Update demo .sh scripts (#6078)
* Remove sudo package installation from demo scripts * Change the build_dir path (benchmark_app.sh, squeezenet_download_convert_run) * Remove redundant pip_binary * Revert 'inference_engine_samples_build' as the build folder for .bat * Add check for python 3.8 * Update help messages * Use `model-optimizer/requirements.txt` instead of `install_prerequisites.sh` * Add `--user` for python package installation (demo_security_barrier_camera.sh) * Add python venv creation * Create venv in $HOME instead of $ROOT_DIR * Make the step messages look the same as in the .bat scripts * Make the same changes to demo_benchmark_app.sh as in other .sh scripts * Remove a mention of FPGA from a help message * Set venv folder to `venv_openvino`
This commit is contained in:
Dmitry Pigasin
GitHub
parent
8a31e8aafb
commit
860896c4bb
@ -3,14 +3,21 @@
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# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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echo -ne "\e[0;33mWARNING: If you get an error when running the demo in the Docker container, you may need to install additional packages. To do this, run the container as root (-u 0) and run install_openvino_dependencies.sh script. If you get a package-independent error, try setting additional parameters using -sample-options.\e[0m\n"
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ROOT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]-$0}" )" && pwd )"
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VENV_DIR="$HOME/venv_openvino"
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. "$ROOT_DIR/utils.sh"
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usage() {
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echo "Benchmark demo using public SqueezeNet topology"
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echo "-d name specify the target device to infer on; CPU, GPU, FPGA, HDDL or MYRIAD are acceptable. Sample will look for a suitable plugin for device specified"
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echo "-help print help message"
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echo
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echo "Options:"
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echo " -help Print help message"
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echo " -d DEVICE Specify the target device to infer on; CPU, GPU, HDDL or MYRIAD are acceptable. Sample will look for a suitable plugin for device specified"
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echo " -sample-options OPTIONS Specify command line arguments for the sample"
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echo
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exit 1
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}
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@ -50,7 +57,7 @@ fi
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target_precision="FP16"
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printf "target_precision = %s\n" ${target_precision}
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echo -ne "target_precision = ${target_precision}\n"
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models_path="$HOME/openvino_models/models"
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models_cache="$HOME/openvino_models/cache"
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@ -61,13 +68,11 @@ model_name="squeezenet1.1"
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target_image_path="$ROOT_DIR/car.png"
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run_again="Then run the script again\n\n"
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dashes="\n\n###################################################\n\n"
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if [ -e "$ROOT_DIR/../../bin/setupvars.sh" ]; then
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setupvars_path="$ROOT_DIR/../../bin/setupvars.sh"
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else
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printf "Error: setupvars.sh is not found\n"
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echo -ne "Error: setupvars.sh is not found\n"
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fi
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if ! . "$setupvars_path" ; then
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@ -75,14 +80,6 @@ if ! . "$setupvars_path" ; then
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exit 1
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fi
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# Step 1. Download the Caffe model and the prototxt of the model
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echo -ne "${dashes}"
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printf "\n\nDownloading the Caffe model and the prototxt"
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cur_path=$PWD
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printf "\nInstalling dependencies\n"
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if [[ -f /etc/centos-release ]]; then
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DISTRO="centos"
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elif [[ -f /etc/lsb-release ]]; then
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@ -90,55 +87,27 @@ elif [[ -f /etc/lsb-release ]]; then
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fi
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if [[ $DISTRO == "centos" ]]; then
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sudo -E yum install -y centos-release-scl epel-release
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sudo -E yum install -y gcc gcc-c++ make glibc-static glibc-devel libstdc++-static libstdc++-devel libstdc++ libgcc \
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glibc-static.i686 glibc-devel.i686 libstdc++-static.i686 libstdc++.i686 libgcc.i686 cmake
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sudo -E rpm -Uvh http://li.nux.ro/download/nux/dextop/el7/x86_64/nux-dextop-release-0-1.el7.nux.noarch.rpm || true
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sudo -E yum install -y epel-release
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sudo -E yum install -y cmake ffmpeg gstreamer1 gstreamer1-plugins-base libusbx-devel
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# check installed Python version
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if command -v python3.5 >/dev/null 2>&1; then
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python_binary=python3.5
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pip_binary=pip3.5
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fi
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if command -v python3.6 >/dev/null 2>&1; then
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python_binary=python3.6
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pip_binary=pip3.6
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fi
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if [ -z "$python_binary" ]; then
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sudo -E yum install -y rh-python36 || true
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. scl_source enable rh-python36
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python_binary=python3.6
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pip_binary=pip3.6
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fi
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elif [[ $DISTRO == "ubuntu" ]]; then
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sudo -E apt update
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print_and_run sudo -E apt -y install build-essential python3-pip virtualenv cmake libcairo2-dev libpango1.0-dev libglib2.0-dev libgtk2.0-dev libswscale-dev libavcodec-dev libavformat-dev libgstreamer1.0-0 gstreamer1.0-plugins-base
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python_binary=python3
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pip_binary=pip3
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system_ver=$(grep -i "DISTRIB_RELEASE" -f /etc/lsb-release | cut -d "=" -f2)
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if [ "$system_ver" = "16.04" ]; then
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sudo -E apt-get install -y libpng12-dev
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else
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sudo -E apt-get install -y libpng-dev
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fi
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elif [[ "$OSTYPE" == "darwin"* ]]; then
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# check installed Python version
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if command -v python3.7 >/dev/null 2>&1; then
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if command -v python3.8 >/dev/null 2>&1; then
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python_binary=python3.8
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elif command -v python3.7 >/dev/null 2>&1; then
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python_binary=python3.7
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pip_binary=pip3.7
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elif command -v python3.6 >/dev/null 2>&1; then
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python_binary=python3.6
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pip_binary=pip3.6
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elif command -v python3.5 >/dev/null 2>&1; then
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python_binary=python3.5
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pip_binary=pip3.5
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else
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python_binary=python3
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pip_binary=pip3
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fi
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fi
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@ -147,47 +116,52 @@ if ! command -v $python_binary &>/dev/null; then
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exit 1
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fi
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if [[ "$OSTYPE" == "darwin"* ]]; then
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$pip_binary install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
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if [ -e "$VENV_DIR" ]; then
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echo -ne "\n###############|| Using the existing python virtual environment ||###############\n\n"
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else
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sudo -E "$pip_binary" install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
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echo -ne "\n###############|| Creating the python virtual environment ||###############\n\n"
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"$python_binary" -m venv "$VENV_DIR"
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fi
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. "$VENV_DIR/bin/activate"
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python -m pip install -U pip
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python -m pip install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
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# Step 1. Download the Caffe model and the prototxt of the model
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echo -ne "\n###############|| Downloading the Caffe model and the prototxt ||###############\n\n"
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downloader_dir="${INTEL_OPENVINO_DIR}/deployment_tools/open_model_zoo/tools/downloader"
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model_dir=$("$python_binary" "$downloader_dir/info_dumper.py" --name "$model_name" |
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"$python_binary" -c 'import sys, json; print(json.load(sys.stdin)[0]["subdirectory"])')
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model_dir=$(python "$downloader_dir/info_dumper.py" --name "$model_name" |
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python -c 'import sys, json; print(json.load(sys.stdin)[0]["subdirectory"])')
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downloader_path="$downloader_dir/downloader.py"
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print_and_run "$python_binary" "$downloader_path" --name "$model_name" --output_dir "${models_path}" --cache_dir "${models_cache}"
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print_and_run python "$downloader_path" --name "$model_name" --output_dir "${models_path}" --cache_dir "${models_cache}"
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ir_dir="${irs_path}/${model_dir}/${target_precision}"
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if [ ! -e "$ir_dir" ]; then
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# Step 2. Configure Model Optimizer
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echo -ne "${dashes}"
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printf "Install Model Optimizer dependencies\n\n"
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cd "${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/install_prerequisites"
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. ./install_prerequisites.sh caffe
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cd "$cur_path"
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echo -ne "\n###############|| Install Model Optimizer dependencies ||###############\n\n"
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cd "${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer"
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python -m pip install -r requirements.txt
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cd "$PWD"
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# Step 3. Convert a model with Model Optimizer
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echo -ne "${dashes}"
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printf "Convert a model with Model Optimizer\n\n"
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echo -ne "\n###############|| Convert a model with Model Optimizer ||###############\n\n"
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mo_path="${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/mo.py"
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export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=cpp
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print_and_run "$python_binary" "$downloader_dir/converter.py" --mo "$mo_path" --name "$model_name" -d "$models_path" -o "$irs_path" --precisions "$target_precision"
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print_and_run python "$downloader_dir/converter.py" --mo "$mo_path" --name "$model_name" -d "$models_path" -o "$irs_path" --precisions "$target_precision"
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else
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printf "\n\nTarget folder %s already exists. Skipping IR generation with Model Optimizer." "${ir_dir}"
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echo -ne "\n\nTarget folder ${ir_dir} already exists. Skipping IR generation with Model Optimizer."
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echo -ne "If you want to convert a model again, remove the entire ${ir_dir} folder. ${run_again}"
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fi
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# Step 4. Build samples
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echo -ne "${dashes}"
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printf "Build Inference Engine samples\n\n"
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echo -ne "\n###############|| Build Inference Engine samples ||###############\n\n"
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OS_PATH=$(uname -m)
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NUM_THREADS="-j2"
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@ -198,7 +172,7 @@ if [ "$OS_PATH" == "x86_64" ]; then
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fi
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samples_path="${INTEL_OPENVINO_DIR}/deployment_tools/inference_engine/samples/cpp"
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build_dir="$HOME/inference_engine_samples_build"
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build_dir="$HOME/inference_engine_cpp_samples_build"
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binaries_dir="${build_dir}/${OS_PATH}/Release"
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if [ -e "$build_dir/CMakeCache.txt" ]; then
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@ -211,8 +185,7 @@ cmake -DCMAKE_BUILD_TYPE=Release "$samples_path"
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make $NUM_THREADS benchmark_app
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# Step 5. Run samples
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echo -ne "${dashes}"
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printf "Run Inference Engine benchmark app\n\n"
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echo -ne "\n###############|| Run Inference Engine benchmark app ||###############\n\n"
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cd "$binaries_dir"
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@ -220,6 +193,4 @@ cp -f "$ROOT_DIR/${model_name}.labels" "${ir_dir}/"
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print_and_run ./benchmark_app -d "$target" -i "$target_image_path" -m "${ir_dir}/${model_name}.xml" -pc "${sampleoptions[@]}"
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echo -ne "${dashes}"
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printf "Inference Engine benchmark app completed successfully.\n\n"
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echo -ne "\n###############|| Inference Engine benchmark app completed successfully ||###############\n\n"
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@ -3,14 +3,21 @@
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# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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echo -ne "\e[0;33mWARNING: If you get an error when running the demo in the Docker container, you may need to install additional packages. To do this, run the container as root (-u 0) and run install_openvino_dependencies.sh script. If you get a package-independent error, try setting additional parameters using -sample-options.\e[0m\n"
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ROOT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]-$0}" )" && pwd )"
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VENV_DIR="$HOME/venv_openvino"
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. "$ROOT_DIR/utils.sh"
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usage() {
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echo "Security barrier camera demo that showcases three models coming with the product"
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echo "-d name specify the target device to infer on; CPU, GPU, FPGA, HDDL or MYRIAD are acceptable. Sample will look for a suitable plugin for device specified"
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echo "-help print help message"
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echo
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echo "Options:"
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echo " -help Print help message"
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echo " -d DEVICE Specify the target device to infer on; CPU, GPU, HDDL or MYRIAD are acceptable. Sample will look for a suitable plugin for device specified"
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echo " -sample-options OPTIONS Specify command line arguments for the sample"
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echo
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exit 1
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}
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@ -44,11 +51,19 @@ esac
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shift
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done
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target_image_path="$ROOT_DIR/car_1.bmp"
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run_again="Then run the script again\n\n"
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dashes="\n\n###################################################\n\n"
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if [ -e "$ROOT_DIR/../../bin/setupvars.sh" ]; then
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setupvars_path="$ROOT_DIR/../../bin/setupvars.sh"
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else
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echo -ne "Error: setupvars.sh is not found\n"
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fi
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if ! . "$setupvars_path" ; then
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echo -ne "Unable to run ./setupvars.sh. Please check its presence. ${run_again}"
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exit 1
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fi
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if [[ -f /etc/centos-release ]]; then
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DISTRO="centos"
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@ -59,55 +74,27 @@ elif [[ "$OSTYPE" == "darwin"* ]]; then
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fi
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if [[ $DISTRO == "centos" ]]; then
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sudo -E yum install -y centos-release-scl epel-release
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sudo -E yum install -y gcc gcc-c++ make glibc-static glibc-devel libstdc++-static libstdc++-devel libstdc++ libgcc \
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glibc-static.i686 glibc-devel.i686 libstdc++-static.i686 libstdc++.i686 libgcc.i686 cmake
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sudo -E rpm -Uvh http://li.nux.ro/download/nux/dextop/el7/x86_64/nux-dextop-release-0-1.el7.nux.noarch.rpm || true
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sudo -E yum install -y epel-release
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sudo -E yum install -y cmake ffmpeg gstreamer1 gstreamer1-plugins-base libusbx-devel
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# check installed Python version
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if command -v python3.5 >/dev/null 2>&1; then
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python_binary=python3.5
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pip_binary=pip3.5
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fi
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if command -v python3.6 >/dev/null 2>&1; then
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python_binary=python3.6
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pip_binary=pip3.6
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fi
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if [ -z "$python_binary" ]; then
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sudo -E yum install -y rh-python36 || true
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. scl_source enable rh-python36
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python_binary=python3.6
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pip_binary=pip3.6
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fi
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elif [[ $DISTRO == "ubuntu" ]]; then
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sudo -E apt update
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print_and_run sudo -E apt -y install build-essential python3-pip virtualenv cmake libcairo2-dev libpango1.0-dev libglib2.0-dev libgtk2.0-dev libswscale-dev libavcodec-dev libavformat-dev libgstreamer1.0-0 gstreamer1.0-plugins-base
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python_binary=python3
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pip_binary=pip3
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system_ver=$(grep -i "DISTRIB_RELEASE" -f /etc/lsb-release | cut -d "=" -f2)
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if [ "$system_ver" = "16.04" ]; then
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sudo -E apt-get install -y libpng12-dev
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else
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sudo -E apt-get install -y libpng-dev
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fi
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elif [[ "$OSTYPE" == "darwin"* ]]; then
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# check installed Python version
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if command -v python3.7 >/dev/null 2>&1; then
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if command -v python3.8 >/dev/null 2>&1; then
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python_binary=python3.8
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elif command -v python3.7 >/dev/null 2>&1; then
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python_binary=python3.7
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pip_binary=pip3.7
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elif command -v python3.6 >/dev/null 2>&1; then
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python_binary=python3.6
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pip_binary=pip3.6
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elif command -v python3.5 >/dev/null 2>&1; then
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python_binary=python3.5
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pip_binary=pip3.5
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else
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python_binary=python3
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pip_binary=pip3
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fi
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fi
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@ -116,30 +103,23 @@ if ! command -v $python_binary &>/dev/null; then
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exit 1
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fi
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if [[ $DISTRO == "macos" ]]; then
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"$pip_binary" install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
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if [ -e "$VENV_DIR" ]; then
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echo -ne "\n###############|| Using the existing python virtual environment ||###############\n\n"
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else
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sudo -E "$pip_binary" install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
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echo -ne "\n###############|| Creating the python virtual environment ||###############\n\n"
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"$python_binary" -m venv "$VENV_DIR"
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fi
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if [ -e "$ROOT_DIR/../../bin/setupvars.sh" ]; then
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setupvars_path="$ROOT_DIR/../../bin/setupvars.sh"
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else
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printf "Error: setupvars.sh is not found\n"
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fi
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if ! . "$setupvars_path" ; then
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echo -ne "Unable to run ./setupvars.sh. Please check its presence. ${run_again}"
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exit 1
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fi
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. "$VENV_DIR/bin/activate"
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python -m pip install -U pip
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python -m pip install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
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# Step 1. Downloading Intel models
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echo -ne "${dashes}"
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printf "Downloading Intel models\n\n"
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echo -ne "\n###############|| Downloading Intel models ||###############\n\n"
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target_precision="FP16"
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printf "target_precision = %s\n" "${target_precision}"
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echo -ne "target_precision = ${target_precision}\n"
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downloader_dir="${INTEL_OPENVINO_DIR}/deployment_tools/open_model_zoo/tools/downloader"
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@ -150,19 +130,18 @@ models_cache="$HOME/openvino_models/cache"
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declare -a model_args
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while read -r model_opt model_name; do
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model_subdir=$("$python_binary" "$downloader_dir/info_dumper.py" --name "$model_name" |
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"$python_binary" -c 'import sys, json; print(json.load(sys.stdin)[0]["subdirectory"])')
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model_subdir=$(python "$downloader_dir/info_dumper.py" --name "$model_name" |
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python -c 'import sys, json; print(json.load(sys.stdin)[0]["subdirectory"])')
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model_path="$models_path/$model_subdir/$target_precision/$model_name"
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print_and_run "$python_binary" "$downloader_path" --name "$model_name" --output_dir "$models_path" --cache_dir "$models_cache"
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print_and_run python "$downloader_path" --name "$model_name" --output_dir "$models_path" --cache_dir "$models_cache"
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|
||||
model_args+=("$model_opt" "${model_path}.xml")
|
||||
done < "$ROOT_DIR/demo_security_barrier_camera.conf"
|
||||
|
||||
# Step 2. Build samples
|
||||
echo -ne "${dashes}"
|
||||
printf "Build Inference Engine demos\n\n"
|
||||
echo -ne "\n###############|| Build Inference Engine demos ||###############\n\n"
|
||||
|
||||
demos_path="${INTEL_OPENVINO_DIR}/deployment_tools/open_model_zoo/demos"
|
||||
|
||||
@ -189,13 +168,11 @@ cmake -DCMAKE_BUILD_TYPE=Release "$demos_path"
|
||||
make $NUM_THREADS security_barrier_camera_demo
|
||||
|
||||
# Step 3. Run samples
|
||||
echo -ne "${dashes}"
|
||||
printf "Run Inference Engine security_barrier_camera demo\n\n"
|
||||
echo -ne "\n###############|| Run Inference Engine security_barrier_camera demo ||###############\n\n"
|
||||
|
||||
binaries_dir="${build_dir}/${OS_PATH}/Release"
|
||||
cd "$binaries_dir"
|
||||
|
||||
print_and_run ./security_barrier_camera_demo -d "$target" -d_va "$target" -d_lpr "$target" -i "$target_image_path" "${model_args[@]}" "${sampleoptions[@]}"
|
||||
|
||||
echo -ne "${dashes}"
|
||||
printf "Demo completed successfully.\n\n"
|
||||
echo -ne "\n###############|| Demo completed successfully ||###############\n\n"
|
||||
|
||||
@ -3,14 +3,21 @@
|
||||
# Copyright (C) 2018-2021 Intel Corporation
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
|
||||
echo -ne "\e[0;33mWARNING: If you get an error when running the demo in the Docker container, you may need to install additional packages. To do this, run the container as root (-u 0) and run install_openvino_dependencies.sh script. If you get a package-independent error, try setting additional parameters using -sample-options.\e[0m\n"
|
||||
|
||||
ROOT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]-$0}" )" && pwd )"
|
||||
VENV_DIR="$HOME/venv_openvino"
|
||||
|
||||
. "$ROOT_DIR/utils.sh"
|
||||
|
||||
usage() {
|
||||
echo "Classification demo using public SqueezeNet topology"
|
||||
echo "-d name specify the target device to infer on; CPU, GPU, FPGA, HDDL or MYRIAD are acceptable. Sample will look for a suitable plugin for device specified"
|
||||
echo "-help print help message"
|
||||
echo
|
||||
echo "Options:"
|
||||
echo " -help Print help message"
|
||||
echo " -d DEVICE Specify the target device to infer on; CPU, GPU, HDDL or MYRIAD are acceptable. Sample will look for a suitable plugin for device specified"
|
||||
echo " -sample-options OPTIONS Specify command line arguments for the sample"
|
||||
echo
|
||||
exit 1
|
||||
}
|
||||
|
||||
@ -46,7 +53,7 @@ done
|
||||
|
||||
target_precision="FP16"
|
||||
|
||||
printf "target_precision = %s\n" "${target_precision}"
|
||||
echo -ne "target_precision = ${target_precision}\n"
|
||||
|
||||
models_path="$HOME/openvino_models/models"
|
||||
models_cache="$HOME/openvino_models/cache"
|
||||
@ -57,13 +64,11 @@ model_name="squeezenet1.1"
|
||||
target_image_path="$ROOT_DIR/car.png"
|
||||
|
||||
run_again="Then run the script again\n\n"
|
||||
dashes="\n\n###################################################\n\n"
|
||||
|
||||
|
||||
if [ -e "$ROOT_DIR/../../bin/setupvars.sh" ]; then
|
||||
setupvars_path="$ROOT_DIR/../../bin/setupvars.sh"
|
||||
else
|
||||
printf "Error: setupvars.sh is not found\n"
|
||||
echo -ne "Error: setupvars.sh is not found\n"
|
||||
fi
|
||||
|
||||
if ! . "$setupvars_path" ; then
|
||||
@ -71,14 +76,6 @@ if ! . "$setupvars_path" ; then
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Step 1. Download the Caffe model and the prototxt of the model
|
||||
echo -ne "${dashes}"
|
||||
printf "\n\nDownloading the Caffe model and the prototxt"
|
||||
|
||||
cur_path=$PWD
|
||||
|
||||
printf "\nInstalling dependencies\n"
|
||||
|
||||
if [[ -f /etc/centos-release ]]; then
|
||||
DISTRO="centos"
|
||||
elif [[ -f /etc/lsb-release ]]; then
|
||||
@ -86,55 +83,27 @@ elif [[ -f /etc/lsb-release ]]; then
|
||||
fi
|
||||
|
||||
if [[ $DISTRO == "centos" ]]; then
|
||||
sudo -E yum install -y centos-release-scl epel-release
|
||||
sudo -E yum install -y gcc gcc-c++ make glibc-static glibc-devel libstdc++-static libstdc++-devel libstdc++ libgcc \
|
||||
glibc-static.i686 glibc-devel.i686 libstdc++-static.i686 libstdc++.i686 libgcc.i686 cmake
|
||||
|
||||
sudo -E rpm -Uvh http://li.nux.ro/download/nux/dextop/el7/x86_64/nux-dextop-release-0-1.el7.nux.noarch.rpm || true
|
||||
sudo -E yum install -y epel-release
|
||||
sudo -E yum install -y cmake ffmpeg gstreamer1 gstreamer1-plugins-base libusbx-devel
|
||||
|
||||
# check installed Python version
|
||||
if command -v python3.5 >/dev/null 2>&1; then
|
||||
python_binary=python3.5
|
||||
pip_binary=pip3.5
|
||||
fi
|
||||
if command -v python3.6 >/dev/null 2>&1; then
|
||||
python_binary=python3.6
|
||||
pip_binary=pip3.6
|
||||
fi
|
||||
if [ -z "$python_binary" ]; then
|
||||
sudo -E yum install -y rh-python36 || true
|
||||
. scl_source enable rh-python36
|
||||
python_binary=python3.6
|
||||
pip_binary=pip3.6
|
||||
fi
|
||||
elif [[ $DISTRO == "ubuntu" ]]; then
|
||||
sudo -E apt update
|
||||
print_and_run sudo -E apt -y install build-essential python3-pip virtualenv cmake libcairo2-dev libpango1.0-dev libglib2.0-dev libgtk2.0-dev libswscale-dev libavcodec-dev libavformat-dev libgstreamer1.0-0 gstreamer1.0-plugins-base
|
||||
python_binary=python3
|
||||
pip_binary=pip3
|
||||
|
||||
system_ver=$(grep -i "DISTRIB_RELEASE" -f /etc/lsb-release | cut -d "=" -f2)
|
||||
if [ "$system_ver" = "16.04" ]; then
|
||||
sudo -E apt-get install -y libpng12-dev
|
||||
else
|
||||
sudo -E apt-get install -y libpng-dev
|
||||
fi
|
||||
elif [[ "$OSTYPE" == "darwin"* ]]; then
|
||||
# check installed Python version
|
||||
if command -v python3.7 >/dev/null 2>&1; then
|
||||
if command -v python3.8 >/dev/null 2>&1; then
|
||||
python_binary=python3.8
|
||||
elif command -v python3.7 >/dev/null 2>&1; then
|
||||
python_binary=python3.7
|
||||
pip_binary=pip3.7
|
||||
elif command -v python3.6 >/dev/null 2>&1; then
|
||||
python_binary=python3.6
|
||||
pip_binary=pip3.6
|
||||
elif command -v python3.5 >/dev/null 2>&1; then
|
||||
python_binary=python3.5
|
||||
pip_binary=pip3.5
|
||||
else
|
||||
python_binary=python3
|
||||
pip_binary=pip3
|
||||
fi
|
||||
fi
|
||||
|
||||
@ -143,47 +112,52 @@ if ! command -v $python_binary &>/dev/null; then
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [[ "$OSTYPE" == "darwin"* ]]; then
|
||||
"$pip_binary" install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
|
||||
if [ -e "$VENV_DIR" ]; then
|
||||
echo -ne "\n###############|| Using the existing python virtual environment ||###############\n\n"
|
||||
else
|
||||
sudo -E "$pip_binary" install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
|
||||
echo -ne "\n###############|| Creating the python virtual environment ||###############\n\n"
|
||||
"$python_binary" -m venv "$VENV_DIR"
|
||||
fi
|
||||
|
||||
. "$VENV_DIR/bin/activate"
|
||||
python -m pip install -U pip
|
||||
python -m pip install -r "$ROOT_DIR/../open_model_zoo/tools/downloader/requirements.in"
|
||||
|
||||
# Step 1. Download the Caffe model and the prototxt of the model
|
||||
echo -ne "\n###############|| Downloading the Caffe model and the prototxt ||###############\n\n"
|
||||
|
||||
downloader_dir="${INTEL_OPENVINO_DIR}/deployment_tools/open_model_zoo/tools/downloader"
|
||||
|
||||
model_dir=$("$python_binary" "$downloader_dir/info_dumper.py" --name "$model_name" |
|
||||
"$python_binary" -c 'import sys, json; print(json.load(sys.stdin)[0]["subdirectory"])')
|
||||
model_dir=$(python "$downloader_dir/info_dumper.py" --name "$model_name" |
|
||||
python -c 'import sys, json; print(json.load(sys.stdin)[0]["subdirectory"])')
|
||||
|
||||
downloader_path="$downloader_dir/downloader.py"
|
||||
|
||||
print_and_run "$python_binary" "$downloader_path" --name "$model_name" --output_dir "${models_path}" --cache_dir "${models_cache}"
|
||||
print_and_run python "$downloader_path" --name "$model_name" --output_dir "${models_path}" --cache_dir "${models_cache}"
|
||||
|
||||
ir_dir="${irs_path}/${model_dir}/${target_precision}"
|
||||
|
||||
if [ ! -e "$ir_dir" ]; then
|
||||
# Step 2. Configure Model Optimizer
|
||||
echo -ne "${dashes}"
|
||||
printf "Install Model Optimizer dependencies\n\n"
|
||||
cd "${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/install_prerequisites"
|
||||
. ./install_prerequisites.sh caffe
|
||||
cd "$cur_path"
|
||||
echo -ne "\n###############|| Install Model Optimizer dependencies ||###############\n\n"
|
||||
cd "${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer"
|
||||
python -m pip install -r requirements.txt
|
||||
cd "$PWD"
|
||||
|
||||
# Step 3. Convert a model with Model Optimizer
|
||||
echo -ne "${dashes}"
|
||||
printf "Convert a model with Model Optimizer\n\n"
|
||||
echo -ne "\n###############|| Convert a model with Model Optimizer ||###############\n\n"
|
||||
|
||||
mo_path="${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/mo.py"
|
||||
|
||||
export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=cpp
|
||||
print_and_run "$python_binary" "$downloader_dir/converter.py" --mo "$mo_path" --name "$model_name" -d "$models_path" -o "$irs_path" --precisions "$target_precision"
|
||||
print_and_run python "$downloader_dir/converter.py" --mo "$mo_path" --name "$model_name" -d "$models_path" -o "$irs_path" --precisions "$target_precision"
|
||||
else
|
||||
printf "\n\nTarget folder %s already exists. Skipping IR generation with Model Optimizer." "${ir_dir}"
|
||||
echo -ne "\n\nTarget folder ${ir_dir} already exists. Skipping IR generation with Model Optimizer."
|
||||
echo -ne "If you want to convert a model again, remove the entire ${ir_dir} folder. ${run_again}"
|
||||
fi
|
||||
|
||||
# Step 4. Build samples
|
||||
echo -ne "${dashes}"
|
||||
printf "Build Inference Engine samples\n\n"
|
||||
echo -ne "\n###############|| Build Inference Engine samples ||###############\n\n"
|
||||
|
||||
OS_PATH=$(uname -m)
|
||||
NUM_THREADS="-j2"
|
||||
@ -194,7 +168,7 @@ if [ "$OS_PATH" == "x86_64" ]; then
|
||||
fi
|
||||
|
||||
samples_path="${INTEL_OPENVINO_DIR}/deployment_tools/inference_engine/samples/cpp"
|
||||
build_dir="$HOME/inference_engine_samples_build"
|
||||
build_dir="$HOME/inference_engine_cpp_samples_build"
|
||||
binaries_dir="${build_dir}/${OS_PATH}/Release"
|
||||
|
||||
if [ -e "$build_dir/CMakeCache.txt" ]; then
|
||||
@ -207,8 +181,7 @@ cmake -DCMAKE_BUILD_TYPE=Release "$samples_path"
|
||||
make $NUM_THREADS classification_sample_async
|
||||
|
||||
# Step 5. Run samples
|
||||
echo -ne "${dashes}"
|
||||
printf "Run Inference Engine classification sample\n\n"
|
||||
echo -ne "\n###############|| Run Inference Engine classification sample ||###############\n\n"
|
||||
|
||||
cd "$binaries_dir"
|
||||
|
||||
@ -216,5 +189,4 @@ cp -f "$ROOT_DIR/${model_name}.labels" "${ir_dir}/"
|
||||
|
||||
print_and_run ./classification_sample_async -d "$target" -i "$target_image_path" -m "${ir_dir}/${model_name}.xml" "${sampleoptions[@]}"
|
||||
|
||||
echo -ne "${dashes}"
|
||||
printf "Demo completed successfully.\n\n"
|
||||
echo -ne "\n###############|| Demo completed successfully ||###############\n\n"
|
||||
|
||||
Loading…
Reference in New Issue
Block a user