[Examples] Yolo26 Sample for OpenVINO/XNNPACK (pytorch#18583)

### Summary
Yolo12 is replaced by the Yolo26 model in the examples


### Test plan

Local sanity check

| CPU | Backend | Model | Precision | Average detection time, ms
1920x1080 |

|--------------------------------------------|----------|---------|-----------|------------------------|
| Intel(R) Core(TM) i9-10980XE CPU @ 3.00GHz | OpenVINO | Yolo26s | FP32
| 159.48 |
| Intel(R) Core(TM) i9-10980XE CPU @ 3.00GHz | OpenVINO | Yolo26s | INT8
| 73 |
| Intel(R) Core(TM) i9-10980XE CPU @ 3.00GHz | XNNPACK | Yolo26s | FP32
| 312.403 |
| Intel(R) Core(TM) i9-10980XE CPU @ 3.00GHz | XNNPACK | Yolo26s | INT8
| 267.609 |

test_yolo26.sh is running ok on my local machine, please help me to
validate the .ci/scripts/test_yolo26.sh
CC: @mergennachin @lucylq

---------

Co-authored-by: Surya Siddharth Pemmaraju <surya.siddharth.pemmaraju@intel.com>

Author: daniil-lyakhov

.ci/scripts/test_yolo12.sh .ci/scripts/test_yolo26.sh.ci/scripts/test_yolo12.sh renamed to .ci/scripts/test_yolo26.sh

@@ -6,6 +6,7 @@
 # LICENSE file in the root directory of this source tree.
 
 set -ex
+
 # shellcheck source=/dev/null
 source "$(dirname "${BASH_SOURCE[0]}")/utils.sh"
 
@@ -50,21 +51,21 @@ PT2E_QUANTIZE="${PT2E_QUANTIZE:-}"
 # Default CMake Build Type to release mode
 CMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE:-Release}
 
-if [[ $# -lt 5 ]]; then # Assuming 4 mandatory args
-    echo "Expecting atleast 5 positional arguments"
-    echo "Usage: [...]"
-fi
 if [[ -z "${MODEL_NAME:-}" ]]; then
   echo "Missing model name, exiting..."
   exit 1
 fi
 
-
 if [[ -z "${MODE:-}" ]]; then
   echo "Missing mode, choose openvino or xnnpack, exiting..."
   exit 1
 fi
 
+if [[ -z "${VIDEO_PATH:-}" ]]; then
+  echo "Missing video path, exiting..."
+  exit 1
+fi
+
 if [[ -z "${PYTHON_EXECUTABLE:-}" ]]; then
   PYTHON_EXECUTABLE=python3
 fi
@@ -75,21 +76,13 @@ if [[ "${MODE}" =~ .*openvino.* ]]; then
   OPENVINO=ON
   TARGET_LIBS="$TARGET_LIBS openvino_backend "
 
-  git clone https://github.com/openvinotoolkit/openvino.git
-  cd openvino && git b16b776ac119dafda51f69a80f1e6b7376d02c3b
-  git submodule update --init --recursive
-  sudo ./install_build_dependencies.sh
-  mkdir build && cd build
-  cmake .. -DCMAKE_BUILD_TYPE=Release -DENABLE_PYTHON=ON
-  make -j$(nproc)
-
-  cd ..
-  cmake --install build --prefix dist
-
-  source dist/setupvars.sh
-  cd ../backends/openvino
-  pip install -r requirements.txt
-  cd ../../
+  # Install specific OpenVINO runtime from pip.
+  $PYTHON_EXECUTABLE -m pip install --pre openvino==2026.1.0.dev20260131 --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly
+  $PYTHON_EXECUTABLE -m pip install -r backends/openvino/requirements.txt
+
+  # Set OPENVINO_LIB_PATH so the C++ demo runner can also find libopenvino_c.so.
+  OPENVINO_LIB_PATH=$($PYTHON_EXECUTABLE -c "import openvino, os, glob; print(sorted(glob.glob(os.path.join(os.path.dirname(openvino.__file__), 'libs', 'libopenvino_c.so*')))[-1])")
+  export OPENVINO_LIB_PATH
 else
   OPENVINO=OFF
 fi
@@ -103,9 +96,10 @@ fi
 
 which "${PYTHON_EXECUTABLE}"
 
+TORCH_URL=https://download.pytorch.org/whl/cpu
 
-DIR="examples/models/yolo12"
-$PYTHON_EXECUTABLE -m pip install -r ${DIR}/requirements.txt
+DIR="examples/models/yolo26"
+$PYTHON_EXECUTABLE -m pip install --upgrade-strategy only-if-needed --extra-index-url "$TORCH_URL" -r ${DIR}/requirements.txt
 
 cmake_install_executorch_libraries() {
     rm -rf cmake-out
@@ -142,11 +136,11 @@ cmake_install_executorch_libraries() {
 
     echo $TARGET_LIBS
     export CMAKE_BUILD_ARGS="--target $TARGET_LIBS"
-    pip install . --no-build-isolation
+    $PYTHON_EXECUTABLE -m pip install . --no-build-isolation
 }
 
 cmake_build_demo() {
-    echo "Building yolo12 runner"
+    echo "Building yolo26 runner"
     retry cmake \
         -DCMAKE_BUILD_TYPE="$CMAKE_BUILD_TYPE" \
         -DUSE_OPENVINO_BACKEND="$OPENVINO" \
@@ -174,24 +168,29 @@ prepare_artifacts_upload() {
 
 
 # Export model.
-EXPORTED_MODEL_NAME="${MODEL_NAME}_fp32_${MODE}.pte"
-echo "Exporting ${EXPORTED_MODEL_NAME}"
 EXPORT_ARGS="--model_name=${MODEL_NAME} --backend=${MODE}"
+if [[ -n "${PT2E_QUANTIZE}" ]]; then
+  EXPORTED_MODEL_NAME="${MODEL_NAME}_int8_${MODE}.pte"
+  EXPORT_ARGS="${EXPORT_ARGS} --quantize --video_path=${VIDEO_PATH}"
+else
+  EXPORTED_MODEL_NAME="${MODEL_NAME}_fp32_${MODE}.pte"
+fi
+echo "Exporting ${EXPORTED_MODEL_NAME}"
 
 # Add dynamically linked library location
 cmake_install_executorch_libraries
 
-$PYTHON_EXECUTABLE -m examples.models.yolo12.export_and_validate ${EXPORT_ARGS}
+$PYTHON_EXECUTABLE -m examples.models.yolo26.export_and_validate ${EXPORT_ARGS}
 
 
 RUNTIME_ARGS="--model_path=${EXPORTED_MODEL_NAME} --input_path=${VIDEO_PATH}"
 # Check build tool.
 cmake_build_demo
-# Run yolo12 runner
+# Run yolo26 runner
 NOW=$(date +"%H:%M:%S")
-echo "Starting to run yolo12 runner at ${NOW}"
+echo "Starting to run yolo26 runner at ${NOW}"
 # shellcheck source=/dev/null
-cmake-out/examples/models/yolo12/Yolo12DetectionDemo ${RUNTIME_ARGS} > result.txt
+cmake-out/examples/models/yolo26/Yolo26DetectionDemo ${RUNTIME_ARGS} > result.txt
 NOW=$(date +"%H:%M:%S")
 echo "Finished at ${NOW}"
 

README.md

@@ -204,7 +204,7 @@ ExecuTorch powers on-device AI at scale across Meta's family of apps, VR/AR devi
 
 **Multimodal:** [Llava](examples/models/llava/README.md) (vision-language), [Voxtral](examples/models/voxtral/README.md) (audio-language), [Gemma](examples/models/gemma3) (vision-language)
 
-**Vision/Speech:** [MobileNetV2](https://github.com/meta-pytorch/executorch-examples/tree/main/mv2), [DeepLabV3](https://github.com/meta-pytorch/executorch-examples/tree/main/dl3), [Whisper](examples/models/whisper/README.md) <!-- @lint-ignore -->
+**Vision/Speech:** [MobileNetV2](https://github.com/meta-pytorch/executorch-examples/tree/main/mv2), [DeepLabV3](https://github.com/meta-pytorch/executorch-examples/tree/main/dl3), [YOLO26](examples/models/yolo26/README.md), [Whisper](examples/models/whisper/README.md) <!-- @lint-ignore -->
 
 **Resources:** [`examples/`](examples/) directory • [executorch-examples](https://github.com/meta-pytorch/executorch-examples) out-of-tree demos • [Optimum-ExecuTorch](https://github.com/huggingface/optimum-executorch) for HuggingFace models • [Unsloth](https://docs.unsloth.ai/new/deploy-llms-phone) for fine-tuned LLM deployment <!-- @lint-ignore -->
 

backends/openvino/quantizer/quantizer.py

@@ -192,12 +192,18 @@ def set_ignored_scope(
         :param validate: If set to True, then a RuntimeError will be raised if any ignored scope does not match
           in the model graph.
         """
+        subgraphs_ = []
+        if subgraphs:
+            subgraphs_ = [
+                nncf.Subgraph(inputs=subgraph[0], outputs=subgraph[1])
+                for subgraph in subgraphs
+            ]
         self._algo.set_ignored_scope(
             nncf.IgnoredScope(
                 names=names or [],
                 patterns=patterns or [],
                 types=types or [],
-                subgraphs=subgraphs or [],
+                subgraphs=subgraphs_,
                 validate=validate,
             )
         )

docs/source/success-stories.md

@@ -156,7 +156,7 @@ Automate PyTorch model deployment to iOS, Android, and edge devices with ExecuTo
 
 - **LoRA adapter** - Export two LoRA adapters that share a single foundation weight file, saving memory and disk space. [Try →](https://github.com/meta-pytorch/executorch-examples/tree/main/program-data-separation/cpp/lora_example)
 
-- **OpenVINO from Intel** - Deploy [Yolo12](https://github.com/pytorch/executorch/tree/main/examples/models/yolo12), [Llama](https://github.com/pytorch/executorch/tree/main/examples/openvino/llama), and [Stable Diffusion](https://github.com/pytorch/executorch/tree/main/examples/openvino/stable_diffusion) on [OpenVINO from Intel](https://www.intel.com/content/www/us/en/developer/articles/community/optimizing-executorch-on-ai-pcs.html).
+- **OpenVINO from Intel** - Deploy [Yolo26](https://github.com/pytorch/executorch/tree/main/examples/models/yolo26), [Llama](https://github.com/pytorch/executorch/tree/main/examples/openvino/llama), and [Stable Diffusion](https://github.com/pytorch/executorch/tree/main/examples/openvino/stable_diffusion) on [OpenVINO from Intel](https://www.intel.com/content/www/us/en/developer/articles/community/optimizing-executorch-on-ai-pcs.html).
 
 - **Audio Generation** - Generate audio from text prompts using Stable Audio Open Small on Arm CPUs with XNNPACK and KleidiAI. [Try →](https://github.com/Arm-Examples/ML-examples/tree/main/kleidiai-examples/audiogen-et) • [Video →](https://www.youtube.com/watch?v=q2P0ESVxhAY) <!-- @lint-ignore -->
 

examples/models/yolo12/inference.h

@@ -1,6 +1,6 @@
 cmake_minimum_required(VERSION 3.5)
 
-project(Yolo12DetectionDemo VERSION 0.1)
+project(Yolo26DetectionDemo VERSION 0.1)
 
 option(USE_OPENVINO_BACKEND "Build the tutorial with the OPENVINO backend" OFF)
 option(USE_XNNPACK_BACKEND "Build the tutorial with the XNNPACK backend" OFF)
@@ -44,7 +44,8 @@ if(USE_XNNPACK_BACKEND)
 endif()
 
 if(USE_OPENVINO_BACKEND)
-  find_package(OpenVINO REQUIRED)
+  # The OpenVINO backend resolves symbols via dlopen at runtime, so there is no
+  # build-time dependency on the OpenVINO SDK (no find_package needed).
   list(APPEND link_libraries openvino_backend)
   executorch_target_link_options_shared_lib(openvino_backend)
 endif()
@@ -63,14 +64,14 @@ set(PROJECT_SOURCES
     ${EXECUTORCH_ROOT}/extension/runner_util/inputs_portable.cpp
 )
 
-add_executable(Yolo12DetectionDemo ${PROJECT_SOURCES})
+add_executable(Yolo26DetectionDemo ${PROJECT_SOURCES})
 target_link_libraries(
-  Yolo12DetectionDemo PUBLIC ${link_libraries} ${OpenCV_LIBS} executorch_core
+  Yolo26DetectionDemo PUBLIC ${link_libraries} ${OpenCV_LIBS} executorch_core
                              extension_module extension_tensor
 )
 
 find_package(Threads REQUIRED)
-target_link_libraries(Yolo12DetectionDemo PRIVATE Threads::Threads)
+target_link_libraries(Yolo26DetectionDemo PRIVATE Threads::Threads)
 target_include_directories(
-  Yolo12DetectionDemo PUBLIC ${_common_include_directories}
+  Yolo26DetectionDemo PUBLIC ${_common_include_directories}
 )