docs: minor improvements to CUDA docs in READMEs

Signed-off-by: deadprogram <[email protected]>

README.md

@@ -13,6 +13,8 @@ The GoCV package provides Go language bindings for the [OpenCV 4](http://opencv.
 
 The GoCV package supports the latest releases of Go and OpenCV (v4.5.0) on Linux, macOS, and Windows. We intend to make the Go language a "first-class" client compatible with the latest developments in the OpenCV ecosystem.
 
+GoCV supports [CUDA](https://en.wikipedia.org/wiki/CUDA) for hardware acceleration using Nvidia GPUs. Check out the [CUDA README](./cuda/README.md) for more info on how to use GoCV with OpenCV/CUDA.
+
 GoCV also supports [Intel OpenVINO](https://software.intel.com/en-us/openvino-toolkit). Check out the [OpenVINO README](./openvino/README.md) for more info on how to use GoCV with the Intel OpenVINO toolkit.
 
 ## How to use

cuda/README.md

@@ -1,17 +1,18 @@
-# Cuda
+# CUDA
 
-In order to use the cuda package, the cuda toolkit from nvidia needs to be installed on the host system. 
- CUDA backend for DNN module requires CC (Compute Capability) 5.3 or higher. Check your GPU https://developer.nvidia.com/cuda-gpus
+In order to use the GoCV `cuda` package, the CUDA toolkit from nvidia needs to be installed on the host system. 
+
+The CUDA backend for DNN module requires CC (Compute Capability) 5.3 or higher. Check your GPU https://developer.nvidia.com/cuda-gpus
 
 Please see https://docs.nvidia.com/cuda/index.html for more information.
 
-Furthermore opencv must be compiled with cuda support.
+Furthermore opencv must be compiled with CUDA support.
 
-GoCV supports using the Cuda as a backend for the OpenCV deep neural network (DNN) module.
+GoCV also supports using CUDA as a backend for the OpenCV deep neural network (DNN) module.
 
 ## How to use
 
-This code loads a Caffe model, and then uses Cuda to prepare it for execution on the GPU:
+This code loads a Caffe model, and then uses CUDA to prepare it for execution on the GPU:
 
 ```go
 net := gocv.ReadNet("/path/to/your/model.caffemodel", "/path/to/your/config.proto")
@@ -24,20 +25,21 @@ net.SetPreferableBackend(gocv.NetBackendType(gocv.NetBackendCUDA))
 net.SetPreferableTarget(gocv.NetTargetType(gocv.NetTargetCUDA))
 ```
 
-## Install Cuda
+## Installing CUDA
+
 Download and install packages from https://developer.nvidia.com/cuda-downloads
 
-	example 'cuda_10.2.89_440.33.01_linux.run'
+For example, download 'cuda_10.2.89_440.33.01_linux.run'
 
 Download and install packages from https://developer.nvidia.com/rdp/cudnn-archive
 
-	example 'cuDNN Runtime Library for Ubuntu18.04 (Deb)' and 'cuDNN Developer Library for Ubuntu18.04 (Deb)'
+For example the 'cuDNN Runtime Library for Ubuntu18.04 (Deb)' and 'cuDNN Developer Library for Ubuntu18.04 (Deb)'
 
-## Compiling opencv with cuda
+## Compiling OpenCV with CUDA
 
-For now we have included the make target `install_cuda` that compiles opencv with cuda. (For more details on the compilation process please see the `Makefile`)
+We have included the make target `install_cuda` that compiles OpenCV with CUDA support. (For more details on the compilation process please see the `Makefile`)
 
-Simply issue the command `make install_cuda` and you should be good to go.
+Run the command `make install_cuda` and you should be good to go.
 
 If you need static opencv libraries
 
@@ -50,6 +52,6 @@ Then finally verify that it is all working
 
 You should see something along the lines of:
 
-    gocv version: 0.19.0
+    gocv version: 0.25.0
     cuda information:
       Device 0:  "GeForce MX150"  2003Mb, sm_61, Driver/Runtime ver.10.0/10.0