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chore: remove unused .bat files

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16337
2026-01-29 14:04:54 +08:00
parent 942244bd88
commit 4373c77438
18 changed files with 0 additions and 576 deletions
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67
build_engine.bat
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@echo off
chcp 65001 >nul
echo ============================================
echo YOLO INT8 TensorRT Engine Builder
echo ============================================
echo.
REM 激活虚拟环境
echo Activating yolo virtual environment...
call conda activate yolo
echo.
REM 检查ONNX模型
if not exist yolo11n.onnx (
echo ERROR: yolo11n.onnx not found!
echo Please export the ONNX model first.
pause
exit /b 1
)
REM 检查校准缓存
if not exist yolo11n_int8.cache (
echo ERROR: yolo11n_int8.cache not found!
echo Please run calibration_gen.py first to generate the calibration cache.
pause
exit /b 1
)
echo Building TensorRT Engine with INT8 calibration...
echo ONNX: yolo11n.onnx
echo Engine: yolo11n_int8_b1_8.engine
echo Cache: yolo11n_int8.cache
echo.
trtexec ^
--onnx=yolo11n.onnx ^
--saveEngine=yolo11n_int8_b1_8.engine ^
--explicitBatch ^
--int8 ^
--fp16 ^
--workspace=4096 ^
--builderOptimizationLevel=5 ^
--profilingVerbosity=detailed ^
--calib=yolo11n_int8.cache ^
--minShapes=input:1x3x480x640 ^
--optShapes=input:4x3x640x640 ^
--maxShapes=input:8x3x640x736 ^
--useCudaGraph ^
--useSpinWait ^
--noTF32
if %errorlevel% equ 0 (
echo.
echo ============================================
echo Engine built successfully!
echo Output: yolo11n_int8_b1_8.engine
echo ============================================
) else (
echo.
echo ============================================
echo Engine build failed!
echo ============================================
pause
exit /b 1
)
pause

22
build_fp16_480.bat
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@echo off
echo ============================================
echo Build & Test FP16 480p (correct way)
echo ============================================
call conda activate yolo
echo [1/3] Delete old engine...
del /Q yolo11n_fp16_480.engine 2>nul
echo Done.
echo.
echo [2/3] Build FP16 480p engine (static 1x3x480x480)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_fp16_480.engine --explicitBatch --fp16 --minShapes=images:1x3x480x480 --optShapes=images:1x3x480x480 --maxShapes=images:1x3x480x480 --workspace=4096 --noTF32
echo.
echo [3/3] Test FP16 480p...
yolo val model=yolo11n_fp16_480.engine data=coco.yaml imgsz=480 batch=1 device=0 classes=0,1,2,3,5,7 > fp16_480_results.txt 2>&1
echo.
echo Done. Run: python parse_simple.py
pause

20
build_fp16_640.bat
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@echo off
chcp 65001 >nul
echo ============================================
echo Building FP16 640p TensorRT Engine
echo ============================================
echo.
call conda activate yolo
echo Building engine...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_fp16_640.engine --explicitBatch --fp16 --workspace=4096 --builderOptimizationLevel=4 --profilingVerbosity=detailed --optShapes=input:4x3x640x640 --maxShapes=input:8x3x640x640 --useCudaGraph --useSpinWait --noTF32
if %errorlevel% equ 0 (
echo.
echo [SUCCESS] FP16 640p Engine: yolo11n_fp16_640.engine
) else (
echo [FAILED] FP16 640p Engine build failed
)
pause

20
build_int8_480.bat
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@echo off
chcp 65001 >nul
echo ============================================
echo Building INT8 480p TensorRT Engine
echo ============================================
echo.
call conda activate yolo
echo Building engine...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_int8_480.engine --explicitBatch --int8 --fp16 --workspace=4096 --builderOptimizationLevel=4 --profilingVerbosity=detailed --calib=yolo11n_int8_480.cache --optShapes=input:4x3x480x480 --maxShapes=input:8x3x480x480 --minShapes=input:1x3x480x480 --useCudaGraph --useSpinWait --noTF32
if %errorlevel% equ 0 (
echo.
echo [SUCCESS] INT8 480p Engine: yolo11n_int8_480.engine
) else (
echo [FAILED] INT8 480p Engine build failed
)
pause

40
clean_test.bat
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@@ -1,40 +0,0 @@
@echo off
echo ============================================
echo Clean Build & Test: FP16 480p
echo ============================================
call conda activate yolo
echo [1/4] Delete old engine and results...
del /Q yolo11n_fp16_480.engine 2>nul
del /Q fp16_480_results.txt 2>nul
echo Done.
echo.
echo [2/4] Build FP16 480p (static, no dynamic shapes)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_fp16_480.engine --fp16 --workspace=4096 --noTF32
echo Done.
echo.
echo [3/4] Test FP16 480p...
yolo val model=yolo11n_fp16_480.engine data=coco.yaml imgsz=480 batch=1 device=0 classes=0,1,2,3,5,7 > fp16_480_results.txt 2>&1
echo Done.
echo.
echo [4/4] Check results...
python -c "
import re
with open('fp16_480_results.txt','r') as f:
content = f.read()
if 'Error' in content or 'error' in content:
print('ERROR: Validation failed')
else:
m = re.search(r'Speed:.*?([\d.]+)ms.*?([\d.]+)ms inference', content, re.DOTALL)
if m:
print(f'OK: {m.group(2)}ms inference')
else:
print('No speed data found')
"
echo.
echo Done. Run: python parse_simple.py
pause

18
export_and_test.bat
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@echo off
echo ============================================
echo Build FP16 480p using Ultralytics export
echo (includes required metadata)
echo ============================================
call conda activate yolo
echo [1/2] Export FP16 480p engine with metadata...
yolo export model=yolo11n.pt format=engine imgsz=480 device=0 half=True
echo.
echo [2/2] Test FP16 480p...
yolo val model=yolo11n.engine data=coco.yaml imgsz=480 batch=1 device=0 classes=0,1,2,3,5,7 > fp16_480_results.txt 2>&1
echo.
echo Done. Run: python parse_simple.py
pause

21
fix_fp16_engine.bat
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@echo off
echo ============================================
echo Rebuild FP16-480p with Ultralytics export
echo (includes required metadata for yolo val)
echo ============================================
call conda activate yolo
echo [1/2] Delete old engine...
del /Q yolo11n_fp16_480.engine 2>nul
echo Done.
echo.
echo [2/2] Build FP16-480p engine with yolo export...
yolo export model=yolo11n.pt format=engine imgsz=480 device=0 half=True
echo.
echo Engine built: yolo11n_fp16_480.engine
echo.
echo Now run: full_coco_benchmark.bat
pause

27
full_coco_benchmark.bat
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@echo off
echo ============================================
echo Full COCO Benchmark: FP16-480p vs INT8-640p
echo Dataset: COCO val2017 (5000 images)
echo No class filtering - full 80 classes
echo ============================================
call conda activate yolo
echo [1/3] Build FP16 480p engine (if not exists)...
if not exist yolo11n_fp16_480.engine (
yolo export model=yolo11n.pt format=engine imgsz=480 device=0 half=True
) else (
echo FP16 480p engine already exists
)
echo.
echo [2/3] Test FP16 480p (full COCO, no classes filter)...
yolo val model=yolo11n_fp16_480.engine data=coco.yaml imgsz=480 batch=1 device=0 > fp16_480_full_results.txt 2>&1
echo.
echo [3/3] Test INT8 640p (full COCO, no classes filter)...
yolo val model=yolo11n_int8_b1_8.engine data=coco.yaml imgsz=640 batch=1 device=0 > int8_640_full_results.txt 2>&1
echo.
echo Done. Run: python parse_full_coco.py
pause

33
rebuild_engines.bat
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@echo off
echo ============================================
echo Rebuilding TensorRT engines with batch 1-8
echo ============================================
call conda activate yolo
echo.
echo [1/5] Building INT8 640p (batch 1-8)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_int8_b1_8.engine --explicitBatch --int8 --fp16 --workspace=4096 --builderOptimizationLevel=4 --calib=yolo11n_int8.cache --minShapes=input:1x3x640x640 --optShapes=input:4x3x640x640 --maxShapes=input:8x3x640x640 --useCudaGraph --useSpinWait --noTF32
echo Done.
echo.
echo [2/5] Building FP16 640p (batch 1-8)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_fp16_640.engine --explicitBatch --fp16 --workspace=4096 --builderOptimizationLevel=4 --minShapes=input:1x3x640x640 --optShapes=input:4x3x640x640 --maxShapes=input:8x3x640x640 --useCudaGraph --useSpinWait --noTF32
echo Done.
echo.
echo [3/5] Building INT8 480p (batch 1-8)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_int8_480.engine --explicitBatch --int8 --fp16 --workspace=4096 --builderOptimizationLevel=4 --calib=yolo11n_int8_480.cache --minShapes=input:1x3x480x480 --optShapes=input:4x3x480x480 --maxShapes=input:8x3x480x480 --useCudaGraph --useSpinWait --noTF32
echo Done.
echo.
echo [4/5] Building FP16 480p (batch 1-8)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_fp16_480.engine --explicitBatch --fp16 --workspace=4096 --builderOptimizationLevel=4 --minShapes=input:1x3x480x480 --optShapes=input:4x3x480x480 --maxShapes=input:8x3x480x480 --useCudaGraph --useSpinWait --noTF32
echo Done.
echo.
echo ============================================
echo All engines rebuilt!
echo Now run: run_all_benchmarks.bat
echo ============================================
pause

28
rebuild_fp16.bat
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@echo off
echo ============================================
echo Rebuilding FP16 engines with batch=1 support
echo ============================================
call conda activate yolo
echo.
echo [1/3] Rebuilding FP16 640p (batch 1-8)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_fp16_640.engine --explicitBatch --fp16 --workspace=4096 --builderOptimizationLevel=4 --minShapes=input:1x3x640x640 --optShapes=input:4x3x640x640 --maxShapes=input:8x3x640x640 --useCudaGraph --useSpinWait --noTF32
echo Done.
echo.
echo [2/3] Rebuilding FP16 480p (batch 1-8)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_fp16_480.engine --explicitBatch --fp16 --workspace=4096 --builderOptimizationLevel=4 --minShapes=input:1x3x480x480 --optShapes=input:4x3x480x480 --maxShapes=input:8x3x480x480 --useCudaGraph --useSpinWait --noTF32
echo Done.
echo.
echo [3/3] Rebuilding INT8 640p (batch 1-8)...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_int8_b1_8.engine --explicitBatch --int8 --fp16 --workspace=4096 --builderOptimizationLevel=4 --calib=yolo11n_int8.cache --minShapes=input:1x3x640x640 --optShapes=input:4x3x640x640 --maxShapes=input:8x3x640x640 --useCudaGraph --useSpinWait --noTF32
echo Done.
echo.
echo ============================================
echo All engines rebuilt!
echo Now run: run_correct_benchmark.bat
echo ============================================
pause

29
run_all_benchmarks.bat
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@echo off
echo ============================================
echo YOLO11n Person and Vehicle Detection Benchmark
echo ============================================
call conda activate yolo
echo [1/4] Testing FP32...
yolo val model=yolo11n.pt data=coco_person_vehicle.yaml imgsz=640 rect=False batch=1 > fp32_results.txt 2>&1
echo Done: fp32_results.txt
echo [2/4] Testing INT8 640p...
yolo val model=yolo11n_int8_b1_8.engine data=coco_person_vehicle.yaml imgsz=640 rect=False batch=1 > int8_640_results.txt 2>&1
echo Done: int8_640_results.txt
echo [3/4] Testing FP16 640p...
yolo val model=yolo11n_fp16_640.engine data=coco_person_vehicle.yaml imgsz=640 rect=False batch=1 > fp16_640_results.txt 2>&1
echo Done: fp16_640_results.txt
echo [4/4] Testing FP16 480p...
yolo val model=yolo11n_fp16_480.engine data=coco_person_vehicle.yaml imgsz=480 rect=False batch=1 > fp16_480_results.txt 2>&1
echo Done: fp16_480_results.txt
echo.
echo ============================================
echo All validation tests completed!
echo Now run: python parse_results.py
echo ============================================
pause

34
run_correct_benchmark.bat
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@echo off
echo ============================================
echo YOLO11n Benchmark - Person & Vehicle Only
echo Classes: 0(person),1(bicycle),2(car),3(motorcycle),5(bus),7(truck)
echo ============================================
echo.
call conda activate yolo
echo [1/4] Testing FP32 (PyTorch)...
yolo val model=yolo11n.pt data=coco.yaml imgsz=640 batch=1 device=0 classes=0,1,2,3,5,7 > fp32_results.txt 2>&1
echo Done: fp32_results.txt
echo.
echo [2/4] Testing INT8 640p...
yolo val model=yolo11n_int8_b1_8.engine data=coco.yaml imgsz=640 batch=1 device=0 classes=0,1,2,3,5,7 > int8_640_results.txt 2>&1
echo Done: int8_640_results.txt
echo.
echo [3/4] Testing FP16 640p...
yolo val model=yolo11n_fp16_640.engine data=coco.yaml imgsz=640 batch=1 device=0 classes=0,1,2,3,5,7 > fp16_640_results.txt 2>&1
echo Done: fp16_640_results.txt
echo.
echo [4/4] Testing FP16 480p...
yolo val model=yolo11n_fp16_480.engine data=coco.yaml imgsz=480 batch=1 device=0 classes=0,1,2,3,5,7 > fp16_480_results.txt 2>&1
echo Done: fp16_480_results.txt
echo.
echo ============================================
echo All validation tests completed!
echo Now run: python parse_final.py
echo ============================================
pause

34
run_full_analysis.bat
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@echo off
echo ============================================
echo Complete Comparison Analysis
echo ============================================
echo.
call conda activate yolo
echo.
echo [1/4] Running all validation tests...
echo.
call run_all_benchmarks.bat
echo.
echo [2/4] Parsing results and generating report...
echo.
python parse_results.py
echo.
echo [3/4] Generating visualization charts...
echo.
python generate_charts.py
echo.
echo ============================================
echo [4/4] Done!
echo ============================================
echo.
echo Results saved to: vehicle_person_benchmark\
echo - final_report.txt (detailed report)
echo - benchmark_charts.png (charts)
echo - all_results.json (raw data)
pause

94
run_full_workflow.bat
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@echo off
chcp 65001 >nul
echo ============================================
echo YOLO INT8 Quantization Complete Workflow
echo ============================================
echo.
REM 激活虚拟环境
echo [1/4] Activating yolo virtual environment...
call conda activate yolo
echo.
REM 步骤1: 检查并导出ONNX模型
echo [2/4] Checking ONNX model...
if not exist yolo11n.onnx (
echo ONNX model not found. Exporting from yolo11n.pt...
if not exist yolo11n.pt (
echo ERROR: yolo11n.pt not found!
echo Please place yolo11n.pt in the current directory.
pause
exit /b 1
)
python -c "from ultralytics import YOLO; model = YOLO('yolo11n.pt'); model.export(format='onnx', dynamic=True, simplify=True, opset=12)"
if not exist yolo11n.onnx (
echo ERROR: ONNX export failed!
pause
exit /b 1
)
echo ONNX model exported successfully.
) else (
echo ONNX model already exists: yolo11n.onnx
)
echo.
REM 步骤2: 生成校准缓存
echo [3/4] Generating calibration cache...
if not exist yolo11n_int8.cache (
echo Running calibration_gen.py...
python calibration_gen.py
if not exist yolo11n_int8.cache (
echo ERROR: Calibration cache generation failed!
pause
exit /b 1
)
echo Calibration cache generated: yolo11n_int8.cache
) else (
echo Calibration cache already exists: yolo11n_int8.cache
)
echo.
REM 步骤3: 构建TensorRT Engine
echo [4/4] Building TensorRT Engine...
echo.
echo Running trtexec with INT8 calibration...
echo.
trtexec ^
--onnx=yolo11n.onnx ^
--saveEngine=yolo11n_int8_b1_8.engine ^
--explicitBatch ^
--int8 ^
--fp16 ^
--workspace=4096 ^
--builderOptimizationLevel=5 ^
--profilingVerbosity=detailed ^
--calib=yolo11n_int8.cache ^
--minShapes=input:1x3x640x640 ^
--optShapes=input:4x3x640x640 ^
--maxShapes=input:8x3x640x640 ^
--useCudaGraph ^
--useSpinWait ^
--noTF32
if %errorlevel% equ 0 (
echo.
echo ============================================
echo TensorRT Engine built successfully!
echo Output: yolo11n_int8_b1_8.engine
echo ============================================
echo.
echo Next steps:
echo 1. Run: python quantize_yolo.py
echo to validate models and calculate mAP drop
echo.
) else (
echo.
echo ============================================
echo Engine build failed!
============================================
pause
exit /b 1
)
pause

13
test_engine_trtexec.bat
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@echo off
echo ============================================
echo Test FP16 480p engine with trtexec
echo ============================================
call conda activate yolo
echo [TEST] Direct inference with trtexec...
trtexec --loadEngine=yolo11n_fp16_480.engine --shapes=images:1x3x480x480 --iterations=10 --noDataTransfers --useCudaGraph
echo.
echo Done.
pause

17
test_speed_trtexec.bat
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@@ -1,17 +0,0 @@
@echo off
echo ============================================
echo TensorRT Engine Benchmark
echo Run after: conda activate yolo
echo ============================================
echo.
echo [1] INT8-640p Speed Test...
trtexec --loadEngine=yolo11n_int8_b1_8.engine --shapes=images:1x3x640x640 --iterations=100
echo.
echo [2] FP16-480p Speed Test...
trtexec --loadEngine=yolo11n_fp16_480.engine --shapes=images:1x3x480x480 --iterations=100
echo.
echo Done.
pause

17
test_two_engines.bat
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@@ -1,17 +0,0 @@
@echo off
echo ============================================
echo Build FP16 480p + Test FP16 480p
echo ============================================
call conda activate yolo
echo [1/2] Building FP16 480p engine...
trtexec --onnx=yolo11n.onnx --saveEngine=yolo11n_fp16_480.engine --explicitBatch --fp16 --workspace=4096 --builderOptimizationLevel=4 --minShapes=images:1x3x480x480 --optShapes=images:4x3x480x480 --maxShapes=images:8x3x480x480 --useCudaGraph --useSpinWait --noTF32
echo.
echo [2/2] Testing FP16 480p...
yolo val model=yolo11n_fp16_480.engine data=coco.yaml imgsz=480 batch=1 device=0 classes=0,1,2,3,5,7 > fp16_480_results.txt 2>&1
echo.
echo Done. Run: python parse_simple.py
pause

42
validate_int8.bat
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@@ -1,42 +0,0 @@
@echo off
chcp 65001 >nul
echo ============================================
echo YOLO INT8 TensorRT Validation Script
echo ============================================
echo.
REM 激活虚拟环境
echo Activating yolo virtual environment...
call conda activate yolo
echo.
REM 检查engine文件
if not exist yolo11n_int8_b1_8.engine (
echo ERROR: yolo11n_int8_b1_8.engine not found!
echo Please build the engine first using: build_engine.bat
pause
exit /b 1
)
echo Validating INT8 TensorRT Engine with COCO dataset...
echo Engine: yolo11n_int8_b1_8.engine
echo.
REM 使用rect=False确保输入尺寸为640x640
yolo val model=yolo11n_int8_b1_8.engine data=coco.yaml imgsz=640 rect=False
if %errorlevel% equ 0 (
echo.
echo ============================================
echo Validation completed successfully!
echo ============================================
) else (
echo.
echo ============================================
echo Validation failed!
echo ============================================
pause
exit /b 1
)
pause