Аренда GPU для OpenCV
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# Ubuntu 24, системный Python managed — ставим в venv:
python3 -m venv /opt/cv && source /opt/cv/bin/activate
pip install --upgrade pip
# С GUI (cv2.imshow и пр.):
pip install opencv-python
# Без GUI (для серверов и Docker):
pip install opencv-python-headless
# С contrib‑модулями (SIFT, tracking, xfeatures2d):
pip install opencv-contrib-python
# Проверка:
python3 -c 'import cv2; print(cv2.__version__, cv2.cuda.getCudaEnabledDeviceCount())'

# Ubuntu 24.04, CUDA 12.x, cuDNN 9 — должны быть в /usr/local/cuda
apt-get update && apt-get install -y \
  build-essential cmake git pkg-config \
  libjpeg-dev libpng-dev libtiff-dev libwebp-dev \
  libavcodec-dev libavformat-dev libswscale-dev libv4l-dev \
  libgtk-3-dev libtbb-dev libeigen3-dev python3-dev python3-numpy

git clone --depth 1 -b 4.13.0 https://github.com/opencv/opencv.git
git clone --depth 1 -b 4.13.0 https://github.com/opencv/opencv_contrib.git

cmake -S opencv -B build \
  -D CMAKE_BUILD_TYPE=Release \
  -D CMAKE_INSTALL_PREFIX=/usr/local \
  -D OPENCV_EXTRA_MODULES_PATH=$(pwd)/opencv_contrib/modules \
  -D WITH_CUDA=ON -D WITH_CUDNN=ON -D OPENCV_DNN_CUDA=ON \
  -D CUDA_ARCH_BIN='8.9;9.0' \
  -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 \
  -D BUILD_opencv_python3=ON -D BUILD_EXAMPLES=OFF

cmake --build build -j$(nproc)
cmake --install build && ldconfig

# Проверка CUDA:
python3 -c 'import cv2; print(cv2.cuda.getCudaEnabledDeviceCount())'  # > 0

# Pull official OpenCV docker image with CUDA:
docker pull opencvcourses/opencv-docker:latest

# Или собираем свой Dockerfile поверх nvidia/cuda:
cat > Dockerfile <<'EOF'
FROM nvidia/cuda:12.6.3-cudnn-devel-ubuntu22.04
RUN apt-get update && apt-get install -y python3-pip git cmake build-essential \
    libgl1 libglib2.0-0
RUN pip install opencv-contrib-python-headless numpy
WORKDIR /app
EOF

docker build -t opencv-cuda .
docker run --gpus all --rm -it -v $(pwd):/app opencv-cuda \
  python3 -c 'import cv2; print(cv2.cuda.getCudaEnabledDeviceCount())'

# main.cpp — пример GPU‑pipeline (Sobel + Gaussian + DNN inference):
cat > main.cpp <<'EOF'
#include <opencv2/opencv.hpp>
#include <opencv2/cudaimgproc.hpp>
#include <opencv2/cudafilters.hpp>
int main() {
  cv::Mat host = cv::imread("in.jpg");
  cv::cuda::GpuMat d_src; d_src.upload(host);
  cv::cuda::GpuMat d_gray;
  cv::cuda::cvtColor(d_src, d_gray, cv::COLOR_BGR2GRAY);
  auto sobel = cv::cuda::createSobelFilter(CV_8UC1, CV_16S, 1, 0);
  cv::cuda::GpuMat d_out; sobel->apply(d_gray, d_out);
  cv::Mat host_out; d_out.download(host_out);
  cv::imwrite("out.png", host_out);
}
EOF

g++ main.cpp -o pipeline `pkg-config --cflags --libs opencv4`
./pipeline