Tutorial - SAM (Segment Anything)
Let's run Meta's SAM
on NVIDIA Jetson.
What you need
-
One of the following Jetson:
Jetson AGX Orin 64GB Jetson AGX Orin (32GB) Jetson Orin Nano Orin (8GB)⚠️1
-
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)
-
Sufficient storage space (preferably with NVMe SSD).
6.8GB
for container image- Spaces for models
Set up a container for sam
Clone jetson-containers
See jetson-containers
' sam
package README for more infomation**
git clone https://github.com/dusty-nv/jetson-containers
cd jetson-containers
sudo apt update; sudo apt install -y python3-pip
pip3 install -r requirements.txt
How to start
Use run.sh
and autotag
script to automatically pull or build a compatible container image.
cd jetson-containers
./run.sh $(./autotag sam)
The container has a default run command (CMD
) that will automatically start the Jupyter Lab server.
Open your browser and access http://<IP_ADDRESS>:8888
.
The default password for Jupyter Lab is
nvidia
.
Run Jupyter notebook
In Jupyter Lab, navigate to notebooks
and open automatic_mask_generator_example.py
notebook.
Create a new cell at the top, insert the model download command below and run the cell.
!wget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth
Then go through executing all the cells below Set-up.
Results
-
The biggest
vit_h
(2.4GB) model may not ran due to OOM, butvit_l
(1.1GB) runs on Jetson Orin Nano. ↩