:/dev/bus/usb
+      - /usr/lib/wsl:/usr/lib/wsl

Immich/hwaccel.transcoding.yml

@@ -0,0 +1,55 @@
+# Configurations for hardware-accelerated transcoding
+
+# If using Unraid or another platform that doesn't allow multiple Compose files,
+# you can inline the config for a backend by copying its contents
+# into the immich-microservices service in the docker-compose.yml file.
+
+# See https://docs.immich.app/features/hardware-transcoding for more info on using hardware transcoding.
+
+services:
+  cpu: {}
+
+  nvenc:
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities:
+                - gpu
+                - compute
+                - video
+
+  quicksync:
+    devices:
+      - /dev/dri:/dev/dri
+
+  rkmpp:
+    security_opt: # enables full access to /sys and /proc, still far better than privileged: true
+      - systempaths=unconfined
+      - apparmor=unconfined
+    group_add:
+      - video
+    devices:
+      - /dev/rga:/dev/rga
+      - /dev/dri:/dev/dri
+      - /dev/dma_heap:/dev/dma_heap
+      - /dev/mpp_service:/dev/mpp_service
+      #- /dev/mali0:/dev/mali0 # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
+    volumes:
+      #- /etc/OpenCL:/etc/OpenCL:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
+      #- /usr/lib/aarch64-linux-gnu/libmali.so.1:/usr/lib/aarch64-linux-gnu/libmali.so.1:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
+
+  vaapi:
+    devices:
+      - /dev/dri:/dev/dri
+
+  vaapi-wsl: # use this for VAAPI if you're running Immich in WSL2
+    devices:
+      - /dev/dri:/dev/dri
+      - /dev/dxg:/dev/dxg
+    volumes:
+      - /usr/lib/wsl:/usr/lib/wsl
+    environment:
+      - LIBVA_DRIVER_NAME=d3d12