18 KiB
18 KiB
Build code
前置作業
CMake && Visual Studio
-
下載OpenCV:opencv
-
解壓縮後放到
D:\temp\build_opencv\opencv-4.5.3\source -
建立
D:\temp\build_opencv\opencv-4.5.3\build -
下載OpenCV contrib:opencv_contrib
-
解壓縮後放到
D:\temp\build_opencv\opencv_contrib -
打開cmake-gui
-
用
Add Entry先加入以下define !
如果是檔名,type就選FILEPATH,如果是目錄,type就選PATH- PYTHON3_EXECUTABLE=C:/python39/python.exe
- PYTHON3_INCLUDE_DIR=C:/python39/include
- PYTHON3_LIBRARY=C:/python39/libs/python39.lib
- PYTHON3_NUMPY_INCLUDE_DIRS=C:/python39/Lib/site-packages/numpy/core/include
- PYTHON3_PACKAGES_PATH=C:/python39/Lib/site-packages
如果要build win32 + Python 3.6.3 x86的話,改為以下設定:
- PYTHON3_EXECUTABLE=C:/Python363/python.exe
- PYTHON3_INCLUDE_DIR=C:/Python363/include
- PYTHON3_LIBRARY=C:/Python363/libs/python36.lib
- PYTHON3_NUMPY_INCLUDE_DIRS=C:/Python363/Lib/site-packages/numpy/core/include
- PYTHON3_PACKAGES_PATH=C:/Python363/Lib/site-packages
-
這些要打勾
- BUILD_opencv_world
- BUILD_opencv_python3
- OPENCV_DNN_CUDA
- OPENCV_PYTHON3_VERSION
- OPENCV_FORCE_PYTHON_LIBS
- OPENCV_ENABLE_NONFREE
- ENABLE_FAST_MATH
- WITH_CUDA
- WITH_OPENMP
- OPENCV_EXTRA_MODULES_PATH=D:/temp/build_opencv/opencv_contrib/modules
-
再按一次Configure,必須沒有錯誤的跑完,像是
General configuration for OpenCV 4.5.3 ===================================== Version control: unknown Extra modules: Location (extra): D:/temp/build_opencv/opencv_contrib/modules Version control (extra): 4.5.3-6-g907efb96 Platform: Timestamp: 2021-08-18T03:40:06Z Host: Windows 10.0.19043 AMD64 CMake: 3.21.1 CMake generator: Visual Studio 16 2019 CMake build tool: C:/Program Files (x86)/Microsoft Visual Studio/2019/Professional/MSBuild/Current/Bin/MSBuild.exe MSVC: 1929 Configuration: Debug Release CPU/HW features: Baseline: SSE SSE2 SSE3 requested: SSE3 Dispatched code generation: SSE4_1 SSE4_2 FP16 AVX AVX2 AVX512_SKX requested: SSE4_1 SSE4_2 AVX FP16 AVX2 AVX512_SKX SSE4_1 (17 files): + SSSE3 SSE4_1 SSE4_2 (2 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 (1 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 AVX AVX (5 files): + SSSE3 SSE4_1 POPCNT SSE4_2 AVX AVX2 (31 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2 AVX512_SKX (7 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2 AVX_512F AVX512_COMMON AVX512_SKX C/C++: Built as dynamic libs?: YES C++ standard: 11 C++ Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2019/Professional/VC/Tools/MSVC/14.29.30037/bin/Hostx64/x64/cl.exe (ver 19.29.30040.0) C++ flags (Release): /DWIN32 /D_WINDOWS /W4 /GR /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS /Gy /bigobj /Oi /fp:fast /EHa /wd4127 /wd4251 /wd4324 /wd4275 /wd4512 /wd4589 /MP /MD /O2 /Ob2 /DNDEBUG C++ flags (Debug): /DWIN32 /D_WINDOWS /W4 /GR /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS /Gy /bigobj /Oi /fp:fast /EHa /wd4127 /wd4251 /wd4324 /wd4275 /wd4512 /wd4589 /MP /MDd /Zi /Ob0 /Od /RTC1 C Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2019/Professional/VC/Tools/MSVC/14.29.30037/bin/Hostx64/x64/cl.exe C flags (Release): /DWIN32 /D_WINDOWS /W3 /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS /Gy /bigobj /Oi /fp:fast /MP /MD /O2 /Ob2 /DNDEBUG C flags (Debug): /DWIN32 /D_WINDOWS /W3 /D _CRT_SECURE_NO_DEPRECATE /D _CRT_NONSTDC_NO_DEPRECATE /D _SCL_SECURE_NO_WARNINGS /Gy /bigobj /Oi /fp:fast /MP /MDd /Zi /Ob0 /Od /RTC1 Linker flags (Release): /machine:x64 /INCREMENTAL:NO Linker flags (Debug): /machine:x64 /debug /INCREMENTAL ccache: NO Precompiled headers: NO Extra dependencies: cudart_static.lib nppc.lib nppial.lib nppicc.lib nppidei.lib nppif.lib nppig.lib nppim.lib nppist.lib nppisu.lib nppitc.lib npps.lib cublas.lib cudnn.lib cufft.lib -LIBPATH:C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.4/lib/x64 3rdparty dependencies: OpenCV modules: To be built: aruco barcode bgsegm bioinspired calib3d ccalib core cudaarithm cudabgsegm cudacodec cudafeatures2d cudafilters cudaimgproc cudalegacy cudaobjdetect cudaoptflow cudastereo cudawarping cudev datasets dnn dnn_objdetect dnn_superres dpm face features2d flann fuzzy gapi hfs highgui img_hash imgcodecs imgproc intensity_transform line_descriptor mcc ml objdetect optflow phase_unwrapping photo plot python3 quality rapid reg rgbd saliency shape stereo stitching structured_light superres surface_matching text tracking ts video videoio videostab wechat_qrcode world xfeatures2d ximgproc xobjdetect xphoto Disabled: - Disabled by dependency: - Unavailable: alphamat cvv freetype hdf java julia matlab ovis python2 python2 sfm viz Applications: tests perf_tests apps Documentation: NO Non-free algorithms: NO Windows RT support: NO GUI: Win32 UI: YES VTK support: NO Media I/O: ZLib: build (ver 1.2.11) JPEG: build-libjpeg-turbo (ver 2.1.0-62) WEBP: build (ver encoder: 0x020f) PNG: build (ver 1.6.37) TIFF: build (ver 42 - 4.2.0) JPEG 2000: build (ver 2.4.0) OpenEXR: build (ver 2.3.0) HDR: YES SUNRASTER: YES PXM: YES PFM: YES Video I/O: DC1394: NO FFMPEG: YES (prebuilt binaries) avcodec: YES (58.134.100) avformat: YES (58.76.100) avutil: YES (56.70.100) swscale: YES (5.9.100) avresample: YES (4.0.0) GStreamer: NO DirectShow: YES Media Foundation: YES DXVA: YES Parallel framework: Concurrency Trace: YES (with Intel ITT) Other third-party libraries: Intel IPP: 2020.0.0 Gold [2020.0.0] at: D:/temp/build_opencv/opencv-4.5.3/build/3rdparty/ippicv/ippicv_win/icv Intel IPP IW: sources (2020.0.0) at: D:/temp/build_opencv/opencv-4.5.3/build/3rdparty/ippicv/ippicv_win/iw Lapack: NO Eigen: NO Custom HAL: NO Protobuf: build (3.5.1) NVIDIA CUDA: YES (ver 11.4, CUFFT CUBLAS) NVIDIA GPU arch: 35 37 50 52 60 61 70 75 80 86 NVIDIA PTX archs: cuDNN: YES (ver 8.2.2) OpenCL: YES (NVD3D11) Include path: D:/temp/build_opencv/opencv-4.5.3/source/3rdparty/include/opencl/1.2 Link libraries: Dynamic load Python 3: Interpreter: C:/python39/python.exe (ver 3.9.6) Libraries: C:/python39/libs/python39.lib (ver 3.9.6) numpy: C:/python39/Lib/site-packages/numpy/core/include (ver 1.19.5) install path: C:/python39/Lib/site-packages/cv2/python-3.9 Python (for build): C:/python39/python.exe Java: ant: NO JNI: NO Java wrappers: NO Java tests: NO Install to: D:/temp/build_opencv/opencv-4.5.3/build/install ----------------------------------------------------------------- Configuring done -
按下Generate按鈕就會生sln檔案。
CMake by command
用command line的話就可以將多個平台一次編起來,不用一直改GUI。
寫了一個build.bat可以編譯不同版本與平台:
rem build.bat
echo on
rem build.bat
rem win32 ARCH=%1, win32/x64
rem 15 VS_CODE=%2, 15/16
rem 2017 VS_VERSION=%3, 2017/2019
rem DEBUG BUILD_TYPE=%4, DEBUG/RELEASE
rem "C:/Python363/python.exe" PYTHON3_EXE=%5
rem "C:/Python363/include" PYTHON3_INCLUDE=%6
rem "C:/Python363/libs/python36.lib" PYTHON3_LIB=%7
rem "C:/Python363/Lib/site-packages/numpy/core/include" PYTHON3_NP_INCLUDE=%8
rem "C:/Python363/Lib/site-packages" PYTHON3_PACKAGES=%9
rem 3.6.3 PY_VERSION=%10
rem 1 CLEAN_BUILD=%11, 1: Delete build folder, 0: Do nothing
set DO_CONFIG=1
set DO_BUILD=1
set ARCH=%1
set VS_CODE=%2
set VS_VERSION=%3
set BUILD_TYPE=%4
set PYTHON3_EXE=%5
set PYTHON3_INCLUDE=%6
set PYTHON3_LIB=%7
set PYTHON3_NP_INCLUDE=%8
set PYTHON3_PACKAGES=%9
set GENERATOR="Visual Studio %VS_CODE% %VS_VERSION%"
shift
set PY_VERSION=%9
set CV_VERSION=4.5.3
set CV_SOURCE="opencv-%CV_VERSION%\source"
set CV_BUILD=build\vs%VS_VERSION%.%ARCH%.%BUILD_TYPE%
set CV_EXTRA_MODULES="opencv_contrib\modules"
shift
set CLEAN_BUILD=%9
if %CLEAN_BUILD% == 1 (
rmdir /s /q %CV_BUILD%
)
if %DO_CONFIG% == 1 (
mkdir %CV_BUILD%
"C:\Program Files\CMake\bin\cmake.exe" ^
-B%CV_BUILD% ^
-H%CV_SOURCE% ^
-G%GENERATOR% ^
-A%ARCH% ^
-DCMAKE_BUILD_TYPE=%BUILD_TYPE% ^
-DOPENCV_EXTRA_MODULES_PATH=%CV_EXTRA_MODULES% ^
-DCMAKE_INSTALL_PREFIX=%CV_BUILD% ^
-DINSTALL_PYTHON_EXAMPLES=OFF ^
-DINSTALL_C_EXAMPLES=OFF ^
-DBUILD_opencv_python3=ON ^
-DPYTHON3_EXECUTABLE=%PYTHON3_EXE% ^
-DPYTHON3_INCLUDE_DIR=%PYTHON3_INCLUDE% ^
-DPYTHON3_LIBRARY=%PYTHON3_LIB% ^
-DPYTHON3_NUMPY_INCLUDE_DIRS=%PYTHON3_NP_INCLUDE% ^
-DPYTHON3_PACKAGES_PATH=%PYTHON3_PACKAGES% ^
-DOPENCV_PYTHON3_VERSION=%PY_VERSION% ^
-DOPENCV_FORCE_PYTHON_LIBS=ON ^
-DBUILD_opencv_world=ON ^
-DOPENCV_ENABLE_NONFREE=ON ^
-DENABLE_FAST_MATH=ON ^
-DWITH_OPENMP=ON ^
-DWITH_OPENGL=ON
)
if %DO_BUILD% == 1 (
"C:\Program Files\CMake\bin\cmake.exe" --build %CV_BUILD% --target INSTALL --config %BUILD_TYPE%
)
這樣以後就可以用參數的方法來設定,譬如要使用vs2019來編譯x64 release的話,就可以這樣下:
rem build_vs2019.x64.RELEASE.bat
echo off
rem ----------------------------------------------------------------------------------------------------
rem
rem x64, RELEASE, 2019, CLEAN
rem
set ARCH=x64
set VS_CODE=16
set VS_VERSION=2019
set BUILD_TYPE=RELEASE
set PYTHON3_EXE="C:/Python39/python.exe"
set PYTHON3_INCLUDE="C:/Python39/include"
set PYTHON3_LIB="C:/Python39/libs/python39.lib"
set PYTHON3_NP_INCLUDE="C:/Python39/Lib/site-packages/numpy/core/include"
set PYTHON3_PACKAGES="C:/Python39/Lib/site-packages"
set PY_VERSION=3.9
set CLEAN_BUILD=1
echo "============================================================"
echo "Build %ARCH%.%VS_VERSION%(%VS_CODE%).%BUILD_TYPE%, Python=%PY_VERSION%, CLEAN_BUILD=%CLEAN_BUILD%"
echo ""
call build.bat ^
%ARCH% %VS_CODE% %VS_VERSION% %BUILD_TYPE% %PYTHON3_EXE% ^
%PYTHON3_INCLUDE% %PYTHON3_LIB% %PYTHON3_NP_INCLUDE% %PYTHON3_PACKAGES% ^
%PY_VERSION% %CLEAN_BUILD%
rem ----------------------------------------------------------------------------------------------------
參考
- Build OpenCV GPU Version On Windows 10
- Cannot install openCV 3.1.0 with python3. CMAKE not including or linking python correctly
- 在Windows上编译带CUDA(GPU)的OpenCV
- How to use OpenCV DNN Module with Nvidia GPU on Windows
- Accelerate OpenCV 4.5.0 on Windows – build with CUDA and python bindings - James Bowley
影像處理
- sift
def adjust_gamma(image, gamma=1.0): invGamma = 1.0 / gamma table = np.array([((i / 255.0) ** invGamma) * 255 for i in np.arange(0, 256)]).astype("uint8") return cv2.LUT(image, table) def sift_compare(path_a, path_b): ''' Use SIFT features to measure image similarity @args: {str} path_a: the path to an image file {str} path_b: the path to an image file @returns: TODO ''' # initialize the sift feature detector orb = cv2.ORB_create() # get the images img_a = cv2.imread(path_a) img_b = cv2.imread(path_b) img_a = adjust_gamma(img_a, 0.1) img_b = adjust_gamma(img_b, 0.1) # find the keypoints and descriptors with SIFT kp_a, desc_a = orb.detectAndCompute(img_a, None) kp_b, desc_b = orb.detectAndCompute(img_b, None) # print(f'len kp_a = {len(kp_a)}, len desc_a = {len(desc_a)}') # print(f'type kp_b = {type(kp_b)}, type desc_b = {type(desc_b)}') # print(f'len kp_b = {len(kp_b)}, len desc_b = {len(desc_b) if desc_b else 0}') if desc_a is None or desc_b is None: # rr.LOG('Error: desc_a = {}, desc_b = {}'.format(type(desc_a), type(desc_b))) # rr.LOG('Error: Return score 0.') return 0 # Initialize the bruteforce matcher bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True) # match.distance is a float between {0:100} - lower means more similar matches = bf.match(desc_a, desc_b) similar_regions = [i for i in matches if i.distance < 70] # print('Length of similar_regions = {}'.format(len(similar_regions))) # print('Length of matches = {}'.format(len(matches))) sorted_matches = sorted(matches, key = lambda x:x.distance) good_matches = sorted_matches[:int(len(sorted_matches) * 0.5)] similar_regions2 = [i for i in good_matches if i.distance < 70] # print('Length of good_matches = {}'.format(len(good_matches))) if len(matches) == 0: return 0 return len(similar_regions) / len(matches)
Color tempertature
code
img1 = cv2.imread(file)
B, G, R = cv2.split(img1)
avgB = cv2.mean(B)[0]
avgG = cv2.mean(G)[0]
avgR = cv2.mean(R)[0]
# X = avgR * -0.14282 + avgG * 1.54924 + avgB * -0.95641
# Y = avgR * -0.32466 + avgG * 1.57837 + avgB * -0.73191
# Z = avgR * -0.68202 + avgG * 0.77073 + avgB * 0.56332
X = 2.789 * avgR + 1.7517 * avgG + 1.1302 * avgB
Y = 1 * avgR + 4.5907 * avgG + 0.0601 * avgB
Z = 0 * avgR + 0.0565 * avgG + 5.5943 * avgB
x = X / (X + Y + Z)
y = Y / (X + Y + Z)
n = (x - 0.3320) / (0.1858 - y)
# n = (0.23881 * avgR + 0.25499 * avgG + -0.58291 * avgB) / (0.11109 * avgR + -0.85406 * avgG + 0.52289 * avgB)
CCT = 449 * pow(n, 3) + 3525 * pow(n, 2) + 6823.3 * n + 5520.33
# CCT = 437 * pow(n, 3) + 3601 * pow(n, 2) + 6831 * n + 5517
# print(f'x = {x}')
# print(f'y = {y}')
# print(f'n = {n}')
print(f'{file}: CCT = {CCT}')
- How to Calculate the Color Temperature / Tint of the Colors in an Image?
- Calculating Color Temperature and Illuminance using the TAOS TCS3414CS Digital Color Sensor_
- Java RGB转色温(CCT)
- Calculate color temperature (CCT) from CIE 1931 xy coordinates
- OpenCV: Color conversions
- sRGB色彩空間 - 維基百科,自由的百科全書
- Color temperature - Wikipedia
- What color is a blackbody? - some pixel rgb values

