In today’s rapidly advancing world of intelligent applications, image and video management is evolving at an unprecedented pace.
Imagine capturing breathtaking travel landscapes or precious moments of your child’s growth — and having your photos automatically categorized, tagged, and searchable via natural language. All processing happens locally, with no dependence on cloud servers, ensuring both speed and privacy. With the powerhouse performance of the M5Stack LLM‑8850 Card, bring your vision to life with an intelligent, deeply personalized photo album that’s uniquely yours.
M5Stack LLM‑8850 Card is an M.2 M‑Key 2242 AI accelerator card designed for edge devices. It is a powerful yet energy-efficient AI edge computing module, purpose-built for multi-modal large models, on-device inference, and intelligent analysis. It delivers high-performance inference for both language and vision models, and can be deployed effortlessly across diverse devices to enable offline, private AI services.
In this article, we’ll show you how to build an intelligent photo management platform with M5Stack LLM-8850 Card, making the organization of your pictures and videos smarter, faster, and more secure.
To achieve this, we’ll leverage Immich, an open‑source self‑hosted photo and video management platform that supports automatic backup, intelligent search, and cross‑device access.
Immich is an open-source self-hosted photo and video management platform that supports automatic backup, intelligent search, and cross-device access.
1. Manually download the program and upload it to raspberrypi5, or pull the model repository with the following command.
git clone https://huggingface.co/AXERA-TECH/immich
File Description:
m5stack@raspberrypi:~/rsp/immich $ ls -lh
total 421M
drwxrwxr-x 2 m5stack m5stack 4.0K Oct 10 09:12 asset
-rw-rw-r-- 1 m5stack m5stack 421M Oct 10 09:20 ax-immich-server-aarch64.tar.gz
-rw-rw-r-- 1 m5stack m5stack 0 Oct 10 09:12 config.json
-rw-rw-r-- 1 m5stack m5stack 7.6K Oct 10 09:12 docker-deploy.zip
-rw-rw-r-- 1 m5stack m5stack 104K Oct 10 09:12 immich_ml-1.129.0-py3-none-any.whl
-rw-rw-r-- 1 m5stack m5stack 9.4K Oct 10 09:12 README.md
-rw-rw-r-- 1 m5stack m5stack 177 Oct 10 09:12 requirements.txt
unzip docker-deploy.zip
cp example.env .env
4. Start the container
docker compose -f docker-compose.yml -f docker-compose.override.yml up -d
If started successfully, the information is as follows:
m5stack@raspberrypi:~/rsp/immich $ docker compose -f docker-compose.yml -f docker-compose.override.yml up -d
WARN[0000] /home/m5stack/rsp/immich/docker-compose.override.yml: the attribute `version` is obsolete, it will be ignored, please remove it to avoid potential confusion
[+] Running 3/3
✔ Container immich_postgres Started 1.0s
✔ Container immich_redis Started 0.9s
✔ Container immich_server Started 0.9s
(mich) m5stack@raspberrypi:~/rsp/immich $ python -m immich_ml
[10/10/25 09:50:12] INFO Starting gunicorn 23.0.0
[10/10/25 09:50:12] INFO Listening at: http://[::]:3003 (8698)
[10/10/25 09:50:12] INFO Using worker: immich_ml.config.CustomUvicornWorker
[10/10/25 09:50:12] INFO Booting worker with pid: 8699
2025-10-10 09:50:13.589360675 [W:onnxruntime:Default, device_discovery.cc:164 DiscoverDevicesForPlatform] GPU device discovery failed: device_discovery.cc:89 ReadFileContents Failed to open file: "/sys/class/drm/card1/device/vendor"
[INFO] Available providers: ['AXCLRTExecutionProvider']
/home/m5stack/rsp/immich/mich/lib/python3.11/site-packages/immich_ml/models/clip/cn_vocab.txt
[10/10/25 09:50:16] INFO Started server process [8699]
[10/10/25 09:50:16] INFO Waiting for application startup.
[10/10/25 09:50:16] INFO Created in-memory cache with unloading after 300s
of inactivity.
[10/10/25 09:50:16] INFO Initialized request thread pool with 4 threads.
[10/10/25 09:50:16] INFO Application startup complete.
In your browser, enter the Raspberry Pi IP address and port 3003, for example: 192.168.20.27:3003
Note: The first visit requires registering an administrator account; the account and password are saved locally.
Once configured, you can upload images.
The first time, you need to configure the machine learning server. Refer to the diagram below to enter the configuration.
Set the URL to the Raspberry Pi IP address and port 3003, e.g., 192.168.20.27:3003.
If using Chinese search for the CLIP model, set it to ViT-L-14-336-CN__axera; for English search, set it to ViT-L-14-336__axera.
After setup, save the configuration.
The first time, you need to manually go to the Jobs tab and trigger SMART SEARCH.
Enter the description of the image in the search bar to retrieve relevant images.
Through this hands-on project, we’ve not only built a powerful smart photo album platform, but also experienced the exceptional performance of the M5Stack LLM‑8850 Card in edge AI computing. Whether setting up a private photo album on your Raspberry Pi or deploying intelligent image processing in security scenarios, the M5Stack LLM‑8850 Card delivers efficient, stable computing power you can rely on.
It brings AI closer to where your data resides, enabling faster, more secure processing and turning your ideas into reality. If you’re looking for a solution for on-device AI inference, give M5Stack LLM‑8850 Card a try — it might just become the core engine of your next project.