NPP nv12->bgr incorrect coefficients

Accelerated Computing GPU-Accelerated Libraries
#1

Hi,

I am seeing a peculiar issue with nppiNV12ToBGR_709HDTV_8u_P2C3R.

I have created a bt709 test file using gstreamer:

gst-launch-1.0 videotestsrc num-buffers=100 ! “video/x-raw, height=1080, width=1920, colorimetry=(string)bt709” ! x264enc bitrate=10000000 ! qtmux ! filesink location=bt709.mp4

I then decoded the same file using the codec sdk and converted NV12->BGR using nppiNV12ToBGR_709HDTV_8u_P2C3R. This resulted in poor colour conversion. Dynamic range is lower than the original, ultimately the picture is dull.

nppiNV12ToBGR_709HDTV_8u_P2C3R
https://pasteboard.co/IriQnNw.bmp

I created a kernel which i believe uses the correct coefficients which produces much better colours and represents the original image.

    float r = y * 1.164384 + v * 1.792741 - 248.101004;
    float g = y * 1.164384 - u * 0.213249 - v * 0.532909 + 76.878085;
    float b = y * 1.164384 + u * 2.112402 - 289.017577;

https://pasteboard.co/IriRS0H.bmp

Am i doing something wrong or is there an issue with npp’s color conversion?

Thanks in advance,
Chris

#2

Can you confirm whether the input is treated as full or limited range ycbcr. Also that the output is full range BGR? It looks to me like nppiNV12ToBGR_709HDTV_8u_P2C3R and nppiNV12ToBGR_8u_P2C3R output limited range BGR [16-235].

Thanks again,
Chris

#3

I can confirm that both nppiNV12ToBGR_709HDTV_8u_P2C3R and nppiNV12ToBGR_8u_P2C3R assume (wrongly IMHO) ycbcr input ranges 0…255.

If the inputs are truly bt601 or bt709, the output for black and white are as follows…

void test_719_to_bgr(const uint8_t* nv12_data){

constexpr size_t input_stride = 8;
constexpr size_t output_stride = 3;
uint8_t *cu_nv12;
uint8_t *cu_bgr;
cudaMalloc(&cu_nv12, 12);
cudaMalloc(&cu_bgr, 3);
cudaMemcpy(cu_nv12, nv12_data, 12, cudaMemcpyHostToDevice);
NppiSize roi{1,1};
Npp8u *yuv_ptrs = {cu_nv12, cu_nv12 + input_stride};
nppiNV12ToBGR_709HDTV_8u_P2C3R(yuv_ptrs, input_stride, cu_bgr, output_stride, roi);
std::array<uint8_t,3> result_bgr{};
cudaMemcpy(&result_bgr[0], cu_bgr, 3, cudaMemcpyDeviceToHost);
for (auto &val : result_bgr){
std::cout << std::to_string(val) << " ";
}
std::cout << “\n”;
}

constexpr uint8_t nv12_black = {0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00};
constexpr uint8_t nv12_white = {0xeb, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00};

test_719_to_bgr(nv12_black);
test_719_to_bgr(nv12_white);

Actual results
16 16 16
235 235 235

Expected results
0 0 0
255 255 255

#4

you might wish to file a bug. The instructions are linked to a sticky post at the top of the CUDA programming forum

#5

I have raised a bug. I think the best solution here is to either add some new functions for limited colour range, or, add a parameter for colour range. At the very least, document the full range assumption.

#6

https://developer.nvidia.com/nvidia_bug/2672777