Add docker-compose scripts for more convenient usage with prebuilt images

docker-compose.yml

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+version: '2.3'
+services:
+    jetson-inference:
+        stdin_open: true # docker run -i
+        tty: true        # docker run -t
+        network_mode: host
+        runtime: nvidia
+        environment:
+            - DISPLAY=${DISPLAY}
+        volumes:
+            - '/tmp/.X11-unix/:/tmp/.X11-unix'
+            - '/tmp/argus_socket:/tmp/argus_socket'
+            - '/etc/enctune.conf:/etc/enctune.conf'
+            - '${PWD}/data:/jetson-inference/data'
+            - '${PWD}/python/training/classification/data:/jetson-inference/python/training/classification/data'
+            - '${PWD}/python/training/classification/models:/jetson-inference/python/training/classification/models'
+            - '${PWD}/python/training/detection/ssd/data:/jetson-inference/python/training/detection/ssd/data'
+            - '${PWD}/python/training/detection/ssd/models:/jetson-inference/python/training/detection/ssd/models'
+            - '${PWD}/python/training/detection/ssd/code:/jetson-inference/python/training/detection/ssd/code'
+        devices:
+            - /dev/video0
+            - /dev/ttyUSB0
+        image: 'dustynv/jetson-inference:r32.6.1'

docker/compose-bootstrap.sh

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+#!/usr/bin/env bash
+#
+# Start an instance of the jetson-inference docker container.
+# See below or run this script with -h or --help to see usage options.
+#
+# This script should be run from the root dir of the jetson-inference project:
+#
+#     $ cd /path/to/your/jetson-inference
+#     $ docker/run.sh
+#
+
+show_help() {
+    echo " "
+    echo "usage: Bootstrap the enironment required for running docker-compose"
+    echo " "
+    echo "   ./docker/compose-bootstrap.sh"
+    echo " "
+    echo "After this, edit docker-compose.yml for correct parameters, and then run ./docker/docker-compose up -d to launch container"
+    echo " "
+    echo "args:"
+    echo " "
+    echo "   --help                       Show this help text and quit"
+    echo " "
+}
+
+die() {
+    printf '%s\n' "$1"
+    show_help
+    exit 1
+}
+
+if [[ -x "$PWD/docker/docker-compose" ]]; then
+    echo "Latest docker-compose configured already, skipping download."
+else
+    echo "Installing latest docker-compose to ./docker/docker-compose. Assuming that curl is installed."
+    # Prevent conflict with local docker-compose installation by maintaing our own binary. It is simple since it is Go static-linked binary anyway.
+    curl -L "https://github.com/docker/compose/releases/download/v2.1.1/docker-compose-$(uname -s)-$(uname -m)" -o $PWD/docker/docker-compose
+    chmod +x $PWD/docker/docker-compose
+fi
+
+# find container tag from L4T version
+source docker/tag.sh
+
+# paths to some project directories
+NETWORKS_DIR="data/networks"
+CLASSIFY_DIR="python/training/classification"
+DETECTION_DIR="python/training/detection/ssd"
+
+DOCKER_ROOT="/jetson-inference"	# where the project resides inside docker
+
+# check if we need to download models
+SIZE_MODELS=$(du -sb $NETWORKS_DIR | cut -f 1)  
+
+echo "size of $NETWORKS_DIR:  $SIZE_MODELS bytes"
+
+if [[ $SIZE_MODELS -lt 204800 ]]; then  # some text files come with the repo (~78KB), so check for a bit more than that
+	sudo apt-get update
+	sudo apt-get install dialog
+	echo "Models have not yet been downloaded, running model downloader tool now..."
+	cd tools
+	./download-models.sh
+	cd ../
+fi
+
+# check for pytorch-ssd base model
+SSD_BASE_MODEL="$DETECTION_DIR/models/mobilenet-v1-ssd-mp-0_675.pth"
+
+if [ ! -f "$SSD_BASE_MODEL" ]; then
+	echo "Downloading pytorch-ssd base model..."
+	wget --quiet --show-progress --progress=bar:force:noscroll --no-check-certificate https://nvidia.box.com/shared/static/djf5w54rjvpqocsiztzaandq1m3avr7c.pth -O $SSD_BASE_MODEL
+fi
+
+mkdir -p $PWD/$DETECTION_DIR/code
+
+# generate mount commands
+DATA_VOLUME="\
+--volume $PWD/data:$DOCKER_ROOT/data \
+--volume $PWD/$CLASSIFY_DIR/data:$DOCKER_ROOT/$CLASSIFY_DIR/data \
+--volume $PWD/$CLASSIFY_DIR/models:$DOCKER_ROOT/$CLASSIFY_DIR/models \
+--volume $PWD/$DETECTION_DIR/data:$DOCKER_ROOT/$DETECTION_DIR/data \
+--volume $PWD/$DETECTION_DIR/models:$DOCKER_ROOT/$DETECTION_DIR/models \
+--volume $PWD/$DETECTION_DIR/code:$DOCKER_ROOT/$DETECTION_DIR/code"
+
+echo "DATA_VOLUME: $DATA_VOLUME"
+
+while :; do
+    case $1 in
+        -h|-\?|--help)
+            show_help    # Display a usage synopsis.
+            exit
+            ;;
+        --)              # End of all options.
+            shift
+            break
+            ;;
+        -?*)
+            printf 'WARN: Unknown option (ignored): %s\n' "$1" >&2
+            ;;
+        *)               # Default case: No more options, so break out of the loop.
+            break
+    esac
+
+    shift
+done
+
+echo "CONTAINER:     $CONTAINER_IMAGE"
+
+# check for V4L2 devices
+V4L2_DEVICES=" "
+
+for i in {0..9}
+do
+	if [ -a "/dev/video$i" ]; then
+		V4L2_DEVICES="$V4L2_DEVICES --device /dev/video$i "
+	fi
+done
+
+echo "V4L2_DEVICES:  $V4L2_DEVICES"
+
+# check for TTY devices to provide Arduino passthrough support
+TTY_DEVICES=" "
+
+for i in {0..9}
+do
+	if [ -a "/dev/ttyUSB$i" ]; then
+		TTY_DEVICES="$TTY_DEVICES --device /dev/ttyUSB$i "
+	fi
+done
+
+for i in {0..9}
+do
+	if [ -a "/dev/ttyACM$i" ]; then
+		TTY_DEVICES="$TTY_DEVICES --device /dev/ttyACM$i "
+	fi
+done
+
+echo "TTY_DEVICES:  $TTY_DEVICES"
+
+# run the container
+sudo xhost +si:localuser:root
+
+echo "Please make sure compose file is using $CONTAINER_IMAGE"
+

docker/compose-shell.sh

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+sudo -E ./docker/docker-compose exec -e TERM=${TERM} jetson-inference /bin/bash

docker/compose-up.sh

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+sudo -E ./docker/docker-compose up -d