I would like to create a vx_image out of an array. Let us say i have 2D array:
unsigned char img_array[720][1280]={{..},{..}, ... } // filled with values
I would like to make it
vx_image
so that i can perform various pixel level operations. Any other idea to do the same thing would also be fine.
I think the best way to interoperate is: from VX(CUDA) to CUDA(native) OR OpenCV(CUDA) and vice-versa. One of the nice way is given here. And the other possible way is below (This snippet is taken from VisionWorks Document):
void processImageWithCUDA(vx_image src, vx_image dst)
{
vx_df_image format = 0;
vxQueryImage(src, VX_IMAGE_ATTRIBUTE_FORMAT, &format, sizeof(format));
assert( format == VX_DF_IMAGE_RGB );
// Get valid region
vx_rectangle_t rect;
vxGetValidRegionImage(src, &rect);
// Map VisionWorks data objects into CUDA device memory
vx_map_id src_map_id;
vx_uint8* src_ptr;
vx_imagepatch_addressing_t src_addr;
vxMapImagePatch(src, &rect, 0, &src_map_id, &src_addr, (void **)&src_ptr, VX_READ_ONLY, NVX_MEMORY_TYPE_CUDA, 0);
vx_map_id dst_map_id;
vx_uint8* dst_ptr;
vx_imagepatch_addressing_t dst_addr;
vxMapImagePatch(dst, &rect, 0, &dst_map_id, &dst_addr, (void **)&dst_ptr, VX_WRITE_ONLY, NVX_MEMORY_TYPE_CUDA, 0);
// Call CUDA function
cudaStream_t stream = NULL;
myOperations_image(src_addr.dim_x, src_addr.dim_y,
stream);
cudaStreamSynchronize(stream);
// Unmap VisionWorks data objects from CUDA device memory
vxUnmapImagePatch(src, src_map_id);
vxUnmapImagePatch(dst, dst_map_id);
}
In both the cases we are not copying to host memory, else it will drastically degrade performance, with a caveat that operations inside myOperations_image() should also maintain this rule.