
Remote Machine Learning Not Working
Hi everyone, so I have my Immich instance running on my Ubuntu system. But my machine is kinda slow so I want to use remote machine learning to speed up things. But before uploading everything I decided to try to upload a couple of photos of my face to test whether the face detection is working or not given this feature will use the RML as said in the documentation.
But the weird thing is, when everything is set to default ML URL which is http://immich-machine-learning:3003
everything is running fine. My faces were detected. However, when I change the URL to point to my desktop where the remote machine learning was set up, I deleted the photos, uploaded them again, and let the workers do their job, this time I got no detected faces though I can see the jobs are running. I tried to re-run the jobs over than 10 times now but it's still not working. But when I go back to the default URL, it works. What am I doing wrong? Below is my compose file for both machine.
On my Ubuntu system :
name: immich 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 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 - /etc/localtime:/etc/localtime:ro env_file: - .env ports: - 2283:3001 depends_on: - redis - database restart: always healthcheck: disable: false immich-machine-learning: 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}-cuda extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration file: hwaccel.ml.yml service: cuda # 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: - .env restart: always ports: - 3003:3003 healthcheck: disable: false redis: container_name: immich_redis image: docker.io/redis:6.2-alpine@sha256:e3b17ba9479deec4b7d1eeec1548a253acc5374d68d3b27937fcfe4df8d18c7e healthcheck: test: redis-cli ping || exit 1 restart: always database: container_name: immich_postgres image: docker.io/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0 environment: POSTGRES_PASSWORD: ${DB_PASSWORD} POSTGRES_USER: ${DB_USERNAME} POSTGRES_DB: ${DB_DATABASE_NAME} POSTGRES_INITDB_ARGS: '--data-checksums' volumes: # Do not edit the next line. If you want to change the database storage location on your system, edit the value of DB_DATA_LOCATION in the .env file - ${DB_DATA_LOCATION}:/var/lib/postgresql/data healthcheck: test: pg_isready --dbname='${DB_DATABASE_NAME}' --username='${DB_USERNAME}' || exit 1; Chksum="$$(psql --dbname='${DB_DATABASE_NAME}' --username='${DB_USERNAME}' --tuples-only --no-align --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1 interval: 5m start_interval: 30s start_period: 5m command: ["postgres", "-c", "shared_preload_libraries=vectors.so", "-c", 'search_path="$$user", public, vectors', "-c", "logging_collector=on", "-c", "max_wal_size=2GB", "-c", "shared_buffers=512MB", "-c", "wal_compression=on"] restart: always volumes: model-cache:
On my remote ML system (Using WSL2 and Docker Desktop):
name: immich_remote_ml services: immich-machine-learning: 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}-cuda extends: file: hwaccel.ml.yml service: cuda # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable volumes: - model-cache:/cache restart: always ports: - 3003:3003 volumes: model-cache: name: immich_remote_ml services: immich-machine-learning: 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}-cuda extends: file: hwaccel.ml.yml service: cuda # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable volumes: - model-cache:/cache restart: always ports: - 3003:3003 volumes: model-cache:
If anyone could correct me what I am doing wrong it would be a huge help. Thanks.
Just guessing here, but did you check without hardware acceleration?
Oh, and what's in the ML logs?
Hi, what do you mean by check without hardware acceleration? And where do I access the logs? Is it available in Portainer? I manage my docker images in portainer.