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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:

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

  2. Running one of the following JetPack.5x

    JetPack 5.1.2 (L4T r35.4.1) JetPack 5.1.1 (L4T r35.3.1) JetPack 5.1 (L4T r35.2.1)

  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.