AGX Xavier 场景下的 【OpenCV + FFmpeg + CUDA + GStreamer】 重装 & 编译的2025年稳定方案
✅ 1️⃣ 先卸载老版本
AGX 自带很多预装包,原则:卸载干净,避免旧库和新编译冲突。
🔹 卸载 OpenCV
dpkg -l | grep opencv
sudo apt-get remove --purge libopencv* python3-opencv
# 自己 make install 装过的也一起删
sudo rm -rf /usr/local/include/opencv4
sudo rm -rf /usr/local/lib/libopencv*
sudo rm -rf /usr/local/lib/pkgconfig/opencv4.pc
sudo rm -rf /usr/local/lib/python3*/dist-packages/cv2*
# 卸载 pip 版本(如果有)
pip3 uninstall opencv-python opencv-contrib-python
sudo ldconfig
🔹 卸载 FFmpeg
dpkg -l | grep ffmpeg
sudo apt-get remove --purge ffmpeg
sudo rm -rf /usr/local/bin/ffmpeg /usr/local/bin/ffprobe /usr/local/lib/libav*
sudo ldconfig
✅ 2️⃣ 检查 CUDA 和 GStreamer
AGX Xavier 自带 CUDA,JetPack 4.5 默认是 CUDA 10.2 + GStreamer 1.14.x
→ 不要自己乱装 CUDA,保持 JetPack 自带就行。
检查一下:
nvcc --version
gst-launch-1.0 --version
确认有:
CUDA compilation tools, release 10.2, V10.2.89
GStreamer 1.14.x
✅ 3️⃣ 安装依赖
sudo apt-get update
# 编译工具
sudo apt-get install -y build-essential cmake git pkg-config
# GStreamer (一定要有)
sudo apt-get install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev \
gstreamer1.0-plugins-good gstreamer1.0-plugins-bad \
gstreamer1.0-plugins-ugly gstreamer1.0-libav
# 图像编解码
sudo apt-get install -y libjpeg-dev libpng-dev libtiff-dev libavcodec-dev libavformat-dev libswscale-dev libv4l-dev
# OpenGL 和 V4L2
sudo apt-get install -y libgtk-3-dev libcanberra-gtk* libtbb2 libtbb-dev libdc1394-22-dev
# Python
sudo apt-get install -y python3-dev python3-numpy
✅ 4️⃣ 编译 OpenCV (推荐 4.5.5)
🔹 拉源码
cd ~
git clone https://github.com/opencv/opencv.git
cd opencv
git checkout 4.5.5
cd ~
git clone https://github.com/opencv/opencv_contrib.git
cd opencv_contrib
git checkout 4.5.5
cd ~/opencv
mkdir build && cd build
将opencv_contrib放在opencv的文件夹下。后面配置CMake路径时注意统一。
解决ADE被墙
cmake的过程中,会因为下载ADE被墙,而停顿,因此只好手动下载。
wget https://github.com/opencv/ade/archive/refs/tags/v0.1.1f.zip
# 解压到 opencv_contrib/modules/ade 或者 opencv/3rdparty/ade
unzip v0.1.1f.zip
mv ade-0.1.1f/* ~/opencv_build/opencv/3rdparty/ade
opencv/
├── 3rdparty/
│ ├── ade/
│ ├── CMakeLists.txt
│ ├── source.cpp ...
只要在
opencv/3rdparty/ade/
里能找到它的CMakeLists.txt
,就没问题。
并在CMake是加上一句:
-D OPENCV_ADE_DIR=~/opencv_build/opencv/3rdparty/ade
解决NVIDIA_OPTICAL_FLOW被墙
🔹 CMake 推荐配置(AGX Xavier 专属 🚀)
cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=~/opencv/opencv_contrib/modules -D WITH_CUDA=ON -D WITH_CUDNN=ON -D OPENCV_DNN_CUDA=ON -D ENABLE_FAST_MATH=ON -D CUDA_FAST_MATH=ON -D WITH_CUBLAS=ON -D WITH_GSTREAMER=ON -D WITH_FFMPEG=ON -D WITH_GSTREAMER_0_10=OFF -D WITH_LIBV4L=ON -D WITH_OPENGL=ON -D WITH_QT=OFF -D BUILD_opencv_python2=OFF -D BUILD_opencv_python3=ON -D PYTHON3_EXECUTABLE=$(which python3) -D PYTHON3_INCLUDE_DIR=$(python3 -c "from sysconfig import get_paths as gp; print(gp()['include'])") -D PYTHON3_LIBRARY=$(python3 -c "from sysconfig import get_paths as gp; print(gp()['stdlib'])") -D OPENCV_GENERATE_PKGCONFIG=ON -D BUILD_TESTS=OFF -D OPENCV_ENABLE_NONFREE=ON -D BUILD_EXAMPLES=OFF -D OPENCV_ADE_DIR=~/opencv/3rdparty/ade ..
需要包含:
-D BUILD_opencv_python3=ON \
-D PYTHON3_EXECUTABLE=$(which python3) \
-D PYTHON3_INCLUDE_DIR=$(python3 -c "from sysconfig import get_paths as gp; print(gp()['include'])") \
-D PYTHON3_LIBRARY=$(python3 -c "from sysconfig import get_paths as gp; print(gp()['stdlib'])") \
否则会提示:
python3 -c "import cv2; print(cv2.getBuildInformation())" | grep CUDATraceback (most recent call last):
File "<string>", line 1, in <module>
ModuleNotFoundError: No module named 'cv2'
nvidia@agxA:~/opencv/build$ python3 -c "import cv2; print(cv2.getBuildInformation())" | grep GStreamer
Traceback (most recent call last):
File "<string>", line 1, in <module>
ModuleNotFoundError: No module named 'cv2'
🔹 编译 & 安装
make -j$(nproc) # Xavier AGX 建议一次用 4-6 核,别一次全开,避免 OOM
sudo make install
sudo ldconfig
✅ 5️⃣ (可选)FFmpeg
如果主要用 GStreamer 了,FFmpeg 不必须单独编译。
要自己带硬编解码:
-
Jetson 上推荐用 NVIDIA 提供的 L4T Multimedia API 或者
nvmpi
社区版。 -
nvmpi
维护得很久没更新,新项目直接用 GStreamer + nvarguscamerasrc + nvv4l2decoder 最稳定。
✅ 6️⃣ 验证
# OpenCV
python3 -c "import cv2; print(cv2.getBuildInformation())" | grep CUDA
python3 -c "import cv2; print(cv2.getBuildInformation())" | grep GStreamer
# GStreamer
gst-inspect-1.0 | grep nv
关键点总结:
1️⃣ JetPack 4.5 的 CUDA/FFmpeg/GStreamer 都需要自己编时打开
2️⃣ ADE
可手动解压替代自动下载
3️⃣ JNI
、Tesseract
非刚需可以跳过或后装
4️⃣ BUILD_opencv_python3=ON
和 Python 路径一定配好
5️⃣ 不要混用 pip 的 opencv-python
,它是 CPU 版,没 GPU