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SAM

Facebook's Segment Anything (SAM) are pretrained models that perform image segmentation on RGB images and can aid the human in the annotation process.

Prerequisites#

Linux#

  • docker
  • redis-server (sudo apt install redis-server)

Windows#

  • WSL2 using 22.04.x

    • docker (instructions)
    • redis-server (sudo apt install redis-server)

Directories#

sam
|
+-- cache    # cache directory for Pytorch-related files 
|
+-- models   # for storing the SAM models

You can create the structure using the following command:

mkdir -p sam/cache \
mkdir -p sam/models

Pretrained models#

Pretrained models can be downloaded from here, with the medium-sized vit_l being the recommended one (requires <6GB GPU RAM). vit_l is used in the commands below.

From within the sam/models directory, run the following command:

wget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_l_0b3195.pth

Service scripts (WSL2 without Docker Desktop UI)#

  • Create a bash script happy_sam_start.sh in /usr/local/bin with the following content:
#!/bin/bash
redis-server &
dockerd &
seq 10 | xargs -I{} sh -c "echo waiting...; sleep 1;"

  • Make the script executable with sudo chmod a+x happy_sam_start.sh

  • Create a bash script happy_sam_stop.sh in /usr/local/bin with the following content:

#!/bin/bash
killall redis-server
killall dockerd
  • Make the script executable with sudo chmod a+x happy_sam_stop.sh

SAM scripts#

In the sam directory, create script start.sh with the following content:

#!/bin/bash

scriptdir=`dirname -- "$0";`

docker run --pull always --rm \
  -u $(id -u):$(id -g) -e USER=$USER \
  -v $scriptdir/cache:/.cache \
  -v $scriptdir:/workspace \
  --gpus=all --net=host \
  -t waikatodatamining/pytorch-sam:2023-04-16_cuda11.6 \
  sam_predict_redis \
  --redis_in sam_in \
  --redis_out sam_out \
  --model /workspace/models/sam_vit_l_0b3195.pth \
  --model_type vit_l \
  --verbose

And make executable with chmod a+x start.sh.

Next, create a script called stop.sh with the following content:

#!/bin/bash

ids=`ps a | grep [s]am_predict_redis | sed s/"^[ ]*"//g | cut -f1 -d" "`
for id in $ids
do
  kill -9 $id
done

And make executable with chmod a+x stop.sh.

Starting#

Docker and Redis (WSL2 without Docker Desktop UI)#

sudo /usr/local/bin/happy_sam_start.sh

Wait till the Waiting... output stops, which waits for about 10 seconds after the Docker daemon starts in the background.

SAM#

In the sam directory, execute the start.sh script.

Stopping#

SAM#

In the sam directory, execute the stop.sh script.

Docker and Redis (WSL2 without Docker Desktop UI)#

sudo /usr/local/bin/happy_sam_stop.sh

NB: This will also stop any running SAM/SAM-HQ process.