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Tutorial - NanoDB

Let's run NanoDB's interactive demo to witness the impact of Vector Database that handles multimodal data.

What you need

  1. One of the following Jetson devices:

    Jetson AGX Orin (64GB) Jetson AGX Orin (32GB) Jetson Orin NX (16GB)

  2. Running one of the following versions of JetPack:

    JetPack 5 (L4T r35.x) JetPack 6 (L4T r36.x)

  3. Sufficient storage space (preferably with NVMe SSD).

    • 7.0GB for container image

Set up a container for nanodb

Clone jetson-containers

See jetson-containers' nanodb package README for more infomation**

git clone
cd jetson-containers
sudo apt update; sudo apt install -y python3-pip
pip3 install -r requirements.txt

How to start

Download your data

Just for an example, let's just use MS COCO dataset.

cd jetson-containers
mkdir data/datasets/coco/
cd data/datasets/coco

Indexing Data

First, we need to build the index by scanning your dataset directory.

cd jetson-containers
./ -v ${PWD}/data/datasets/coco:/my_dataset $(./autotag nanodb) \
  python3 -m nanodb \
    --scan /my_dataset \
    --path /my_dataset/nanodb \
    --autosave --validate 

This will take about 2 hours.

Once the database has loaded and completed any start-up operations , it will drop down to a > prompt from which the user can run search queries.
You can quickly check the operation by typing your query on this prompt.

> a girl riding a horse

* index=80110   /data/datasets/coco/2017/train2017/000000393735.jpg      similarity=0.29991915822029114
* index=158747  /data/datasets/coco/2017/unlabeled2017/000000189708.jpg  similarity=0.29254037141799927
* index=123846  /data/datasets/coco/2017/unlabeled2017/000000026239.jpg  similarity=0.292171448469162
* index=127338  /data/datasets/coco/2017/unlabeled2017/000000042508.jpg  similarity=0.29118549823760986
* index=77416   /data/datasets/coco/2017/train2017/000000380634.jpg      similarity=0.28964102268218994
* index=51992   /data/datasets/coco/2017/train2017/000000256290.jpg      similarity=0.28929752111434937
* index=228640  /data/datasets/coco/2017/unlabeled2017/000000520381.jpg  similarity=0.28642547130584717
* index=104819  /data/datasets/coco/2017/train2017/000000515895.jpg      similarity=0.285491943359375

You can press Ctrl+C to exit from the app and the container.

Interactive web UI

Spin up the Gradio server.

cd jetson-containers
./ -v ${PWD}/data/datasets/coco:/my_dataset $(./autotag nanodb) \
  python3 -m nanodb \
    --path /my_dataset/nanodb \
    --server --port=7860

You can use your PC (or any machine) that can access your Jetson via a network, and navigate your browser to http://<IP_ADDRESS>:7860

You can enter text search queries as well as drag/upload images.