mirror of
https://github.com/moonlight-stream/moonlight-qt.git
synced 2025-07-01 23:35:55 +00:00
Optimize CUDA support to avoid roundtrip to CPU memory
This commit is contained in:
parent
f0c292f508
commit
3e9aea1f7a
14
app/app.pro
14
app/app.pro
@ -88,6 +88,11 @@ unix:!macx {
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PKGCONFIG += libdrm
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CONFIG += libdrm
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}
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packagesExist(ffnvcodec) {
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PKGCONFIG += ffnvcodec
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CONFIG += cuda
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}
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}
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packagesExist(wayland-client) {
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@ -196,7 +201,6 @@ ffmpeg {
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SOURCES += \
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streaming/video/ffmpeg.cpp \
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streaming/video/ffmpeg-renderers/sdlvid.cpp \
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streaming/video/ffmpeg-renderers/cuda.cpp \
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streaming/video/ffmpeg-renderers/pacer/pacer.cpp \
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streaming/video/ffmpeg-renderers/pacer/nullthreadedvsyncsource.cpp
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@ -204,7 +208,6 @@ ffmpeg {
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streaming/video/ffmpeg.h \
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streaming/video/ffmpeg-renderers/renderer.h \
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streaming/video/ffmpeg-renderers/sdlvid.h \
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streaming/video/ffmpeg-renderers/cuda.h \
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streaming/video/ffmpeg-renderers/pacer/pacer.h \
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streaming/video/ffmpeg-renderers/pacer/nullthreadedvsyncsource.h
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}
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@ -261,6 +264,13 @@ libdrm {
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LIBS += -ldl
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}
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}
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cuda {
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message(CUDA support enabled)
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DEFINES += HAVE_CUDA
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SOURCES += streaming/video/ffmpeg-renderers/cuda.cpp
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HEADERS += streaming/video/ffmpeg-renderers/cuda.h
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}
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config_EGL {
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message(EGL renderer selected)
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@ -1,5 +1,13 @@
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#include "cuda.h"
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#include <ffnvcodec/dynlink_loader.h>
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#include <SDL_opengl.h>
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extern "C" {
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#include <libavutil/hwcontext_cuda.h>
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}
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CUDARenderer::CUDARenderer()
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: m_HwContext(nullptr)
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{
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@ -55,3 +63,96 @@ bool CUDARenderer::isDirectRenderingSupported()
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return false;
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}
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bool CUDARenderer::copyCudaFrameToBoundTexture(AVFrame* frame)
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{
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static CudaFunctions* funcs;
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CUresult err;
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AVCUDADeviceContext* devCtx = (AVCUDADeviceContext*)(((AVHWFramesContext*)frame->hw_frames_ctx->data)->device_ctx->hwctx);
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bool ret = false;
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if (!funcs) {
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// One-time init of CUDA library
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cuda_load_functions(&funcs, nullptr);
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if (!funcs) {
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SDL_LogError(SDL_LOG_CATEGORY_APPLICATION, "Failed to initialize CUDA library");
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return false;
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}
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}
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SDL_assert(frame->format == AV_PIX_FMT_CUDA);
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// Push FFmpeg's CUDA context to use for our CUDA operations
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err = funcs->cuCtxPushCurrent(devCtx->cuda_ctx);
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if (err != CUDA_SUCCESS) {
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SDL_LogError(SDL_LOG_CATEGORY_APPLICATION, "cuCtxPushCurrent() failed: %d", err);
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return false;
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}
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// NV12 has 2 planes
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for (int i = 0; i < 2; i++) {
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CUgraphicsResource cudaResource;
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CUarray cudaArray;
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GLint tex;
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// Get the ID of this plane's texture
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glActiveTexture(GL_TEXTURE0 + i);
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glGetIntegerv(GL_TEXTURE_BINDING_2D, &tex);
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// Register it with CUDA
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err = funcs->cuGraphicsGLRegisterImage(&cudaResource, tex, GL_TEXTURE_2D, CU_GRAPHICS_REGISTER_FLAGS_WRITE_DISCARD);
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if (err != CUDA_SUCCESS) {
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SDL_LogError(SDL_LOG_CATEGORY_APPLICATION, "cuGraphicsGLRegisterImage() failed: %d", err);
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goto Exit;
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}
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// Map it to allow us to use it as a copy destination
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err = funcs->cuGraphicsMapResources(1, &cudaResource, devCtx->stream);
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if (err != CUDA_SUCCESS) {
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SDL_LogError(SDL_LOG_CATEGORY_APPLICATION, "cuGraphicsMapResources() failed: %d", err);
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funcs->cuGraphicsUnregisterResource(cudaResource);
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goto Exit;
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}
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// Get a pointer to the mapped array
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err = funcs->cuGraphicsSubResourceGetMappedArray(&cudaArray, cudaResource, 0, 0);
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if (err != CUDA_SUCCESS) {
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SDL_LogError(SDL_LOG_CATEGORY_APPLICATION, "cuGraphicsSubResourceGetMappedArray() failed: %d", err);
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funcs->cuGraphicsUnmapResources(1, &cudaResource, devCtx->stream);
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funcs->cuGraphicsUnregisterResource(cudaResource);
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goto Exit;
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}
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CUDA_MEMCPY2D cu2d = {
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.srcMemoryType = CU_MEMORYTYPE_DEVICE,
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.srcDevice = (CUdeviceptr)frame->data[i],
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.srcPitch = (size_t)frame->linesize[i],
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.dstMemoryType = CU_MEMORYTYPE_ARRAY,
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.dstArray = cudaArray,
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.dstPitch = (size_t)frame->width >> i,
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.WidthInBytes = (size_t)frame->width,
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.Height = (size_t)frame->height >> i
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};
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// Do the copy
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err = funcs->cuMemcpy2D(&cu2d);
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if (err != CUDA_SUCCESS) {
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SDL_LogError(SDL_LOG_CATEGORY_APPLICATION, "cuMemcpy2D() failed: %d", err);
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funcs->cuGraphicsUnmapResources(1, &cudaResource, devCtx->stream);
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funcs->cuGraphicsUnregisterResource(cudaResource);
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goto Exit;
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}
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funcs->cuGraphicsUnmapResources(1, &cudaResource, devCtx->stream);
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funcs->cuGraphicsUnregisterResource(cudaResource);
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}
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ret = true;
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Exit:
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{
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CUcontext dummy;
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funcs->cuCtxPopCurrent(&dummy);
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}
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return ret;
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}
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@ -12,6 +12,9 @@ public:
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virtual bool needsTestFrame() override;
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virtual bool isDirectRenderingSupported() override;
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// Helper function used by SDLRenderer to read our CUDA frame
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static bool copyCudaFrameToBoundTexture(AVFrame* frame);
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private:
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AVBufferRef* m_HwContext;
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};
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@ -5,6 +5,10 @@
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#include <Limelight.h>
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#ifdef HAVE_CUDA
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#include "cuda.h"
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#endif
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SdlRenderer::SdlRenderer()
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: m_Renderer(nullptr),
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m_Texture(nullptr),
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@ -203,7 +207,7 @@ void SdlRenderer::renderFrame(AVFrame* frame)
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return;
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}
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if (frame->hw_frames_ctx != nullptr) {
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if (frame->hw_frames_ctx != nullptr && frame->format != AV_PIX_FMT_CUDA) {
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// If we are acting as the frontend for a hardware
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// accelerated decoder, we'll need to read the frame
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// back to render it.
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@ -254,6 +258,7 @@ void SdlRenderer::renderFrame(AVFrame* frame)
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case AV_PIX_FMT_YUV420P:
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sdlFormat = SDL_PIXELFORMAT_YV12;
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break;
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case AV_PIX_FMT_CUDA:
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case AV_PIX_FMT_NV12:
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sdlFormat = SDL_PIXELFORMAT_NV12;
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break;
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@ -290,7 +295,18 @@ void SdlRenderer::renderFrame(AVFrame* frame)
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}
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}
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if (frame->format == AV_PIX_FMT_YUV420P) {
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if (frame->format == AV_PIX_FMT_CUDA) {
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#ifdef HAVE_CUDA
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SDL_GL_BindTexture(m_Texture, nullptr, nullptr);
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CUDARenderer::copyCudaFrameToBoundTexture(frame);
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SDL_GL_UnbindTexture(m_Texture);
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#else
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SDL_LogError(SDL_LOG_CATEGORY_APPLICATION,
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"Got CUDA frame, but not built with CUDA support!");
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goto Exit;
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#endif
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}
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else if (frame->format == AV_PIX_FMT_YUV420P) {
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SDL_UpdateYUVTexture(m_Texture, nullptr,
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frame->data[0],
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frame->linesize[0],
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#include <h264_stream.h>
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#include "ffmpeg-renderers/sdlvid.h"
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#include "ffmpeg-renderers/cuda.h"
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#ifdef Q_OS_WIN32
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#include "ffmpeg-renderers/dxva2.h"
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@ -36,6 +35,10 @@
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#include "ffmpeg-renderers/eglvid.h"
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#endif
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#ifdef HAVE_CUDA
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#include "ffmpeg-renderers/cuda.h"
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#endif
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// This is gross but it allows us to use sizeof()
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#include "ffmpeg_videosamples.cpp"
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@ -567,11 +570,11 @@ IFFmpegRenderer* FFmpegVideoDecoder::createHwAccelRenderer(const AVCodecHWConfig
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// Second pass for our second-tier hwaccel implementations
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else if (pass == 1) {
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switch (hwDecodeCfg->device_type) {
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#ifdef HAVE_CUDA
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case AV_HWDEVICE_TYPE_CUDA:
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// CUDA should only be used if all other options fail, since it requires
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// read-back of frames. This should only be used for the NVIDIA+Wayland case
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// with VDPAU covering the NVIDIA+X11 scenario.
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// CUDA should only be used to cover the NVIDIA+Wayland case
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return new CUDARenderer();
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#endif
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default:
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return nullptr;
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}
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