From 4d590f48cd0a4d175a334e176cfe2aebc1a5c22a Mon Sep 17 00:00:00 2001
From: martabal <74269598+martabal@users.noreply.github.com>
Date: Thu, 23 May 2024 17:54:33 +0200
Subject: [PATCH] update README
---
README.md | 124 ++++++++++++++++++++++++++++++++++--------------------
1 file changed, 78 insertions(+), 46 deletions(-)
diff --git a/README.md b/README.md
index 4e3f076..39ebad5 100644
--- a/README.md
+++ b/README.md
@@ -47,49 +47,79 @@ To use a SSL connection to your PostgreSQL database, include a PostgreSQL URL in
To use Intel Quicksync hardware acceleration:
-1. Ensure your container has access to the `/dev/dri` video device.
-2. Add the device to your container by including the following option in your Docker run command:
+- Ensure your container has access to the `/dev/dri` video device.
-```bash
-docker run --device=/dev/dri:/dev/dri ...
-```
+- Add the device to your container by including the following option in your Docker run command:
+
+ - Docker run:
+
+ ```bash
+ docker run --device=/dev/dri:/dev/dri ...
+ ```
+
+ - Docker compose:
+
+ ```yaml
+ services:
+ immich:
+ image: ghcr.io/martabal/immich:latest
+ ...
+ devices:
+ - "/dev/dri:/dev/dri"
+ ```
### Nvidia - NVENC/VAAPI
To use Nvidia hardware acceleration:
-1. First, install the Nvidia container runtime on your host machine. Follow the [installation instructions here]( nvidia-docker).
+- First, install the Nvidia container runtime on your host machine. Follow the [installation instructions here]( nvidia-docker).
-2. After installing `nvidia-docker2`, recreate or create a new Docker container using the Nvidia runtime. This can be done in two ways:
+- After installing `nvidia-docker2`, recreate or create a new Docker container using the Nvidia runtime. This can be done in two ways:
- Add both `--runtime=nvidia` and `NVIDIA_VISIBLE_DEVICES=all` to your Docker run command. Replace `all` with a specific GPU's UUID if needed. Example:
-```bash
-docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all
-```
+ - Docker run:
+
+ ```bash
+ docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all
+ ```
+
+ - Docker compose:
+
+ ```yaml
+ services:
+ immich:
+ image: ghcr.io/martabal/immich:latest
+ ...
+ runtime: nvidia
+ environment:
+ - NVIDIA_VISIBLE_DEVICES=all
+ ```
- Alternatively, use `--gpus=all` in your Docker run command. Example:
-```bash
-docker run --gpus=all ...
-```
+ - Docker run:
-or
+ ```bash
+ docker run --gpus=all ...
+ ```
-```yaml
-services:
- immich:
- image: ghcr.io/martabal/immich:latest
- ...
- deploy:
- resources:
- reservations:
- devices:
- - driver: nvidia
- count: 1
- capabilities:
- - gpu
-```
+ - Docker compose:
+
+ ```yaml
+ services:
+ immich:
+ image: ghcr.io/martabal/immich:latest
+ ...
+ deploy:
+ resources:
+ reservations:
+ devices:
+ - driver: nvidia
+ count: 1
+ capabilities:
+ - gpu
+ ```
### Machine-learning acceleration
@@ -97,29 +127,31 @@ services:
To use OpenVINO:
-1. Make sure your [CPU supports OpenVINO](https://docs.openvino.ai/2024/about-openvino/system-requirements.html)
+- Make sure your [CPU supports OpenVINO](https://docs.openvino.ai/2024/about-openvino/system-requirements.html)
-2. Add a new path `-p /dev/bus/usb:/dev/bus/usb` and add `--device=/dev/dri --device-cgroup-rule='c 189:* rmw'` in your Docker run command. Example:
+- Add a new path `-p /dev/bus/usb:/dev/bus/usb` and add `--device=/dev/dri --device-cgroup-rule='c 189:* rmw'` in your Docker run command. Example:
-```bash
-docker run --device=/dev/dri --device-cgroup-rule='c 189:* rmw' -p /dev/bus/usb:/dev/bus/usb ...
-```
+ - Docker run:
-or
+ ```bash
+ docker run --device=/dev/dri --device-cgroup-rule='c 189:* rmw' -p /dev/bus/usb:/dev/bus/usb ...
+ ```
-```yaml
-services:
- immich:
- image: ghcr.io/martabal/immich:latest
- ...
- device_cgroup_rules:
- - 'c 189:* rmw'
- devices:
- - /dev/dri:/dev/dri
- volumes:
+ - Docker compose:
+
+ ```yaml
+ services:
+ immich:
+ image: ghcr.io/martabal/immich:latest
...
- - /dev/bus/usb:/dev/bus/usb
-```
+ device_cgroup_rules:
+ - 'c 189:* rmw'
+ devices:
+ - /dev/dri:/dev/dri
+ volumes:
+ ...
+ - /dev/bus/usb:/dev/bus/usb
+ ```
#### Nvidia - CUDA