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Yolo12 OpenVINO/XNNPACK sample
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‎.ci/scripts/test_yolo12.sh‎

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#!/bin/bash
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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set -ex
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# shellcheck source=/dev/null
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source "$(dirname "${BASH_SOURCE[0]}")/utils.sh"
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while [[ $# -gt 0 ]]; do
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case "$1" in
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-model)
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MODEL_NAME="$2" # stories110M
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shift 2
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;;
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-mode)
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MODE="$2" # portable or xnnpack+custom or xnnpack+custom+qe
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shift 2
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;;
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-pt2e_quantize)
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PT2E_QUANTIZE="$2"
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shift 2
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;;
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-upload)
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UPLOAD_DIR="$2"
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shift 2
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;;
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-video_path)
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VIDEO_PATH="$2" # portable or xnnpack+custom or xnnpack+custom+qe
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shift 2
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;;
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*)
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echo "Unknown option: $1"
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usage
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;;
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esac
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done
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# Default mode to xnnpack+custom if not set
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MODE=${MODE:-"openvino"}
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# Default UPLOAD_DIR to empty string if not set
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UPLOAD_DIR="${UPLOAD_DIR:-}"
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# Default PT2E_QUANTIZE to empty string if not set
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PT2E_QUANTIZE="${PT2E_QUANTIZE:-}"
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# Default CMake Build Type to release mode
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CMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE:-Release}
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if [[ $# -lt 5 ]]; then # Assuming 4 mandatory args
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echo "Expecting atleast 5 positional arguments"
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echo "Usage: [...]"
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fi
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if [[ -z "${MODEL_NAME:-}" ]]; then
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echo "Missing model name, exiting..."
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exit 1
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fi
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if [[ -z "${MODE:-}" ]]; then
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echo "Missing mode, choose openvino or xnnpack, exiting..."
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exit 1
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fi
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if [[ -z "${PYTHON_EXECUTABLE:-}" ]]; then
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PYTHON_EXECUTABLE=python3
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fi
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TARGET_LIBS=""
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if [[ "${MODE}" =~ .*openvino.* ]]; then
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OPENVINO=ON
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TARGET_LIBS="$TARGET_LIBS openvino_backend "
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git clone https://github.com/daniil-lyakhov/openvino.git
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cd openvino && git checkout dl/executorch/yolo12
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git submodule update --init --recursive
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sudo ./install_build_dependencies.sh
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mkdir build && cd build
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cmake .. -DCMAKE_BUILD_TYPE=Release -DENABLE_PYTHON=ON
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make -j$(nproc)
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cd ..
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cmake --install build --prefix dist
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source dist/setupvars.sh
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cd ../backends/openvino
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pip install -r requirements.txt
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cd ../../
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else
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OPENVINO=OFF
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fi
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if [[ "${MODE}" =~ .*xnnpack.* ]]; then
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XNNPACK=ON
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TARGET_LIBS="$TARGET_LIBS xnnpack_backend "
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else
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XNNPACK=OFF
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fi
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which "${PYTHON_EXECUTABLE}"
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DIR="examples/models/yolo12"
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$PYTHON_EXECUTABLE -m pip install -r ${DIR}/requirements.txt
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cmake_install_executorch_libraries() {
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rm -rf cmake-out
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build_dir=cmake-out
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mkdir $build_dir
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retry cmake -DCMAKE_INSTALL_PREFIX="${build_dir}" \
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-DCMAKE_BUILD_TYPE="${CMAKE_BUILD_TYPE}" \
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-DEXECUTORCH_BUILD_OPENVINO="$OPENVINO" \
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-DEXECUTORCH_BUILD_XNNPACK="$XNNPACK" \
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-DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
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-DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
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-DEXECUTORCH_BUILD_EXTENSION_RUNNER_UTIL=ON \
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-DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
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-B"${build_dir}"
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# Build the project
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cmake --build ${build_dir} --target install --config ${CMAKE_BUILD_TYPE} -j$(nproc)
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export CMAKE_ARGS="
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-DEXECUTORCH_BUILD_OPENVINO="$OPENVINO" \
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-DEXECUTORCH_BUILD_XNNPACK="$XNNPACK" \
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-DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
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-DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
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-DEXECUTORCH_BUILD_EXTENSION_RUNNER_UTIL=ON \
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-DEXECUTORCH_ENABLE_LOGGING=ON \
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-DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
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-DEXECUTORCH_BUILD_PYBIND=ON"
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echo $TARGET_LIBS
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export CMAKE_BUILD_ARGS="--target $TARGET_LIBS"
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pip install . --no-build-isolation
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}
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cmake_build_demo() {
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echo "Building yolo12 runner"
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retry cmake \
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-DCMAKE_BUILD_TYPE="$CMAKE_BUILD_TYPE" \
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-DUSE_OPENVINO_BACKEND="$OPENVINO" \
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-DUSE_XNNPACK_BACKEND="$XNNPACK" \
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-Bcmake-out/${DIR} \
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${DIR}
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cmake --build cmake-out/${DIR} -j9 --config "$CMAKE_BUILD_TYPE"
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}
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cleanup_files() {
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rm $EXPORTED_MODEL_NAME
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}
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prepare_artifacts_upload() {
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if [ -n "${UPLOAD_DIR}" ]; then
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echo "Preparing for uploading generated artifacs"
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zip -j model.zip "${EXPORTED_MODEL_NAME}"
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mkdir -p "${UPLOAD_DIR}"
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mv model.zip "${UPLOAD_DIR}"
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mv result.txt "${UPLOAD_DIR}"
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fi
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}
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# Export model.
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EXPORTED_MODEL_NAME="${MODEL_NAME}_fp32_${MODE}.pte"
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echo "Exporting ${EXPORTED_MODEL_NAME}"
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EXPORT_ARGS="--model_name=${MODEL_NAME} --backend=${MODE}"
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# Add dynamically linked library location
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cmake_install_executorch_libraries
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$PYTHON_EXECUTABLE -m examples.models.yolo12.export_and_validate ${EXPORT_ARGS}
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RUNTIME_ARGS="--model_path=${EXPORTED_MODEL_NAME} --input_path=${VIDEO_PATH}"
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# Check build tool.
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cmake_build_demo
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# Run yolo12 runner
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NOW=$(date +"%H:%M:%S")
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echo "Starting to run yolo12 runner at ${NOW}"
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# shellcheck source=/dev/null
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cmake-out/examples/models/yolo12/Yolo12DetectionDemo ${RUNTIME_ARGS} > result.txt
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NOW=$(date +"%H:%M:%S")
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echo "Finished at ${NOW}"
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RESULT=$(cat result.txt)
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prepare_artifacts_upload
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cleanup_files

‎backends/openvino/README.md‎

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### Build OpenVINO from Source
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```bash
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git clone https://github.com/openvinotoolkit/openvino.git
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cd openvino && git checkout releases/2025/1
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git clone https://github.com/daniil-lyakhov/openvino.git
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cd openvino && git checkout dl/executorch/yolo12
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git submodule update --init --recursive
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sudo ./install_build_dependencies.sh
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mkdir build && cd build

‎examples/models/yolo12/CMakeLists.txt‎

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cmake_minimum_required(VERSION 3.5)
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project(Yolo12DetectionDemo VERSION 0.1)
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option(USE_OPENVINO_BACKEND "Build the tutorial with the OPENVINO backend" ON)
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option(USE_XNNPACK_BACKEND "Build the tutorial with the XNNPACK backend" OFF)
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set(CMAKE_INCLUDE_CURRENT_DIR ON)
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set(CMAKE_CXX_STANDARD 17)
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set(CMAKE_CXX_STANDARD_REQUIRED ON)
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set(CMAKE_CXX_EXTENSIONS OFF)
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# OpenCV
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find_package(OpenCV REQUIRED)
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include_directories(${OpenCV_INCLUDE_DIRS})
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# !OpenCV
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if(NOT PYTHON_EXECUTABLE)
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set(PYTHON_EXECUTABLE python3)
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endif()
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set(EXECUTORCH_ROOT ${CMAKE_CURRENT_SOURCE_DIR}/../../..)
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set(TORCH_ROOT ${EXECUTORCH_ROOT}/third-party/pytorch)
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include(${EXECUTORCH_ROOT}/tools/cmake/Utils.cmake)
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# Let files say "include <executorch/path/to/header.h>".
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set(_common_include_directories ${EXECUTORCH_ROOT}/..)
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# find `executorch` libraries Same as for gflags
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find_package(executorch CONFIG REQUIRED PATHS ${EXECUTORCH_ROOT}/cmake-out)
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target_link_options_shared_lib(executorch)
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set(link_libraries gflags)
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list(APPEND link_libraries portable_ops_lib portable_kernels)
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target_link_options_shared_lib(portable_ops_lib)
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if(USE_XNNPACK_BACKEND)
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set(xnnpack_backend_libs xnnpack_backend XNNPACK microkernels-prod)
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list(APPEND link_libraries ${xnnpack_backend_libs})
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target_link_options_shared_lib(xnnpack_backend)
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endif()
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if(USE_OPENVINO_BACKEND)
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add_subdirectory(${EXECUTORCH_ROOT}/backends/openvino openvino_backend)
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target_include_directories(
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openvino_backend
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INTERFACE ${CMAKE_CURRENT_BINARY_DIR}/../../include
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${CMAKE_CURRENT_BINARY_DIR}/../../include/executorch/runtime/core/portable_type/c10
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${CMAKE_CURRENT_BINARY_DIR}/../../lib
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)
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list(APPEND link_libraries openvino_backend)
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target_link_options_shared_lib(openvino_backend)
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endif()
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list(APPEND link_libraries extension_threadpool pthreadpool)
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list(APPEND _common_include_directories
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${XNNPACK_ROOT}/third-party/pthreadpool/include
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)
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set(PROJECT_SOURCES
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main.cpp
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inference.h
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${EXECUTORCH_ROOT}/extension/data_loader/file_data_loader.cpp
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${EXECUTORCH_ROOT}/extension/evalue_util/print_evalue.cpp
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${EXECUTORCH_ROOT}/extension/runner_util/inputs.cpp
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${EXECUTORCH_ROOT}/extension/runner_util/inputs_portable.cpp
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)
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add_executable(Yolo12DetectionDemo ${PROJECT_SOURCES})
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target_link_libraries(Yolo12DetectionDemo PUBLIC
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${link_libraries}
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${OpenCV_LIBS}
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executorch_core
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extension_module
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extension_tensor
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)
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find_package(Threads REQUIRED)
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target_link_libraries(Yolo12DetectionDemo PRIVATE Threads::Threads)
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target_include_directories(Yolo12DetectionDemo PUBLIC ${_common_include_directories})

‎examples/models/yolo12/README.md‎

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# YOLO12 Detection C++ Inference with ExecuTorch
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<p align="center">
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<br>
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<img src="./yolo12s_demo.gif">
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<br>
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</p>
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This example demonstrates how to perform inference of [Ultralytics YOLO12 family](https://docs.ultralytics.com/models/yolo12/) detection models in C++ leveraging the Executorch backends:
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- [OpenVINO](../../../backends/openvino/README.md)
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- [XNNPACK](../../../backends/xnnpack/README.md)
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# Instructions
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### Step 1: Install ExecuTorch
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To install ExecuTorch, follow this [guide](https://pytorch.org/executorch/stable/getting-started-setup.html).
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### Step 2: Install the backend of your choice
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- [OpenVINO backend installation guide](../../../backends/openvino/README.md#build-instructions)
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- [XNNPACK backend installation guilde](https://pytorch.org/executorch/stable/tutorial-xnnpack-delegate-lowering.html#running-the-xnnpack-model-with-cmake)
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### Step 3: Install the demo requirements
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Python demo requirements:
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```bash
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python -m pip install -r examples/models/yolo12/requirements.txt
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```
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Demo infenrece dependency - OpenCV library:
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https://opencv.org/get-started/
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### Step 4: Export the Yolo12 model to the ExecuTorch
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OpenVINO:
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```bash
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python export_and_validate.py --model_name yolo12s --input_dims=[1920,1080] --backend openvino --device CPU
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```
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XNNPACK:
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```bash
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python export_and_validate.py --model_name yolo12s --input_dims=[1920,1080] --backend xnnpack
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```
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> **_NOTE:_** Quantization is comming soon!
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Exported model could be validated using the `--validate` key:
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```bash
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python export_and_validate.py --model_name yolo12s --backend ... --validate dataset_name.yaml
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```
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A list of available datasets and instructions on how to use a custom dataset can be found [here](https://docs.ultralytics.com/datasets/detect/).
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Validation only supports the default `--input_dims`; please do not specify this parameter when using the `--validate` flag.
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To get a full parameters description please use the following command:
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```bash
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python export_and_validate.py --help
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```
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### Step 5: Build the demo project
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OpenVINO:
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```bash
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cd examples/models/yolo12
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mkdir build && cd build
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cmake -DCMAKE_BUILD_TYPE=Release -DUSE_OPENVINO_BACKEND=ON ..
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make -j$(nproc)
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```
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XNNPACK:
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```bash
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cd examples/models/yolo12
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mkdir build && cd build
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cmake -DCMAKE_BUILD_TYPE=Release -DUSE_XNNPACK_BACKEND=ON ..
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make -j$(nproc)
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```
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### Step 6: Run the demo
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```bash
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./build/Yolo12DetectionDemo -model_path /path/to/exported/model -input_path /path/to/video/file -output_path /path/to/output/annotated/video
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```
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To get a full parameters description please use the following command:
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```
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./build/Yolo12DetectionDemo --help
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```
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# Credits:
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Ultralytics examples: https://github.com/ultralytics/ultralytics/tree/main/examples
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Sample video: https://www.pexels.com/@shanu-1040189/

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