从Python（Pycuda gpuarray）到OpENCV（CV :: CUDA :: GPUMAT）的交换GPU数据，反之亦然（重复）

Question

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是否可以在Pycuda和OpenCV CUDA模块之间交换数据？ Pycuda拥有自己的pycuda gpuarray类，OpenCV有自己的gpu_mat。

该计划是在图像（例如现在仅将其倒置）对图像执行某种动作，将其保留在GPU上，然后使用OpenCV执行Charny。

import numpy
import time
import numpy as np
import pycuda.autoinit
import pycuda.driver as cuda
from pycuda.compiler import SourceModule
import pycuda.gpuarray as gpuarray
import cv2

mod = SourceModule("""
__global__ void multiply_them(uchar3 *dest, uchar3* img, int row, int col)
{
  int i = blockDim.x * blockIdx.x + threadIdx.x;
  int j = blockIdx.y * blockDim.y + threadIdx.y;

  if (j >= row || i >= col) { return; }

  dest[j * col + i].x = 255 - img[j * col + i].x;
    dest[j * col + i].y = 255 - img[j * col + i].y;
    dest[j * col + i].z = 255 - img[j * col + i].z;
  
}
""")


img = cv2.imread("./colorful_image.jpg", 0)
dest = numpy.zeros_like(img)

col = np.int32(img.shape[1])
row = np.int32(img.shape[0])

start = time.perf_counter()

multiply_them = mod.get_function("multiply_them")

img_gpu = gpuarray.to_gpu(img.astype(numpy.uint8))
dest_gpu = gpuarray.to_gpu(dest.astype(numpy.uint8))

block_size = (32,32,1)
grid_size = (int(col/block_size[0] + 1), int(row/block_size[1] + 1),1)
multiply_them(dest_gpu, img_gpu, row, col, block=block_size, grid=grid_size)

# dest_gpu = dest_gpu.get()  # If we download to CPU it work fine but we dont want that.
# dest_gpu = cv2.cuda_GpuMat(dest_gpu)

cannyFilter = cv2.cuda.createCannyEdgeDetector(50, 120)
gpu_img_canny = cannyFilter.detect(dest_gpu)
b = gpu_img_canny.download()

cv2.imwrite("./slika_canny.jpg", b)
stop = time.perf_counter() 
print("Time: ", stop-start)