Mac编译问题: ffmpeg依赖和opencv动态库 #203
Comments
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我没有在windows编译过，你可以看一下别人是怎么解决的。 References for Windows10 userswindows下的使用可以参考以下这几个讨论(some references for windows users)
另外,是win32和system32，目前lite.ai.toolkit没有考虑32位的系统。还有就是在windows下编译完之后，需要手动把依赖库都拷贝到build/lite.ai.toolkit/lib和build/lite.ai.toolkit/bin，并且检查修改下模型文件的路径，比如说路径的反斜杠之类的。(Also, for win32 and system32, currently, lite.ai.toolkit does not consider 32-bit systems. Also, after compiling under Windows, you need to manually copy the dependent libraries to build/lite.ai.toolkit/lib and build/lite.ai.toolkit/bin, and check and modify the path of the model file, for example, The backslash of the path.) Search issues about windows
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你这里看起来几乎都是onnxruntime的问题，应该某些转换被禁用了，导致编译通不过 |
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我就是把opecv和onnxruntime下载下来，然后把相应的文件拷到lite.ai.toolkit里面，然后build，build成功了，就是make -j8的时候就开始报错。 |
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我不太懂为啥build成功了还要make? 不是cmake + make之后才会build成功吗。windows的命令行感觉不太好使啊，windows建议采用 cmake+clion的方式，将opencv和onnxruntime的dll下载下来放在lite.ai.toolkit/lib,并删除原来的dylib(这是mac的)，用clion来打开工程，设置编译工具链设置为vs2017对应的，尝试在clion中加载lite.ai.toolkit根目录的CMakeLists.txt初始化工程（注意要记得先将CMakeLists.txt中的ENABLE_MNN/ENABLE_TNN/ENABLE_NCNN都先手动指定为OFF，因为windows下无法使用我写好的build.sh，build.sh是有默认设置的，所以在win只能手动改），看一下cmake输出的各个message是否正常。然后初始化成功后，点击右上角的build，进行编译。其实编译逻辑都写在CMakeLists.txt了，有问题可以看看CMakeLists.txt。编译完的lite.ai.toolkit.dll会在build/lite.ai.toolkit/lib目录下，使用时，需要把opencv、onnxruntime、lite.ai.toolkit的dll都放在同一个目录下 |
emm,是我说错了，就是运行build.sh cmake成功了，然后make -j8 报错了。。。 |
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你这里看起来是编译器禁用了某些选项，导致onnxruntime的链接有问题，我看到连execption都被禁用了。具体我就不清楚了。 |
哥，我换了个mac 编译还是有点问题，能帮我看看是啥问题吗 |
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链接不到动态库。为什么会用到opencv_dnn这个库呢？应该是不需要的啊 |
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你在mac下直接运行 sh ./build.sh 应该就可以编译了。我这边都是这样编译的。 |
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我感觉我帮不了你了，不知道你的系统到底啥问题..... |
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你在mac是怎么编译的？太奇怪了，因为我是在Mac下开发的，所以我觉得mac下是不太可能出问题的啊。 |
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我在mac下的编译log: ➜ github git clone --depth=1 https://github.com/DefTruth/lite.ai.toolkit.git
Cloning into 'lite.ai.toolkit'...
remote: Enumerating objects: 1453, done.
remote: Counting objects: 100% (1453/1453), done.
remote: Compressing objects: 100% (989/989), done.
remote: Total 1453 (delta 585), reused 1136 (delta 431), pack-reused 0
Receiving objects: 100% (1453/1453), 291.42 MiB | 16.53 MiB/s, done.
Resolving deltas: 100% (585/585), done.
Checking out files: 100% (1407/1407), done.
➜ github cd lite.ai.toolkit
➜ lite.ai.toolkit git:(main) sh ./build.sh
build directory exist! clearing ...
clear built files done ! & rebuilding ...
-- The C compiler identification is AppleClang 10.0.1.10010046
-- The CXX compiler identification is AppleClang 10.0.1.10010046
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/cc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
########## Checking Platform for: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit ###########
==================================== Lite.AI.ToolKit 0.1.0 =============================
Project: lite.ai.toolkit
Version: 0.1.0
SO Version: 0.1.0
Build Type: MinSizeRel
Platform Name: macos
Root Path: /Users/qiuyanjun/Desktop/third_party/github/lite.ai.toolkit
================================================================================
################################### Engines Enable Details ... #######################################
-- INCLUDE_OPENCV: ON
-- ENABLE_ONNXRUNTIME: ON
-- ENABLE_MNN: OFF
-- ENABLE_NCNN: OFF
-- ENABLE_TNN: OFF
######################################################################################################
########## Setting up OpenCV libs for: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit ###########
###########################################################################################
Installing Lite.AI.ToolKit Headers for ONNXRuntime Backend ...
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/include/lite/ort/core/ort_config.h
.......
Installing Lite.AI.ToolKit Headers ...
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/include/lite/backend.h
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/include/lite/config.h
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/include/lite/lite.ai.defs.h
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/include/lite/lite.ai.headers.h
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/include/lite/lite.h
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/include/lite/models.h
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-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/include/lite/utils.h
>>>> Added Shared Library: lite.ai.toolkit !
Installing OpenCV libs -> INCLUDE_OPENCV: ON ...
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libopencv_core.4.5.dylib
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libopencv_core.dylib
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-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libopencv_imgcodecs.dylib
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libopencv_imgproc.4.5.dylib
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libopencv_imgproc.dylib
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libopencv_video.4.5.dylib
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libopencv_video.dylib
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-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libopencv_videoio.dylib
Installing ONNXRuntime libs -> ENABLE_ONNXRUNTIME: ON ...
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libonnxruntime.1.7.0.dylib
-- Installing: /Users/xxx/Desktop/third_party/github/lite.ai.toolkit/build/lite.ai.toolkit/lib/libonnxruntime.dylib
>>>> Added Lite Executable: lite_age_googlenet !
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-- Configuring done
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[ 44%] Building CXX object examples/lite/CMakeFiles/lite_faceboxes.dir/cv/test_lite_faceboxes.cpp.o
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[ 49%] Building CXX object examples/lite/CMakeFiles/lite_cava_combined_face.dir/cv/test_lite_cava_combined_face.cpp.o
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➜ lite.ai.toolkit git:(main) ✗ cd build/lite.ai.toolkit/bin
➜ bin git:(main) ✗ ls
liblite.ai.toolkit.0.1.0.dylib libopencv_video.4.5.dylib lite_densenet lite_facenet lite_glint_partial_fc lite_naive_pose_robust_face lite_resnet lite_ssd_mobilenetv1 lite_vgg16_gender
liblite.ai.toolkit.dylib libopencv_video.dylib lite_efficient_emotion7 lite_fast_style_transfer lite_hardnet lite_nanodet lite_resnext lite_ssrnet lite_yolo5face
libonnxruntime.1.7.0.dylib libopencv_videoio.4.5.dylib lite_efficient_emotion8 lite_fcn_resnet101 lite_ibnnet lite_nanodet_depreciated lite_retinaface lite_subpixel_cnn lite_yolop
libonnxruntime.dylib libopencv_videoio.dylib lite_efficientdet lite_focal_arcface lite_mg_matting lite_nanodet_efficientnet_lite lite_rexnet_emotion7 lite_tencent_cifp_face lite_yolor
libopencv_core.4.5.dylib lite_age_googlenet lite_efficientdet_d7 lite_focal_asia_arcface lite_mobile_emotion7 lite_nanodet_efficientnet_lite_depreciated lite_rvm lite_tencent_curricular_face lite_yolov3
libopencv_core.dylib lite_cava_combined_face lite_efficientdet_d8 lite_fsanet lite_mobile_facenet lite_nanodet_plus lite_scaled_yolov4 lite_tiny_yolov3 lite_yolov4
libopencv_imgcodecs.4.5.dylib lite_cava_ghost_arcface lite_efficientnet_lite4 lite_gender_googlenet lite_mobilenetv2 lite_pfld lite_scrfd lite_tiny_yolov4_coco lite_yolov5
libopencv_imgcodecs.dylib lite_center_loss_face lite_emotion_ferplus lite_ghostnet lite_mobilenetv2_68 lite_pfld68 lite_shufflenetv2 lite_tiny_yolov4_voc lite_yolov5_v6.0
libopencv_imgproc.4.5.dylib lite_colorizer lite_face_landmarks_1000 lite_glint_arcface lite_mobilenetv2_se_68 lite_pfld98 lite_sphere_face lite_ultraface lite_yolox
libopencv_imgproc.dylib lite_deeplabv3_resnet101 lite_faceboxes lite_glint_cosface lite_mobilese_focal_face lite_pose_robust_face lite_ssd lite_vgg16_age lite_yolox_v0.1.1
➜ bin git:(main) ✗ ./lite_yolov5
LITEORT_DEBUG LogId: ../../../hub/onnx/cv/yolov5s.onnx
=============== Input-Dims ==============
input_node_dims: 1
input_node_dims: 3
input_node_dims: 640
input_node_dims: 640
=============== Output-Dims ==============
Output: 0 Name: pred Dim: 0 :1
Output: 0 Name: pred Dim: 1 :25200
Output: 0 Name: pred Dim: 2 :85
Output: 1 Name: output2 Dim: 0 :1
Output: 1 Name: output2 Dim: 1 :3
Output: 1 Name: output2 Dim: 2 :80
Output: 1 Name: output2 Dim: 3 :80
Output: 1 Name: output2 Dim: 4 :85
Output: 2 Name: output3 Dim: 0 :1
Output: 2 Name: output3 Dim: 1 :3
Output: 2 Name: output3 Dim: 2 :40
Output: 2 Name: output3 Dim: 3 :40
Output: 2 Name: output3 Dim: 4 :85
Output: 3 Name: output4 Dim: 0 :1
Output: 3 Name: output4 Dim: 1 :3
Output: 3 Name: output4 Dim: 2 :20
Output: 3 Name: output4 Dim: 3 :20
Output: 3 Name: output4 Dim: 4 :85
========================================
detected num_anchors: 25200
generate_bboxes num: 48
Default Version Detected Boxes Num: 5
LITEORT_DEBUG LogId: ../../../hub/onnx/cv/yolov5s.onnx
=============== Input-Dims ==============
input_node_dims: 1
input_node_dims: 3
input_node_dims: 640
input_node_dims: 640
=============== Output-Dims ==============
Output: 0 Name: pred Dim: 0 :1
Output: 0 Name: pred Dim: 1 :25200
Output: 0 Name: pred Dim: 2 :85
Output: 1 Name: output2 Dim: 0 :1
Output: 1 Name: output2 Dim: 1 :3
Output: 1 Name: output2 Dim: 2 :80
Output: 1 Name: output2 Dim: 3 :80
Output: 1 Name: output2 Dim: 4 :85
Output: 2 Name: output3 Dim: 0 :1
Output: 2 Name: output3 Dim: 1 :3
Output: 2 Name: output3 Dim: 2 :40
Output: 2 Name: output3 Dim: 3 :40
Output: 2 Name: output3 Dim: 4 :85
Output: 3 Name: output4 Dim: 0 :1
Output: 3 Name: output4 Dim: 1 :3
Output: 3 Name: output4 Dim: 2 :20
Output: 3 Name: output4 Dim: 3 :20
Output: 3 Name: output4 Dim: 4 :85
========================================
detected num_anchors: 25200
generate_bboxes num: 39
ONNXRuntime Version Detected Boxes Num: 4
➜ bin git:(main) ✗ |
sh build.sh
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已经编译成功了啊，可以在build/lite.ai.toolkit/lib里面用 otool -L liblite.ai.toolkit.dylib 看一下依赖关系 |
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➜ lib git:(main) ✗ otool -L liblite.ai.toolkit.dylib
liblite.ai.toolkit.dylib:
@rpath/liblite.ai.toolkit.0.1.0.dylib (compatibility version 0.1.0, current version 0.1.0)
@rpath/libopencv_core.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_imgproc.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_imgcodecs.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_video.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_videoio.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libonnxruntime.1.7.0.dylib (compatibility version 0.0.0, current version 1.7.0)
/usr/local/opt/llvm/lib/libc++.1.dylib (compatibility version 1.0.0, current version 1.0.0)
/usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1252.250.1)看看你的rpath有没有问题 |
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对啊，也没问题啊，咋运行lite_yolov5就出现问题了呢 ....我这边也是这样的 |
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看一些lite_yolov5的rpath ➜ lib git:(main) ✗ cd ../bin
➜ bin git:(main) ✗ otool -L lite_yolov5
lite_yolov5:
@rpath/liblite.ai.toolkit.0.1.0.dylib (compatibility version 0.1.0, current version 0.1.0)
@rpath/libopencv_core.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_imgproc.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_imgcodecs.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_video.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_videoio.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libonnxruntime.1.7.0.dylib (compatibility version 0.0.0, current version 1.7.0)
/usr/local/opt/llvm/lib/libc++.1.dylib (compatibility version 1.0.0, current version 1.0.0)
/usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1252.250.1) |
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醉了，那不应该有问题啊，都是一样的 |
呜呜呜，是我太菜了。。 |
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不知道是不是环境不同的问题，确实是个bug，你把我预编译的完整的opencv库下载下来，解压后放在build/lite.ai.toolkit/lib 和 build/lite.ai.toolkit/bin ，再运行lite_yolov5应该就可以了 |
➜ lib git:(main) ✗ otool -L libopencv_video.4.5.dylib
libopencv_video.4.5.dylib:
@rpath/libopencv_video.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_dnn.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_calib3d.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_features2d.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_flann.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_imgproc.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_core.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
/usr/lib/libc++.1.dylib (compatibility version 1.0.0, current version 904.4.0)
/usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1292.60.1)
➜ lib git:(main) ✗ otool -L libopencv_videoio.4.5.dylib
libopencv_videoio.4.5.dylib:
@rpath/libopencv_videoio.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_imgcodecs.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_imgproc.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
@rpath/libopencv_core.4.5.dylib (compatibility version 4.5.0, current version 4.5.2)
/usr/local/opt/ffmpeg/lib/libavcodec.58.dylib (compatibility version 58.0.0, current version 58.134.100)
/usr/local/opt/ffmpeg/lib/libavformat.58.dylib (compatibility version 58.0.0, current version 58.76.100)
/usr/local/opt/ffmpeg/lib/libavutil.56.dylib (compatibility version 56.0.0, current version 56.70.100)
/usr/local/opt/ffmpeg/lib/libswscale.5.dylib (compatibility version 5.0.0, current version 5.9.100)
/usr/local/opt/ffmpeg/lib/libavresample.4.dylib (compatibility version 4.0.0, current version 4.0.0)
/System/Library/Frameworks/Cocoa.framework/Versions/A/Cocoa (compatibility version 1.0.0, current version 23.0.0)
/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate (compatibility version 1.0.0, current version 4.0.0)
/System/Library/Frameworks/AVFoundation.framework/Versions/A/AVFoundation (compatibility version 1.0.0, current version 2.0.0)
/System/Library/Frameworks/CoreGraphics.framework/Versions/A/CoreGraphics (compatibility version 64.0.0, current version 1463.2.1)
/System/Library/Frameworks/CoreMedia.framework/Versions/A/CoreMedia (compatibility version 1.0.0, current version 1.0.0)
/System/Library/Frameworks/CoreVideo.framework/Versions/A/CoreVideo (compatibility version 1.2.0, current version 1.5.0)
/System/Library/Frameworks/QuartzCore.framework/Versions/A/QuartzCore (compatibility version 1.2.0, current version 1.11.0)
/usr/lib/libc++.1.dylib (compatibility version 1.0.0, current version 904.4.0)
/usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1292.60.1)
/System/Library/Frameworks/CoreFoundation.framework/Versions/A/CoreFoundation (compatibility version 150.0.0, current version 1770.255.0)
/System/Library/Frameworks/Foundation.framework/Versions/C/Foundation (compatibility version 300.0.0, current version 1770.255.0)
/usr/lib/libobjc.A.dylib (compatibility version 1.0.0, current version 228.0.0)ffmpeg也要安装，不然可能也会有问题，通过 brew install ffmpeg 安装 |
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是的，需要4.2.2的ffmpeg，homebrew现在更新到了最新的5.0版本，很多接口都变了。需要git clone低版本的源码来安装ffmpeg，并指定--prefix=/usr/local/opt/ffmpeg。可以看opencv的issue: git clone --depth=1 https://git.ffmpeg.org/ffmpeg.git -b n4.2.2
cd ffmpeg
./configure --enable-shared --disable-x86asm --prefix=/usr/local/opt/ffmpeg --disable-static
make -j8
make install |
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预告一下：mac也正在弄一个连带ffmpeg打包的lite.ai.toolkit预编译库，这周末应该会放出来。最近ffmpeg升级大版本后（>4.4）,opencv原来的依赖ffmpeg的模块不再兼容了 |
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我知道了，因为源码编的4.2.2 没有libavresample，但是之前通过brew安装的是有的，homebrew升级后同步了最新的ffmpeg又不兼容opencv. 所以会导致这些问题。你要不直接试一下lite.ai.toolkit的dev分支吧，我今天修复了这个兼容的问题。但还没合并，还需要检查一下。 git clone --depth=1 https://github.com/DefTruth/lite.ai.toolkit.git -b dev # dev分支代码
cd lite.ai.toolkit && sh ./build.sh # On MacOS, you can use the built OpenCV, ONNXRuntime, MNN, NCNN and TNN libs in this repo.或者重新编译一下opencv，替换掉我原来的就可以了
git clone --depth=1 https://git.ffmpeg.org/ffmpeg.git -b n4.2.2
cd ffmpeg
./configure --enable-shared --disable-x86asm --prefix=/usr/local/opt/ffmpeg --disable-static
make -j8
make install
git clone --depth=1 https://github.com/opencv/opencv.git -b 4.5.2
cd opencv
#!/bin/bash
mkdir build
mkdir your-path-to-custom-dir
cd build
cmake .. \
-D CMAKE_BUILD_TYPE=Release \
-D CMAKE_INSTALL_PREFIX=/User/xxx/xxx/opencv/your-path-to-custom-dir \ # 新建一个你自定义的目录，写绝对路径指向这个目录
-D BUILD_TESTS=OFF \
-D BUILD_PERF_TESTS=OFF \
-D BUILD_opencv_python3=OFF \
-D BUILD_opencv_python2=OFF \
-D BUILD_SHARED_LIBS=ON \
-D BUILD_opencv_apps=OFF \
-D WITH_FFMPEG=ON
make -j8
make install
cd ..运行编译 sh ./build.sh编译完opencv后，直接替换新的dylib |
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@chenjiachengzzz 已经合并最新代码了，你用最新的试一下? git clone --depth=1 https://github.com/DefTruth/lite.ai.toolkit.git # latest
cd lite.ai.toolkit && sh ./build.sh # On MacOS, you can use the built OpenCV, ONNXRuntime, MNN, NCNN and TNN libs in this repo.
cd build/lite.ai.toolkit/bin
./lite_yolov5更新信息请看： |
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"编译完opencv后，直接替换新的dylib"，请问大佬，这句话什么意思呀？ |
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