简记immich初体验 - 向阳哌小站

从大概半年前我就在关注immich了，不过因为服务器架构频繁变动，因此没有去动手部署。目前已经基本定型（其实是没精力折腾了），因此开始部署一些“家庭必备”小服务。

GPU Support#

PVE，IOMMU，禁用nouveau，直通显卡，ubuntu（其他发行版也可），Nvidia-driver，CUDA，CUDNN，老生常谈的事情了，这里不再赘述
随后需要为docker启用GPU支持，docker安装，nvidia-container-toolkit，随手丢个链接：https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
需要时请查阅最新版文档，旧版本不一定生效（痛骂NoVideo）

Docker Compose#

懒狗快捷指南：#

docker-compose.yml
hwaccel.ml.yml
hwaccel.transcoding.yml
.env

具体实现：#

接下来的四个文件是按照官网说明编写的，但运行时出现了问题，不要直接复制粘贴！！！

docker-compose.yml

1
#
2
# WARNING: Make sure to use the docker-compose.yml of the current release:
3
#
4
# https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml
5
#
6
# The compose file on main may not be compatible with the latest release.
7
#
8

9
name: immich
10

11
services:
12
  immich-server:
13
    container_name: immich_server
14
    image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
15
    extends:
16
      file: hwaccel.transcoding.yml
17
      service: nvenc # Set to 'nvenc' for Nvidia GPU-based hardware transcoding
18
      #   service: cpu # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
19
    volumes:
20
      # 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
21
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
22
      - /etc/localtime:/etc/localtime:ro
23
    env_file:
24
      - .env
25
    ports:
26
      - 2283:3001
27
    depends_on:
28
      - redis
29
      - database
30
    restart: always
31
    healthcheck:
32
      disable: false
33

34
  immich-machine-learning:
35
    container_name: immich_machine_learning
36
    # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
37
    # Example tag: ${IMMICH_VERSION:-release}-cuda
38
    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}-cuda # Adding -cuda to enable CUDA support
39
    extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
40
      file: hwaccel.ml.yml
41
      service: cuda # Set to 'cuda' for Nvidia GPU-based machine learning acceleration
42
      #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
43
    volumes:
44
      - model-cache:/cache
45
    env_file:
46
      - .env
47
    restart: always
48
    healthcheck:
49
      disable: false
50

51
  redis:
52
    container_name: immich_redis
53
    image: docker.io/redis:6.2-alpine@sha256:e3b17ba9479deec4b7d1eeec1548a253acc5374d68d3b27937fcfe4df8d18c7e
54
    healthcheck:
55
      test: redis-cli ping || exit 1
56
    restart: always
57

58
  database:
59
    container_name: immich_postgres
60
    image: docker.io/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
61
    environment:
62
      POSTGRES_PASSWORD: ${DB_PASSWORD}
63
      POSTGRES_USER: ${DB_USERNAME}
64
      POSTGRES_DB: ${DB_DATABASE_NAME}
65
      POSTGRES_INITDB_ARGS: '--data-checksums'
66
    volumes:
67
      # 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
68
      - ${DB_DATA_LOCATION}:/var/lib/postgresql/data
69
    healthcheck:
70
      test: pg_isready --dbname='${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"; [ "$$Chksum" = '0' ] || exit 1
71
      interval: 5m
72
      start_interval: 30s
73
      start_period: 5m
74
    command: ["postgres", "-c", "shared_preload_libraries=vectors.so", "-c", 'search_path="$$user", public, vectors', "-c", "logging_collector=on", "-c", "max_wal_size=2GB", "-c", "shared_buffers=512MB", "-c", "wal_compression=on"]
75
    restart: always
76

77
volumes:
78
  model-cache:

hwaccel.ml.yml

1
# Configurations for hardware-accelerated machine learning
2

3
# If using Unraid or another platform that doesn't allow multiple Compose files,
4
# you can inline the config for a backend by copying its contents
5
# into the immich-machine-learning service in the docker-compose.yml file.
6

7
# See https://immich.app/docs/features/ml-hardware-acceleration for info on usage.
8

9
services:
10
  armnn:
11
    devices:
12
      - /dev/mali0:/dev/mali0
13
    volumes:
14
      - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver)
15
      - /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)
16

17
  cpu: {}
18

19
  cuda:
20
    deploy:
21
      resources:
22
        reservations:
23
          devices:
24
            - driver: nvidia
25
              count: 1
26
              capabilities:
27
                - gpu
28

29
  openvino:
30
    device_cgroup_rules:
31
      - 'c 189:* rmw'
32
    devices:
33
      - /dev/dri:/dev/dri
34
    volumes:
35
      - /dev/bus/usb:/dev/bus/usb
36

37
  openvino-wsl:
38
    devices:
39
      - /dev/dri:/dev/dri
40
      - /dev/dxg:/dev/dxg
41
    volumes:
42
      - /dev/bus/usb:/dev/bus/usb
43
      - /usr/lib/wsl:/usr/lib/wsl

hwaccel.transcoding.yml

1
# Configurations for hardware-accelerated transcoding
2

3
# If using Unraid or another platform that doesn't allow multiple Compose files,
4
# you can inline the config for a backend by copying its contents
5
# into the immich-microservices service in the docker-compose.yml file.
6

7
# See https://immich.app/docs/features/hardware-transcoding for more info on using hardware transcoding.
8

9
services:
10
  cpu: {}
11

12
  nvenc:
13
    deploy:
14
      resources:
15
        reservations:
16
          devices:
17
            - driver: nvidia
18
              count: 1
19
              capabilities:
20
                - gpu
21
                - compute
22
                - video
23

24
  quicksync:
25
    devices:
26
      - /dev/dri:/dev/dri
27

28
  rkmpp:
29
    security_opt: # enables full access to /sys and /proc, still far better than privileged: true
30
      - systempaths=unconfined
31
      - apparmor=unconfined
32
    group_add:
33
      - video
34
    devices:
35
      - /dev/rga:/dev/rga
36
      - /dev/dri:/dev/dri
37
      - /dev/dma_heap:/dev/dma_heap
38
      - /dev/mpp_service:/dev/mpp_service
39
      #- /dev/mali0:/dev/mali0 # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
40
    volumes:
41
      #- /etc/OpenCL:/etc/OpenCL:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
42
      #- /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
43

44
  vaapi:
45
    devices:
46
      - /dev/dri:/dev/dri
47

48
  vaapi-wsl: # use this for VAAPI if you're running Immich in WSL2
49
    devices:
50
      - /dev/dri:/dev/dri
51
    volumes:
52
      - /usr/lib/wsl:/usr/lib/wsl
53
    environment:
54
      - LD_LIBRARY_PATH=/usr/lib/wsl/lib
55
      - LIBVA_DRIVER_NAME=d3d12

.env

1
# You can find documentation for all the supported env variables at https://immich.app/docs/install/environment-variables
2

3
# The location where your uploaded files are stored
4
UPLOAD_LOCATION=/AppData/immich/library
5
# The location where your database files are stored
6
DB_DATA_LOCATION=/AppData/immich/postgres
7

8
# To set a timezone, uncomment the next line and change Etc/UTC to a TZ identifier from this list: https://en.wikipedia.org/wiki/List_of_tz_database_time_zones#List
9
# TZ=Etc/UTC
10

11
# The Immich version to use. You can pin this to a specific version like "v1.71.0"
12
IMMICH_VERSION=release
13

14
# Connection secret for postgres. You should change it to a random password
15
# Please use only the characters `A-Za-z0-9`, without special characters or spaces
16
DB_PASSWORD=postgres
17

18
# The values below this line do not need to be changed
19
###################################################################################
20
DB_USERNAME=postgres
21
DB_DATABASE_NAME=immich

通过查看日志发现了问题：

1
                             RuntimeError:
2
                             /onnxruntime_src/onnxruntime/core/providers/cuda/cu
3
                             da_call.cc:123 std::conditional_t<THRW, void,
4
                             onnxruntime::common::Status>
5
                             onnxruntime::CudaCall(ERRTYPE, const char*, const
6
                             char*, ERRTYPE, const char*, const char*, int)
7
                             [with ERRTYPE = cudaError; bool THRW = true;
8
                             std::conditional_t<THRW, void, common::Status> =
9
                             void]
10
                             /onnxruntime_src/onnxruntime/core/providers/cuda/cu
11
                             da_call.cc:116 std::conditional_t<THRW, void,
12
                             onnxruntime::common::Status>
13
                             onnxruntime::CudaCall(ERRTYPE, const char*, const
14
                             char*, ERRTYPE, const char*, const char*, int)
15
                             [with ERRTYPE = cudaError; bool THRW = true;
16
                             std::conditional_t<THRW, void, common::Status> =
17
                             void] CUDA failure 100: no CUDA-capable device is
18
                             detected ; GPU=30355 ; hostname=f0cdef844009 ;
19
                             file=/onnxruntime_src/onnxruntime/core/providers/cu
20
                             da/cuda_execution_provider.cc ; line=280 ;
21
                             expr=cudaSetDevice(info_.device_id);
22

23

24

25
                             The above exception was the direct cause of the
26
                             following exception:
27

28
                             ╭─────── Traceback (most recent call last) ───────╮
29
                             │ /usr/src/app/main.py:152 in predict             │
30
                             │                                                 │
31
                             │   149 │   │   inputs = text                     │
32
                             │   150 │   else:                                 │
33
                             │   151 │   │   raise HTTPException(400, "Either  │
34
                             │ ❱ 152 │   response = await run_inference(inputs │
35
                             │   153 │   return ORJSONResponse(response)       │
36
                             │   154                                           │
37
                             │   155                                           │
38
                             │                                                 │
39
                             │ /usr/src/app/main.py:175 in run_inference       │
40
                             │                                                 │
41
                             │   172 │   │   response[entry["task"]] = output  │
42
                             │   173 │                                         │
43
                             │   174 │   without_deps, with_deps = entries     │
44
                             │ ❱ 175 │   await asyncio.gather(*[_run_inference │
45
                             │   176 │   if with_deps:                         │
46
                             │   177 │   │   await asyncio.gather(*[_run_infer │
47
                             │   178 │   if isinstance(payload, Image):        │
48
                             │                                                 │
49
                             │ /usr/src/app/main.py:169 in _run_inference      │
50
                             │                                                 │
51
                             │   166 │   │   │   except KeyError:              │
52
                             │   167 │   │   │   │   message = f"Task {entry[' │
53
                             │       output of {dep}"                          │
54
                             │   168 │   │   │   │   raise HTTPException(400,  │
55
                             │ ❱ 169 │   │   model = await load(model)         │
56
                             │   170 │   │   output = await run(model.predict, │
57
                             │   171 │   │   outputs[model.identity] = output  │
58
                             │   172 │   │   response[entry["task"]] = output  │
59
                             │                                                 │
60
                             │ /usr/src/app/main.py:213 in load                │
61
                             │                                                 │
62
                             │   210 │   │   return model                      │
63
                             │   211 │                                         │
64
                             │   212 │   try:                                  │
65
                             │ ❱ 213 │   │   return await run(_load, model)    │
66
                             │   214 │   except (OSError, InvalidProtobuf, Bad │
67
                             │   215 │   │   log.warning(f"Failed to load {mod │
68
                             │       '{model.model_name}'. Clearing cache.")   │
69
                             │   216 │   │   model.clear_cache()               │
70
                             │                                                 │
71
                             │ /usr/src/app/main.py:188 in run                 │
72
                             │                                                 │
73
                             │   185 │   if thread_pool is None:               │
74
                             │   186 │   │   return func(*args, **kwargs)      │
75
                             │   187 │   partial_func = partial(func, *args, * │
76
                             │ ❱ 188 │   return await asyncio.get_running_loop │
77
                             │   189                                           │
78
                             │   190                                           │
79
                             │   191 async def load(model: InferenceModel) ->  │
80
                             │                                                 │
81
                             │ /usr/local/lib/python3.11/concurrent/futures/th │
82
                             │ read.py:58 in run                               │
83
                             │                                                 │
84
                             │ /usr/src/app/main.py:200 in _load               │
85
                             │                                                 │
86
                             │   197 │   │   │   raise HTTPException(500, f"Fa │
87
                             │   198 │   │   with lock:                        │
88
                             │   199 │   │   │   try:                          │
89
                             │ ❱ 200 │   │   │   │   model.load()              │
90
                             │   201 │   │   │   except FileNotFoundError as e │
91
                             │   202 │   │   │   │   if model.model_format ==  │
92
                             │   203 │   │   │   │   │   raise e               │
93
                             │                                                 │
94
                             │ /usr/src/app/models/base.py:53 in load          │
95
                             │                                                 │
96
                             │    50 │   │   self.download()                   │
97
                             │    51 │   │   attempt = f"Attempt #{self.load_a │
98
                             │       else "Loading"                            │
99
                             │    52 │   │   log.info(f"{attempt} {self.model_ │
100
                             │       '{self.model_name}' to memory")           │
101
                             │ ❱  53 │   │   self.session = self._load()       │
102
                             │    54 │   │   self.loaded = True                │
103
                             │    55 │                                         │
104
                             │    56 │   def predict(self, *inputs: Any, **mod │
105
                             │                                                 │
106
                             │ /usr/src/app/models/clip/visual.py:62 in _load  │
107
                             │                                                 │
108
                             │   59 │   │   self.mean = np.array(self.preproce │
109
                             │   60 │   │   self.std = np.array(self.preproces │
110
                             │   61 │   │                                      │
111
                             │ ❱ 62 │   │   return super()._load()             │
112
                             │   63 │                                          │
113
                             │   64 │   def transform(self, image: Image.Image │
114
                             │   65 │   │   image = resize_pil(image, self.siz │
115
                             │                                                 │
116
                             │ /usr/src/app/models/base.py:79 in _load         │
117
                             │                                                 │
118
                             │    76 │   │   )                                 │
119
                             │    77 │                                         │
120
                             │    78 │   def _load(self) -> ModelSession:      │
121
                             │ ❱  79 │   │   return self._make_session(self.mo │
122
                             │    80 │                                         │
123
                             │    81 │   def clear_cache(self) -> None:        │
124
                             │    82 │   │   if not self.cache_dir.exists():   │
125
                             │                                                 │
126
                             │ /usr/src/app/models/base.py:111 in              │
127
                             │ _make_session                                   │
128
                             │                                                 │
129
                             │   108 │   │   │   case ".armnn":                │
130
                             │   109 │   │   │   │   session: ModelSession = A │
131
                             │   110 │   │   │   case ".onnx":                 │
132
                             │ ❱ 111 │   │   │   │   session = OrtSession(mode │
133
                             │   112 │   │   │   case _:                       │
134
                             │   113 │   │   │   │   raise ValueError(f"Unsupp │
135
                             │   114 │   │   return session                    │
136
                             │                                                 │
137
                             │ /usr/src/app/sessions/ort.py:28 in __init__     │
138
                             │                                                 │
139
                             │    25 │   │   self.providers = providers if pro │
140
                             │    26 │   │   self.provider_options = provider_ │
141
                             │       self._provider_options_default            │
142
                             │    27 │   │   self.sess_options = sess_options  │
143
                             │       self._sess_options_default                │
144
                             │ ❱  28 │   │   self.session = ort.InferenceSessi │
145
                             │    29 │   │   │   self.model_path.as_posix(),   │
146
                             │    30 │   │   │   providers=self.providers,     │
147
                             │    31 │   │   │   provider_options=self.provide │
148
                             │                                                 │
149
                             │ /opt/venv/lib/python3.11/site-packages/onnxrunt │
150
                             │ ime/capi/onnxruntime_inference_collection.py:43 │
151
                             │ 2 in __init__                                   │
152
                             │                                                 │
153
                             │    429 │   │   │   │   │   self.disable_fallbac │
154
                             │    430 │   │   │   │   │   return               │
155
                             │    431 │   │   │   │   except Exception as fall │
156
                             │ ❱  432 │   │   │   │   │   raise fallback_error │
157
                             │    433 │   │   │   # Fallback is disabled. Rais │
158
                             │    434 │   │   │   raise e                      │
159
                             │    435                                          │
160
                             │                                                 │
161
                             │ /opt/venv/lib/python3.11/site-packages/onnxrunt │
162
                             │ ime/capi/onnxruntime_inference_collection.py:42 │
163
                             │ 7 in __init__                                   │
164
                             │                                                 │
165
                             │    424 │   │   │   │   │   print(f"EP Error {e} │
166
                             │    425 │   │   │   │   │   print(f"Falling back │
167
                             │    426 │   │   │   │   │   print("************* │
168
                             │ ❱  427 │   │   │   │   │   self._create_inferen │
169
                             │    428 │   │   │   │   │   # Fallback only once │
170
                             │    429 │   │   │   │   │   self.disable_fallbac │
171
                             │    430 │   │   │   │   │   return               │
172
                             │                                                 │
173
                             │ /opt/venv/lib/python3.11/site-packages/onnxrunt │
174
                             │ ime/capi/onnxruntime_inference_collection.py:48 │
175
                             │ 3 in _create_inference_session                  │
176
                             │                                                 │
177
                             │    480 │   │   │   disabled_optimizers = set(di │
178
                             │    481 │   │                                    │
179
                             │    482 │   │   # initialize the C++ InferenceSe │
180
                             │ ❱  483 │   │   sess.initialize_session(provider │
181
                             │    484 │   │                                    │
182
                             │    485 │   │   self._sess = sess                │
183
                             │    486 │   │   self._sess_options = self._sess. │
184
                             ╰─────────────────────────────────────────────────╯
185
                             RuntimeError:
186
                             /onnxruntime_src/onnxruntime/core/providers/cuda/cu
187
                             da_call.cc:123 std::conditional_t<THRW, void,
188
                             onnxruntime::common::Status>
189
                             onnxruntime::CudaCall(ERRTYPE, const char*, const
190
                             char*, ERRTYPE, const char*, const char*, int)
191
                             [with ERRTYPE = cudaError; bool THRW = true;
192
                             std::conditional_t<THRW, void, common::Status> =
193
                             void]
194
                             /onnxruntime_src/onnxruntime/core/providers/cuda/cu
195
                             da_call.cc:116 std::conditional_t<THRW, void,
196
                             onnxruntime::common::Status>
197
                             onnxruntime::CudaCall(ERRTYPE, const char*, const
198
                             char*, ERRTYPE, const char*, const char*, int)
199
                             [with ERRTYPE = cudaError; bool THRW = true;
200
                             std::conditional_t<THRW, void, common::Status> =
201
                             void] CUDA failure 100: no CUDA-capable device is
202
                             detected ; GPU=30355 ; hostname=f0cdef844009 ;
203
                             file=/onnxruntime_src/onnxruntime/core/providers/cu
204
                             da/cuda_execution_provider.cc ; line=280 ;
205
                             expr=cudaSetDevice(info_.device_id);
206

207

208
[08/18/24 10:37:48] INFO     Shutting down due to inactivity.
209
[08/18/24 10:37:48] INFO     Shutting down
210
[08/18/24 10:37:48] INFO     Waiting for application shutdown.
211
[08/18/24 10:37:49] INFO     Application shutdown complete.
212
[08/18/24 10:37:49] INFO     Finished server process [51638]
213
[08/18/24 10:37:49] ERROR    Worker (pid:51638) was sent SIGINT!
214
[08/18/24 10:37:49] INFO     Booting worker with pid: 56010
215
[08/18/24 10:37:53] INFO     Started server process [56010]
216
[08/18/24 10:37:53] INFO     Waiting for application startup.
217
[08/18/24 10:37:53] INFO     Created in-memory cache with unloading after 300s
218
                             of inactivity.
219
[08/18/24 10:37:53] INFO     Initialized request thread pool with 16 threads.
220
[08/18/24 10:37:53] INFO     Application startup complete.

根据报错可以发现：没有支持CUDA的设备，即容器的GPU支持配置有误
因此修改配置文件：

docker-compose.yml

1
# Configurations for hardware-accelerated transcoding
2

3
# If using Unraid or another platform that doesn't allow multiple Compose files,
4
# you can inline the config for a backend by copying its contents
5
# into the immich-microservices service in the docker-compose.yml file.
6

7
# See https://immich.app/docs/features/hardware-transcoding for more info on using hardware transcoding.
8

9
services:
10
  cpu: {}
11

12
  nvenc:
13
    deploy:
14
      resources:
15
        reservations:
16
          devices:
17
            - driver: nvidia
18
              count: 1
19
              capabilities:
20
                - gpu
21
                - compute
22
                - video
23

24
  quicksync:
25
    devices:
26
      - /dev/dri:/dev/dri
27

28
  rkmpp:
29
    security_opt: # enables full access to /sys and /proc, still far better than privileged: true
30
      - systempaths=unconfined
31
      - apparmor=unconfined
32
    group_add:
33
      - video
34
    devices:
35
      - /dev/rga:/dev/rga
36
      - /dev/dri:/dev/dri
37
      - /dev/dma_heap:/dev/dma_heap
38
      - /dev/mpp_service:/dev/mpp_service
39
      #- /dev/mali0:/dev/mali0 # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
40
    volumes:
41
      #- /etc/OpenCL:/etc/OpenCL:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
42
      #- /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
43

44
  vaapi:
45
    devices:
46
      - /dev/dri:/dev/dri
47

48
  vaapi-wsl: # use this for VAAPI if you're running Immich in WSL2
49
    devices:
50
      - /dev/dri:/dev/dri
51
    volumes:
52
      - /usr/lib/wsl:/usr/lib/wsl
53
    environment:
54
      - LD_LIBRARY_PATH=/usr/lib/wsl/lib
55
      - LIBVA_DRIVER_NAME=d3d12
56
root@ai-p100:/AppData/immich/immich-app# cat .env
57
# You can find documentation for all the supported env variables at https://immich.app/docs/install/environment-variables
58

59
# The location where your uploaded files are stored
60
UPLOAD_LOCATION=/AppData/immich/library
61
# The location where your database files are stored
62
DB_DATA_LOCATION=/AppData/immich/postgres
63

64
# To set a timezone, uncomment the next line and change Etc/UTC to a TZ identifier from this list: https://en.wikipedia.org/wiki/List_of_tz_database_time_zones#List
65
# TZ=Etc/UTC
66

67
# The Immich version to use. You can pin this to a specific version like "v1.71.0"
68
IMMICH_VERSION=release
69

70
# Connection secret for postgres. You should change it to a random password
71
# Please use only the characters `A-Za-z0-9`, without special characters or spaces
72
DB_PASSWORD=postgres
73

74
# The values below this line do not need to be changed
75
###################################################################################
76
DB_USERNAME=postgres
77
DB_DATABASE_NAME=immich
78
root@ai-p100:/AppData/immich/immich-app# cat docker-compose.yml
79
name: immich
80

81
services:
82
  immich-server:
83
    container_name: immich_server
84
    image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
85
    extends:
86
      file: hwaccel.transcoding.yml
87
      service: nvenc
88
    volumes:
89
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
90
      - /etc/localtime:/etc/localtime:ro
91
    env_file:
92
      - .env
93
    ports:
94
      - 2283:3001
95
    depends_on:
96
      - redis
97
      - database
98
    restart: always
99
    healthcheck:
100
      disable: false
101
    deploy:
102
      resources:
103
        reservations:
104
          devices:
105
            - driver: nvidia
106
              count: 1
107
              capabilities: [gpu, compute, video]
108

109
  immich-machine-learning:
110
    container_name: immich_machine_learning
111
    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}-cuda
112
    extends:
113
      file: hwaccel.ml.yml
114
      service: cuda
115
    volumes:
116
      - model-cache:/cache
117
    env_file:
118
      - .env
119
    restart: always
120
    healthcheck:
121
      disable: false
122
    deploy:
123
      resources:
124
        reservations:
125
          devices:
126
            - driver: nvidia
127
              count: 1
128
              capabilities: [gpu]
129

130
  redis:
131
    container_name: immich_redis
132
    image: docker.io/redis:6.2-alpine@sha256:e3b17ba9479deec4b7d1eeec1548a253acc5374d68d3b27937fcfe4df8d18c7e
133
    healthcheck:
134
      test: redis-cli ping || exit 1
135
    restart: always
136

137
  database:
138
    container_name: immich_postgres
139
    image: docker.io/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
140
    environment:
141
      POSTGRES_PASSWORD: ${DB_PASSWORD}
142
      POSTGRES_USER: ${DB_USERNAME}
143
      POSTGRES_DB: ${DB_DATABASE_NAME}
144
      POSTGRES_INITDB_ARGS: '--data-checksums'
145
    volumes:
146
      - ${DB_DATA_LOCATION}:/var/lib/postgresql/data
147
    healthcheck:
148
      test: pg_isready --dbname='${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"; [ "$$Chksum" = '0' ] || exit 1
149
      interval: 5m
150
      start_interval: 30s
151
      start_period: 5m
152
    command: ["postgres", "-c", "shared_preload_libraries=vectors.so", "-c", 'search_path="$$user", public, vectors', "-c", "logging_collector=on", "-c", "max_wal_size=2GB", "-c", "shared_buffers=512MB", "-c", "wal_compression=on"]
153
    restart: always
154

155
volumes:
156
  model-cache:

其中区别就是：添加了以下字段：

1
    deploy:
2
      resources:
3
        reservations:
4
          devices:
5
            - driver: nvidia
6
              count: 1
7
              capabilities: [gpu]

具体配置#

首先是照片上传，移动端几乎全平台支持，直接下载App然后授权访问相册就可以了
PC稍微麻烦些，需要安装node.js后安装immich-cli，具体请查阅文档
immich-cli需要node.js版本在20.0以上，所以如果发行版的软件源较为老旧，请换更新的nodesource源