Accuracy check YML

.github/workflows/ci.yml

@@ -229,7 +229,7 @@ jobs:
         token: ${{ secrets.CODECOV_TOKEN }}
         slug: embedded-dev-research/ITLabAI
 
-  evaluate-model:
+  evaluate-model-alexnet:
     runs-on: ubuntu-latest
     needs: [build-linux]
     permissions:
@@ -319,3 +319,285 @@ jobs:
           git commit -m "[CI] Update accuracy: $(cat accuracy_value.txt)"
           git push origin master
         fi
+
+  evaluate-models-onnx:
+    runs-on: ubuntu-latest
+    needs: [build-linux]
+    permissions:
+      contents: write
+    strategy:
+      fail-fast: false
+      matrix:
+        model: [googlenet, densenet, resnet, yolo]
+        include:
+          - model: googlenet
+            parser: parser_onnx.py
+            model_file: GoogLeNet.onnx
+            model_path: docs/models/GoogLeNet.onnx
+            model_url: ''
+            extra_args: "--onednn 10000"
+          - model: densenet
+            parser: parser_onnx.py
+            model_file: densenet121_Opset16.onnx
+            model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/densenet121_Opset16_timm/densenet121_Opset16.onnx?download=
+            extra_args: "--onednn 1000"
+          - model: resnet
+            parser: parser_onnx.py
+            model_file: resnest101e_Opset16.onnx
+            model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/resnest101e_Opset16_timm/resnest101e_Opset16.onnx?download=
+            extra_args: "--onednn 1000"
+          - model: yolo
+            parser: parser_onnx.py
+            model_file: yolo11x-cls.pt
+            model_url: https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo11x-cls.pt
+            extra_args: "--onednn 1000"
+
+    steps:
+    - uses: actions/checkout@v4
+      with:
+        fetch-depth: 0
+
+    - name: Download binary and libs
+      uses: actions/download-artifact@v4
+      with:
+        name: mnist-RELEASE
+        path: build/
+
+    - name: Set binary path
+      id: set_eval_binary
+      run: |
+        echo "EVAL_BINARY=build/bin/ACC" >> $GITHUB_OUTPUT
+
+    - name: Install system dependencies
+      run: |
+        sudo apt-get update
+        sudo apt-get install -y libgtk-3-0 libtbb12 libjpeg-dev libpng-dev libtiff-dev libopenjp2-7 libdnnl3
+        sudo ldconfig
+
+    - name: Download model (if URL provided)
+      if: matrix.model_url != ''
+      run: |
+        mkdir -p docs/models
+        echo "Скачивание ${{ matrix.model_file }} из ${{ matrix.model_url }}"
+        wget -O docs/models/${{ matrix.model_file }} ${{ matrix.model_url }}
+        ls -la docs/models/
+
+    - name: Setup Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.10'
+
+    - name: Install Python dependencies from requirements.txt
+      run: |
+        cd app/Converters
+        pip install -r requirements.txt
+        cd ../..
+
+    - name: Cache model JSON files
+      id: cache-model-json
+      uses: actions/cache@v4
+      with:
+        path: docs/jsons
+        key: model-json-${{ matrix.model }}-${{ hashFiles('app/Converters/parser_onnx.py', 'app/Converters/requirements.txt') }}
+        restore-keys: |
+          model-json-${{ matrix.model }}-
+          model-json-
+
+    - name: Generate model JSON
+      if: steps.cache-model-json.outputs.cache-hit != 'true'
+      run: |
+        mkdir -p docs/jsons
+        cd app/Converters
+        python ${{ matrix.parser }} ${{ matrix.model }}
+        cd ../..
+
+    - name: Cache ImageNet-Paste dataset
+      id: cache-imagenet-restore
+      uses: actions/cache/restore@v4
+      with:
+        path: docs/ImageNet
+        key: imagenet-paste-${{ github.run_id }}-${{ hashFiles('app/Converters/download_imagenet.py') }}
+        restore-keys: |
+          imagenet-paste-
+
+    - name: Download ImageNet-Paste dataset
+      if: steps.cache-imagenet-restore.outputs.cache-hit != 'true'
+      env:
+        HF_TOKEN: ${{ secrets.HF_TOKEN }}
+      run: |
+        mkdir -p docs/ImageNet/test
+        cd app/Converters
+        python download_imagenet.py
+        cd ../..
+
+    - name: Save ImageNet-Paste dataset
+      if: steps.cache-imagenet-restore.outputs.cache-hit != 'true'
+      uses: actions/cache/save@v4
+      with:
+        path: docs/ImageNet
+        key: imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}
+
+    - name: Prepare environment
+      run: |
+        chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
+        echo "LD_LIBRARY_PATH=$PWD/build/bin/all_libs:/usr/lib/x86_64-linux-gnu" >> $GITHUB_ENV
+
+    - name: Increase system limits
+      run: |
+        sudo prlimit --pid $$ --as=unlimited
+        ulimit -s unlimited
+        ulimit -c unlimited
+        echo "Новые лимиты:"
+        ulimit -a
+
+    - name: Run evaluation
+      run: |
+        DATASET_PATH="docs/ImageNet/test"
+        MODEL="${{ matrix.model }}"
+        EXTRA_ARGS="${{ matrix.extra_args }}"
+
+        echo "Запуск оценки для модели $MODEL"
+        echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model $MODEL $EXTRA_ARGS"
+
+        echo "Системная информация до запуска:"
+        echo "--- Память ---"
+        free -h
+        echo "--- CPU ---"
+        top -bn1 | head -5
+        echo "--- Диск ---"
+        df -h docs/ImageNet/test/
+
+        TIMESTAMP=$(date +%s)
+        MONITOR_LOG="monitor_$MODEL.log"
+
+        monitor_process() {
+          local pid=$1
+          local log_file=$2
+
+          echo "Мониторинг процесса $pid..."
+
+          while kill -0 $pid 2>/dev/null; do
+            NOW=$(date '+%H:%M:%S')
+
+            MEM=$(ps -o rss= -p $pid 2>/dev/null | awk '{print $1/1024 " MB"}' || echo "N/A")
+
+            CPU=$(ps -o pcpu= -p $pid 2>/dev/null || echo "N/A")
+
+            TOTAL_MEM=$(free -m | awk 'NR==2{print $3 " MB / " $2 " MB"}')
+
+            echo "[$NOW] PID: $pid | MEM: $MEM | CPU: $CPU% | System MEM: $TOTAL_MEM" >> $log_file
+
+            sleep 2
+          done
+
+         echo "Процесс $pid завершен" >> $log_file
+         }
+
+        echo "Запуск ACC в фоновом режиме..."
+        "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
+        --model $MODEL \
+        $EXTRA_ARGS > accuracy_$MODEL.txt 2>&1 &
+        ACC_PID=$!
+
+        echo "PID процесса: $ACC_PID"
+
+        monitor_process $ACC_PID $MONITOR_LOG &
+        MONITOR_PID=$!
+
+        wait $ACC_PID
+        EXIT_CODE=$?
+
+        kill $MONITOR_PID 2>/dev/null || true
+
+        echo "Результаты мониторинга:"
+        if [ -f "$MONITOR_LOG" ]; then
+          cat "$MONITOR_LOG"
+        else
+         echo "Лог мониторинга не создан"
+        fi
+
+        echo "Системная информация после запуска:"
+        free -h
+
+        echo "Код завершения: $EXIT_CODE"
+
+        if [ $EXIT_CODE -eq 143 ]; then
+          echo "Ошибка 143 (SIGTERM) - процесс убит системой"
+
+          if sudo dmesg | tail -20 | grep -i "killed process" | grep -q "$ACC_PID"; then
+            echo "Подтверждено: процесс убит OOM Killer"
+            sudo dmesg | tail -20 | grep -i "killed process" | tail -5
+          else
+            echo "Не найдено подтверждение OOM Killer в логах"
+            sudo dmesg | tail -20
+          fi
+
+        elif [ $EXIT_CODE -ne 0 ]; then
+          echo "Ошибка при оценке модели $MODEL (код: $EXIT_CODE)"
+        else
+          echo "Оценка успешно завершена"
+        fi
+
+        echo "Лог ACC:"
+        if [ -f "accuracy_$MODEL.txt" ]; then
+          cat "accuracy_$MODEL.txt"
+        else
+         echo "Файл лога не создан"
+        fi
+
+        # Выход с ошибкой если нужно
+        if [ $EXIT_CODE -ne 0 ]; then
+          exit $EXIT_CODE
+        fi
+
+    - name: Extract accuracy value
+      run: |
+        ACCURACY=$(grep -oE '[0-9]+\.?[0-9]*%' accuracy_${{ matrix.model }}.txt | head -1 || echo "0%")
+        echo "$ACCURACY" > accuracy_value_${{ matrix.model }}.txt
+        echo "Accuracy for ${{ matrix.model }}: $ACCURACY"
+
+    - name: Upload accuracy artifacts
+      uses: actions/upload-artifact@v4
+      with:
+        name: accuracy-${{ matrix.model }}
+        path: |
+          accuracy_${{ matrix.model }}.txt
+          accuracy_value_${{ matrix.model }}.txt
+
+    - name: Update README for model (master only)
+      if: github.ref == 'refs/heads/master'
+      run: |
+        TOP1_ACC=$(grep -oE 'Top-1 Accuracy: [0-9]+\.?[0-9]*%' accuracy_${{ matrix.model }}.txt | grep -oE '[0-9]+\.?[0-9]*')
+        TOP5_ACC=$(grep -oE 'Top-5 Accuracy: [0-9]+\.?[0-9]*%' accuracy_${{ matrix.model }}.txt | grep -oE '[0-9]+\.?[0-9]*')
+        DATE=$(date '+%Y-%m-%d')
+
+        if [ -z "$TOP1_ACC" ] || [ -z "$TOP5_ACC" ]; then
+          echo "Ошибка: Не удалось извлечь точность из файла accuracy_${{ matrix.model }}.txt"
+          cat accuracy_${{ matrix.model }}.txt
+          exit 1
+        fi
+
+        UPDATE_TEXT="<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: Top-1: ${TOP1_ACC}% | Top-5: ${TOP5_ACC}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->"
+
+        if grep -q "<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->" README.md; then
+          sed -i "s|<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->.*<!--END_ACCURACY_${{ matrix.model }}-->|${UPDATE_TEXT}|" README.md
+          echo "Обновлена точность для ${{ matrix.model }} в README"
+        else
+          echo "Ошибка: Плейсхолдер <!--ACCURACY_${{ matrix.model }}_PLACEHOLDER--> не найден в README.md"
+          echo "Содержимое README.md:"
+          cat README.md
+          exit 1
+        fi
+
+    - name: Commit and push changes (main only)
+      if: github.ref == 'refs/heads/main'
+      run: |
+        git config --global user.name "GitHub Actions"
+        git config --global user.email "actions@github.com"
+        git add README.md
+        if git diff-index --quiet HEAD --; then
+          echo "No changes to commit"
+        else
+          git commit -m "[CI] Update accuracy for ${{ matrix.model }}: $(cat accuracy_value_${{ matrix.model }}.txt)"
+          git push origin master
+        fi

README.md

@@ -4,7 +4,21 @@
 # AlexNet-MNIST-Inference
 ## Model Performance
 
-<!--ACCURACY_PLACEHOLDER-->Accuracy: Stat: 98.01% (updated: 2025-04-28)<!--END_ACCURACY-->
+### AlexNet-MNIST Accuracy
+<!--ACCURACY_PLACEHOLDER--><!--END_ACCURACY-->
+
+### GoogLeNet Accuracy
+<!--ACCURACY_googlenet_PLACEHOLDER--><!--END_ACCURACY_googlenet-->
+
+### DenseNet Accuracy
+<!--ACCURACY_densenet_PLACEHOLDER--><!--END_ACCURACY_densenet-->
+
+### ResNet Accuracy
+<!--ACCURACY_resnet_PLACEHOLDER--><!--END_ACCURACY_resnet-->
+
+### YOLO Accuracy
+<!--ACCURACY_yolo_PLACEHOLDER--><!--END_ACCURACY_yolo-->
+
 ## Short description
 A lightweight C++ library for performing high-performance inference on classification tasks. Designed for efficiency and educational purposes, this project demonstrates how classic CNNs can be optimized for small-scale tasks in native environments.
 ### Key Features: