860896c4bb
* 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 $ROOT_DIR * Make the step messages look the same as in the .bat scripts * Make the same changes to demo_benchmark_app.sh as in other .sh scripts * Remove a mention of FPGA from a help message * Set venv folder to `venv_openvino`
197 lines
6.1 KiB
Bash
Executable File
197 lines
6.1 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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echo -ne "\e[0;33mWARNING: If you get an error when running the demo in the Docker container, you may need to install additional packages. To do this, run the container as root (-u 0) and run install_openvino_dependencies.sh script. If you get a package-independent error, try setting additional parameters using -sample-options.\e[0m\n"
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ROOT_DIR="$( 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
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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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trap 'error ${LINENO}' ERR
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target="CPU"
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# parse command line options
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while [[ $# -gt 0 ]]
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do
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key="$1"
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case $key in
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-h | -help | --help)
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usage
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;;
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-d)
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target="$2"
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echo target = "${target}"
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shift
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;;
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-sample-options)
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sampleoptions=("${@:2}")
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echo sample-options = "${sampleoptions[*]}"
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shift
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;;
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*)
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# unknown option
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;;
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esac
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shift
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done
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if [ -z "${sampleoptions[*]}" ]; then
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sampleoptions=( -niter 1000 )
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fi
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target_precision="FP16"
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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="$HOME/openvino_models/cache"
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irs_path="$HOME/openvino_models/ir"
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model_name="squeezenet1.1"
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target_image_path="$ROOT_DIR/car.png"
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run_again="Then run the script again\n\n"
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if [ -e "$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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elif [[ -f /etc/lsb-release ]]; then
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DISTRO="ubuntu"
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fi
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if [[ $DISTRO == "centos" ]]; then
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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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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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fi
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elif [[ $DISTRO == "ubuntu" ]]; then
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python_binary=python3
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elif [[ "$OSTYPE" == "darwin"* ]]; then
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# check installed Python version
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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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elif command -v python3.6 >/dev/null 2>&1; then
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python_binary=python3.6
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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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else
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python_binary=python3
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fi
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fi
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if ! command -v $python_binary &>/dev/null; then
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echo -ne "\n\nPython 3.5 (x64) or higher is not installed. It is required to run Model Optimizer, please install it. ${run_again}"
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exit 1
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fi
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if [ -e "$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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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 "$downloader_dir/info_dumper.py" --name "$model_name" |
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python -c 'import sys, json; print(json.load(sys.stdin)[0]["subdirectory"])')
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downloader_path="$downloader_dir/downloader.py"
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print_and_run python "$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 "$ir_dir" ]; then
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# Step 2. Configure Model Optimizer
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echo -ne "\n###############|| Install Model Optimizer dependencies ||###############\n\n"
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cd "${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer"
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python -m pip install -r requirements.txt
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cd "$PWD"
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# Step 3. Convert a model with Model Optimizer
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echo -ne "\n###############|| Convert a model with Model Optimizer ||###############\n\n"
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mo_path="${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 "$downloader_dir/converter.py" --mo "$mo_path" --name "$model_name" -d "$models_path" -o "$irs_path" --precisions "$target_precision"
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else
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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. ${run_again}"
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fi
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# Step 4. Build samples
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echo -ne "\n###############|| Build Inference Engine samples ||###############\n\n"
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OS_PATH=$(uname -m)
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NUM_THREADS="-j2"
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if [ "$OS_PATH" == "x86_64" ]; then
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OS_PATH="intel64"
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NUM_THREADS="-j8"
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fi
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samples_path="${INTEL_OPENVINO_DIR}/deployment_tools/inference_engine/samples/cpp"
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build_dir="$HOME/inference_engine_cpp_samples_build"
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binaries_dir="${build_dir}/${OS_PATH}/Release"
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if [ -e "$build_dir/CMakeCache.txt" ]; then
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rm -rf "$build_dir/CMakeCache.txt"
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fi
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mkdir -p "$build_dir"
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cd "$build_dir"
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cmake -DCMAKE_BUILD_TYPE=Release "$samples_path"
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make $NUM_THREADS benchmark_app
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# Step 5. Run samples
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echo -ne "\n###############|| Run Inference Engine benchmark app ||###############\n\n"
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cd "$binaries_dir"
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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 "\n###############|| Inference Engine benchmark app completed successfully ||###############\n\n"
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