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avfilter/vf_yadif_cuda: CUDA accelerated yadif deinterlacer

Browse Source 
This is a cuda implementation of yadif, which gives us a way to
do deinterlacing when using the nvdec hwaccel. In that scenario
we don't have access to the nvidia deinterlacer.
This commit is contained in:
Philip Langdale 2018-10-21 13:49:16 -07:00
parent 598f0f3927
commit d5272e94ab
8 changed files with 785 additions and 1 deletions
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1
Changelog
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@ -45,6 +45,7 @@ version 4.1:
- xstack filter - xstack filter
- pcm vidc decoder and encoder - pcm vidc decoder and encoder
- (a)graphmonitor filter - (a)graphmonitor filter
- yadif_cuda filter
version 4.0: version 4.0:

1
configure vendored
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@ -3482,6 +3482,7 @@ zscale_filter_deps="libzimg const_nan"
scale_vaapi_filter_deps="vaapi" scale_vaapi_filter_deps="vaapi"
vpp_qsv_filter_deps="libmfx" vpp_qsv_filter_deps="libmfx"
vpp_qsv_filter_select="qsvvpp" vpp_qsv_filter_select="qsvvpp"
yadif_cuda_filter_deps="cuda_sdk"
# examples # examples
avio_dir_cmd_deps="avformat avutil" avio_dir_cmd_deps="avformat avutil"

58
doc/filters.texi
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@ -17983,6 +17983,64 @@ filter").
It accepts the following parameters: It accepts the following parameters:
@table @option
@item mode
The interlacing mode to adopt. It accepts one of the following values:
@table @option
@item 0, send_frame
Output one frame for each frame.
@item 1, send_field
Output one frame for each field.
@item 2, send_frame_nospatial
Like @code{send_frame}, but it skips the spatial interlacing check.
@item 3, send_field_nospatial
Like @code{send_field}, but it skips the spatial interlacing check.
@end table
The default value is @code{send_frame}.
@item parity
The picture field parity assumed for the input interlaced video. It accepts one
of the following values:
@table @option
@item 0, tff
Assume the top field is first.
@item 1, bff
Assume the bottom field is first.
@item -1, auto
Enable automatic detection of field parity.
@end table
The default value is @code{auto}.
If the interlacing is unknown or the decoder does not export this information,
top field first will be assumed.
@item deint
Specify which frames to deinterlace. Accept one of the following
values:
@table @option
@item 0, all
Deinterlace all frames.
@item 1, interlaced
Only deinterlace frames marked as interlaced.
@end table
The default value is @code{all}.
@end table
@section yadif_cuda
Deinterlace the input video using the @ref{yadif} algorithm, but implemented
in CUDA so that it can work as part of a GPU accelerated pipeline with nvdec
and/or nvenc.
It accepts the following parameters:
@table @option @table @option
@item mode @item mode

1
libavfilter/Makefile
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@ -409,6 +409,7 @@ OBJS-$(CONFIG_WEAVE_FILTER) += vf_weave.o
OBJS-$(CONFIG_XBR_FILTER) += vf_xbr.o OBJS-$(CONFIG_XBR_FILTER) += vf_xbr.o
OBJS-$(CONFIG_XSTACK_FILTER) += vf_stack.o framesync.o OBJS-$(CONFIG_XSTACK_FILTER) += vf_stack.o framesync.o
OBJS-$(CONFIG_YADIF_FILTER) += vf_yadif.o yadif_common.o OBJS-$(CONFIG_YADIF_FILTER) += vf_yadif.o yadif_common.o
OBJS-$(CONFIG_YADIF_CUDA_FILTER) += vf_yadif_cuda.o vf_yadif_cuda.ptx.o yadif_common.o
OBJS-$(CONFIG_ZMQ_FILTER) += f_zmq.o OBJS-$(CONFIG_ZMQ_FILTER) += f_zmq.o
OBJS-$(CONFIG_ZOOMPAN_FILTER) += vf_zoompan.o OBJS-$(CONFIG_ZOOMPAN_FILTER) += vf_zoompan.o
OBJS-$(CONFIG_ZSCALE_FILTER) += vf_zscale.o OBJS-$(CONFIG_ZSCALE_FILTER) += vf_zscale.o

1
libavfilter/allfilters.c
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@ -390,6 +390,7 @@ extern AVFilter ff_vf_weave;
extern AVFilter ff_vf_xbr; extern AVFilter ff_vf_xbr;
extern AVFilter ff_vf_xstack; extern AVFilter ff_vf_xstack;
extern AVFilter ff_vf_yadif; extern AVFilter ff_vf_yadif;
extern AVFilter ff_vf_yadif_cuda;
extern AVFilter ff_vf_zmq; extern AVFilter ff_vf_zmq;
extern AVFilter ff_vf_zoompan; extern AVFilter ff_vf_zoompan;
extern AVFilter ff_vf_zscale; extern AVFilter ff_vf_zscale;

2
libavfilter/version.h
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@ -30,7 +30,7 @@
#include "libavutil/version.h" #include "libavutil/version.h"
#define LIBAVFILTER_VERSION_MAJOR 7 #define LIBAVFILTER_VERSION_MAJOR 7
#define LIBAVFILTER_VERSION_MINOR 42 #define LIBAVFILTER_VERSION_MINOR 43
#define LIBAVFILTER_VERSION_MICRO 100 #define LIBAVFILTER_VERSION_MICRO 100
#define LIBAVFILTER_VERSION_INT AV_VERSION_INT(LIBAVFILTER_VERSION_MAJOR, \ #define LIBAVFILTER_VERSION_INT AV_VERSION_INT(LIBAVFILTER_VERSION_MAJOR, \

426
libavfilter/vf_yadif_cuda.c Normal file
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@ -0,0 +1,426 @@
/*
* Copyright (C) 2018 Philip Langdale <philipl@overt.org>
*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
#include <cuda.h>
#include "libavutil/avassert.h"
#include "libavutil/hwcontext_cuda.h"
#include "internal.h"
#include "yadif.h"
extern char vf_yadif_cuda_ptx[];
typedef struct DeintCUDAContext {
YADIFContext yadif;
AVCUDADeviceContext *hwctx;
AVBufferRef *device_ref;
AVBufferRef *input_frames_ref;
AVHWFramesContext *input_frames;
CUcontext cu_ctx;
CUstream stream;
CUmodule cu_module;
CUfunction cu_func_uchar;
CUfunction cu_func_uchar2;
CUfunction cu_func_ushort;
CUfunction cu_func_ushort2;
} DeintCUDAContext;
#define DIV_UP(a, b) ( ((a) + (b) - 1) / (b) )
#define ALIGN_UP(a, b) (((a) + (b) - 1) & ~((b) - 1))
#define BLOCKX 32
#define BLOCKY 16
static int check_cu(AVFilterContext *avctx, CUresult err, const char *func)
{
const char *err_name;
const char *err_string;
av_log(avctx, AV_LOG_TRACE, "Calling %s\n", func);
if (err == CUDA_SUCCESS)
return 0;
cuGetErrorName(err, &err_name);
cuGetErrorString(err, &err_string);
av_log(avctx, AV_LOG_ERROR, "%s failed", func);
if (err_name && err_string)
av_log(avctx, AV_LOG_ERROR, " -> %s: %s", err_name, err_string);
av_log(avctx, AV_LOG_ERROR, "\n");
return AVERROR_EXTERNAL;
}
#define CHECK_CU(x) check_cu(ctx, (x), #x)
static CUresult call_kernel(AVFilterContext *ctx, CUfunction func,
CUdeviceptr prev, CUdeviceptr cur, CUdeviceptr next,
CUarray_format format, int channels,
int src_width, // Width is pixels per channel
int src_height, // Height is pixels per channel
int src_pitch, // Pitch is bytes
CUdeviceptr dst,
int dst_width, // Width is pixels per channel
int dst_height, // Height is pixels per channel
int dst_pitch, // Pitch is pixels per channel
int parity, int tff)
{
DeintCUDAContext *s = ctx->priv;
CUtexObject tex_prev = 0, tex_cur = 0, tex_next = 0;
CUresult err;
int skip_spatial_check = s->yadif.mode&2;
void *args[] = { &dst, &tex_prev, &tex_cur, &tex_next,
&dst_width, &dst_height, &dst_pitch,
&src_width, &src_height, &parity, &tff,
&skip_spatial_check };
CUDA_TEXTURE_DESC tex_desc = {
.filterMode = CU_TR_FILTER_MODE_POINT,
.flags = CU_TRSF_READ_AS_INTEGER,
};
CUDA_RESOURCE_DESC res_desc = {
.resType = CU_RESOURCE_TYPE_PITCH2D,
.res.pitch2D.format = format,
.res.pitch2D.numChannels = channels,
.res.pitch2D.width = src_width,
.res.pitch2D.height = src_height,
.res.pitch2D.pitchInBytes = src_pitch,
};
res_desc.res.pitch2D.devPtr = (CUdeviceptr)prev;
err = CHECK_CU(cuTexObjectCreate(&tex_prev, &res_desc, &tex_desc, NULL));
if (err != CUDA_SUCCESS) {
goto exit;
}
res_desc.res.pitch2D.devPtr = (CUdeviceptr)cur;
err = CHECK_CU(cuTexObjectCreate(&tex_cur, &res_desc, &tex_desc, NULL));
if (err != CUDA_SUCCESS) {
goto exit;
}
res_desc.res.pitch2D.devPtr = (CUdeviceptr)next;
err = CHECK_CU(cuTexObjectCreate(&tex_next, &res_desc, &tex_desc, NULL));
if (err != CUDA_SUCCESS) {
goto exit;
}
err = CHECK_CU(cuLaunchKernel(func,
DIV_UP(dst_width, BLOCKX), DIV_UP(dst_height, BLOCKY), 1,
BLOCKX, BLOCKY, 1,
0, s->stream, args, NULL));
exit:
if (tex_prev)
CHECK_CU(cuTexObjectDestroy(tex_prev));
if (tex_cur)
CHECK_CU(cuTexObjectDestroy(tex_cur));
if (tex_next)
CHECK_CU(cuTexObjectDestroy(tex_next));
return err;
}
static void filter(AVFilterContext *ctx, AVFrame *dst,
int parity, int tff)
{
DeintCUDAContext *s = ctx->priv;
YADIFContext *y = &s->yadif;
CUcontext dummy;
CUresult err;
int i;
err = CHECK_CU(cuCtxPushCurrent(s->cu_ctx));
if (err != CUDA_SUCCESS) {
goto exit;
}
for (i = 0; i < y->csp->nb_components; i++) {
CUfunction func;
CUarray_format format;
int pixel_size, channels;
const AVComponentDescriptor *comp = &y->csp->comp[i];
if (comp->plane < i) {
// We process planes as a whole, so don't reprocess
// them for additional components
continue;
}
pixel_size = (comp->depth + comp->shift) / 8;
channels = comp->step / pixel_size;
if (pixel_size > 2 || channels > 2) {
av_log(ctx, AV_LOG_ERROR, "Unsupported pixel format: %s\n", y->csp->name);
goto exit;
}
switch (pixel_size) {
case 1:
func = channels == 1 ? s->cu_func_uchar : s->cu_func_uchar2;
format = CU_AD_FORMAT_UNSIGNED_INT8;
break;
case 2:
func = channels == 1 ? s->cu_func_ushort : s->cu_func_ushort2;
format = CU_AD_FORMAT_UNSIGNED_INT16;
break;
default:
av_log(ctx, AV_LOG_ERROR, "Unsupported pixel format: %s\n", y->csp->name);
goto exit;
}
av_log(ctx, AV_LOG_TRACE,
"Deinterlacing plane %d: pixel_size: %d channels: %d\n",
comp->plane, pixel_size, channels);
call_kernel(ctx, func,
(CUdeviceptr)y->prev->data[i],
(CUdeviceptr)y->cur->data[i],
(CUdeviceptr)y->next->data[i],
format, channels,
AV_CEIL_RSHIFT(y->cur->width, i ? y->csp->log2_chroma_w : 0),
AV_CEIL_RSHIFT(y->cur->height, i ? y->csp->log2_chroma_h : 0),
y->cur->linesize[i],
(CUdeviceptr)dst->data[i],
AV_CEIL_RSHIFT(dst->width, i ? y->csp->log2_chroma_w : 0),
AV_CEIL_RSHIFT(dst->height, i ? y->csp->log2_chroma_h : 0),
dst->linesize[i] / comp->step,
parity, tff);
}
err = CHECK_CU(cuStreamSynchronize(s->stream));
if (err != CUDA_SUCCESS) {
goto exit;
}
exit:
CHECK_CU(cuCtxPopCurrent(&dummy));
return;
}
static av_cold void deint_cuda_uninit(AVFilterContext *ctx)
{
CUcontext dummy;
DeintCUDAContext *s = ctx->priv;
YADIFContext *y = &s->yadif;
if (s->cu_module) {
CHECK_CU(cuCtxPushCurrent(s->cu_ctx));
CHECK_CU(cuModuleUnload(s->cu_module));
CHECK_CU(cuCtxPopCurrent(&dummy));
}
av_frame_free(&y->prev);
av_frame_free(&y->cur);
av_frame_free(&y->next);
av_buffer_unref(&s->device_ref);
s->hwctx = NULL;
av_buffer_unref(&s->input_frames_ref);
s->input_frames = NULL;
}
static int deint_cuda_query_formats(AVFilterContext *ctx)
{
enum AVPixelFormat pix_fmts[] = {
AV_PIX_FMT_CUDA, AV_PIX_FMT_NONE,
};
int ret;
if ((ret = ff_formats_ref(ff_make_format_list(pix_fmts),
&ctx->inputs[0]->out_formats)) < 0)
return ret;
if ((ret = ff_formats_ref(ff_make_format_list(pix_fmts),
&ctx->outputs[0]->in_formats)) < 0)
return ret;
return 0;
}
static int config_input(AVFilterLink *inlink)
{
AVFilterContext *ctx = inlink->dst;
DeintCUDAContext *s = ctx->priv;
if (!inlink->hw_frames_ctx) {
av_log(ctx, AV_LOG_ERROR, "A hardware frames reference is "
"required to associate the processing device.\n");
return AVERROR(EINVAL);
}
s->input_frames_ref = av_buffer_ref(inlink->hw_frames_ctx);
if (!s->input_frames_ref) {
av_log(ctx, AV_LOG_ERROR, "A input frames reference create "
"failed.\n");
return AVERROR(ENOMEM);
}
s->input_frames = (AVHWFramesContext*)s->input_frames_ref->data;
return 0;
}
static int config_output(AVFilterLink *link)
{
AVHWFramesContext *output_frames;
AVFilterContext *ctx = link->src;
DeintCUDAContext *s = ctx->priv;
YADIFContext *y = &s->yadif;
int ret = 0;
CUcontext dummy;
CUresult err;
av_assert0(s->input_frames);
s->device_ref = av_buffer_ref(s->input_frames->device_ref);
if (!s->device_ref) {
av_log(ctx, AV_LOG_ERROR, "A device reference create "
"failed.\n");
return AVERROR(ENOMEM);
}
s->hwctx = ((AVHWDeviceContext*)s->device_ref->data)->hwctx;
s->cu_ctx = s->hwctx->cuda_ctx;
s->stream = s->hwctx->stream;
link->hw_frames_ctx = av_hwframe_ctx_alloc(s->device_ref);
if (!link->hw_frames_ctx) {
av_log(ctx, AV_LOG_ERROR, "Failed to create HW frame context "
"for output.\n");
ret = AVERROR(ENOMEM);
goto exit;
}
output_frames = (AVHWFramesContext*)link->hw_frames_ctx->data;
output_frames->format = AV_PIX_FMT_CUDA;
output_frames->sw_format = s->input_frames->sw_format;
output_frames->width = ctx->inputs[0]->w;
output_frames->height = ctx->inputs[0]->h;
output_frames->initial_pool_size = 4;
ret = ff_filter_init_hw_frames(ctx, link, 10);
if (ret < 0)
goto exit;
ret = av_hwframe_ctx_init(link->hw_frames_ctx);
if (ret < 0) {
av_log(ctx, AV_LOG_ERROR, "Failed to initialise CUDA frame "
"context for output: %d\n", ret);
goto exit;
}
link->time_base.num = ctx->inputs[0]->time_base.num;
link->time_base.den = ctx->inputs[0]->time_base.den * 2;
link->w = ctx->inputs[0]->w;
link->h = ctx->inputs[0]->h;
if(y->mode & 1)
link->frame_rate = av_mul_q(ctx->inputs[0]->frame_rate,
(AVRational){2, 1});
if (link->w < 3 || link->h < 3) {
av_log(ctx, AV_LOG_ERROR, "Video of less than 3 columns or lines is not supported\n");
ret = AVERROR(EINVAL);
goto exit;
}
y->csp = av_pix_fmt_desc_get(output_frames->sw_format);
y->filter = filter;
err = CHECK_CU(cuCtxPushCurrent(s->cu_ctx));
if (err != CUDA_SUCCESS) {
ret = AVERROR_EXTERNAL;
goto exit;
}
err = CHECK_CU(cuModuleLoadData(&s->cu_module, vf_yadif_cuda_ptx));
if (err != CUDA_SUCCESS) {
ret = AVERROR_INVALIDDATA;
goto exit;
}
err = CHECK_CU(cuModuleGetFunction(&s->cu_func_uchar, s->cu_module, "yadif_uchar"));
if (err != CUDA_SUCCESS) {
ret = AVERROR_INVALIDDATA;
goto exit;
}
err = CHECK_CU(cuModuleGetFunction(&s->cu_func_uchar2, s->cu_module, "yadif_uchar2"));
if (err != CUDA_SUCCESS) {
ret = AVERROR_INVALIDDATA;
goto exit;
}
err= CHECK_CU(cuModuleGetFunction(&s->cu_func_ushort, s->cu_module, "yadif_ushort"));
if (err != CUDA_SUCCESS) {
ret = AVERROR_INVALIDDATA;
goto exit;
}
err = CHECK_CU(cuModuleGetFunction(&s->cu_func_ushort2, s->cu_module, "yadif_ushort2"));
if (err != CUDA_SUCCESS) {
ret = AVERROR_INVALIDDATA;
goto exit;
}
exit:
CHECK_CU(cuCtxPopCurrent(&dummy));
return ret;
}
static const AVClass yadif_cuda_class = {
.class_name = "yadif_cuda",
.item_name = av_default_item_name,
.option = ff_yadif_options,
.version = LIBAVUTIL_VERSION_INT,
.category = AV_CLASS_CATEGORY_FILTER,
};
static const AVFilterPad deint_cuda_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.filter_frame = ff_yadif_filter_frame,
.config_props = config_input,
},
{ NULL }
};
static const AVFilterPad deint_cuda_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.request_frame = ff_yadif_request_frame,
.config_props = config_output,
},
{ NULL }
};
AVFilter ff_vf_yadif_cuda = {
.name = "yadif_cuda",
.description = NULL_IF_CONFIG_SMALL("Deinterlace CUDA frames"),
.priv_size = sizeof(DeintCUDAContext),
.priv_class = &yadif_cuda_class,
.uninit = deint_cuda_uninit,
.query_formats = deint_cuda_query_formats,
.inputs = deint_cuda_inputs,
.outputs = deint_cuda_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_INTERNAL,
.flags_internal = FF_FILTER_FLAG_HWFRAME_AWARE,
};

296
libavfilter/vf_yadif_cuda.cu Normal file
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@ -0,0 +1,296 @@
/*
* Copyright (C) 2018 Philip Langdale <philipl@overt.org>
*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
template<typename T>
__inline__ __device__ T spatial_predictor(T a, T b, T c, T d, T e, T f, T g,
T h, T i, T j, T k, T l, T m, T n)
{
int spatial_pred = (d + k)/2;
int spatial_score = abs(c - j) + abs(d - k) + abs(e - l);
int score = abs(b - k) + abs(c - l) + abs(d - m);
if (score < spatial_score) {
spatial_pred = (c + l)/2;
spatial_score = score;
score = abs(a - l) + abs(b - m) + abs(c - n);
if (score < spatial_score) {
spatial_pred = (b + m)/2;
spatial_score = score;
}
}
score = abs(d - i) + abs(e - j) + abs(f - k);
if (score < spatial_score) {
spatial_pred = (e + j)/2;
spatial_score = score;
score = abs(e - h) + abs(f - i) + abs(g - j);
if (score < spatial_score) {
spatial_pred = (f + i)/2;
spatial_score = score;
}
}
return spatial_pred;
}
__inline__ __device__ int max3(int a, int b, int c)
{
int x = max(a, b);
return max(x, c);
}
__inline__ __device__ int min3(int a, int b, int c)
{
int x = min(a, b);
return min(x, c);
}
template<typename T>
__inline__ __device__ T temporal_predictor(T A, T B, T C, T D, T E, T F,
T G, T H, T I, T J, T K, T L,
T spatial_pred, bool skip_check)
{
int p0 = (C + H) / 2;
int p1 = F;
int p2 = (D + I) / 2;
int p3 = G;
int p4 = (E + J) / 2;
int tdiff0 = abs(D - I);
int tdiff1 = (abs(A - F) + abs(B - G)) / 2;
int tdiff2 = (abs(K - F) + abs(G - L)) / 2;
int diff = max3(tdiff0, tdiff1, tdiff2);
if (!skip_check) {
int maxi = max3(p2 - p3, p2 - p1, min(p0 - p1, p4 - p3));
int mini = min3(p2 - p3, p2 - p1, max(p0 - p1, p4 - p3));
diff = max3(diff, mini, -maxi);
}
if (spatial_pred > p2 + diff) {
spatial_pred = p2 + diff;
}
if (spatial_pred < p2 - diff) {
spatial_pred = p2 - diff;
}
return spatial_pred;
}
template<typename T>
__inline__ __device__ void yadif_single(T *dst,
cudaTextureObject_t prev,
cudaTextureObject_t cur,
cudaTextureObject_t next,
int dst_width, int dst_height, int dst_pitch,
int src_width, int src_height,
int parity, int tff, bool skip_spatial_check)
{
// Identify location
int xo = blockIdx.x * blockDim.x + threadIdx.x;
int yo = blockIdx.y * blockDim.y + threadIdx.y;
if (xo >= dst_width || yo >= dst_height) {
return;
}
// Don't modify the primary field
if (yo % 2 == parity) {
dst[yo*dst_pitch+xo] = tex2D<T>(cur, xo, yo);
return;
}
// Calculate spatial prediction
T a = tex2D<T>(cur, xo - 3, yo - 1);
T b = tex2D<T>(cur, xo - 2, yo - 1);
T c = tex2D<T>(cur, xo - 1, yo - 1);
T d = tex2D<T>(cur, xo - 0, yo - 1);
T e = tex2D<T>(cur, xo + 1, yo - 1);
T f = tex2D<T>(cur, xo + 2, yo - 1);
T g = tex2D<T>(cur, xo + 3, yo - 1);
T h = tex2D<T>(cur, xo - 3, yo + 1);
T i = tex2D<T>(cur, xo - 2, yo + 1);
T j = tex2D<T>(cur, xo - 1, yo + 1);
T k = tex2D<T>(cur, xo - 0, yo + 1);
T l = tex2D<T>(cur, xo + 1, yo + 1);
T m = tex2D<T>(cur, xo + 2, yo + 1);
T n = tex2D<T>(cur, xo + 3, yo + 1);
T spatial_pred =
spatial_predictor(a, b, c, d, e, f, g, h, i, j, k, l, m, n);
// Calculate temporal prediction
int is_second_field = !(parity ^ tff);
cudaTextureObject_t prev2 = prev;
cudaTextureObject_t prev1 = is_second_field ? cur : prev;
cudaTextureObject_t next1 = is_second_field ? next : cur;
cudaTextureObject_t next2 = next;
T A = tex2D<T>(prev2, xo, yo - 1);
T B = tex2D<T>(prev2, xo, yo + 1);
T C = tex2D<T>(prev1, xo, yo - 2);
T D = tex2D<T>(prev1, xo, yo + 0);
T E = tex2D<T>(prev1, xo, yo + 2);
T F = tex2D<T>(cur, xo, yo - 1);
T G = tex2D<T>(cur, xo, yo + 1);
T H = tex2D<T>(next1, xo, yo - 2);
T I = tex2D<T>(next1, xo, yo + 0);
T J = tex2D<T>(next1, xo, yo + 2);
T K = tex2D<T>(next2, xo, yo - 1);
T L = tex2D<T>(next2, xo, yo + 1);
spatial_pred = temporal_predictor(A, B, C, D, E, F, G, H, I, J, K, L,
spatial_pred, skip_spatial_check);
dst[yo*dst_pitch+xo] = spatial_pred;
}
template <typename T>
__inline__ __device__ void yadif_double(T *dst,
cudaTextureObject_t prev,
cudaTextureObject_t cur,
cudaTextureObject_t next,
int dst_width, int dst_height, int dst_pitch,
int src_width, int src_height,
int parity, int tff, bool skip_spatial_check)
{
int xo = blockIdx.x * blockDim.x + threadIdx.x;
int yo = blockIdx.y * blockDim.y + threadIdx.y;
if (xo >= dst_width || yo >= dst_height) {
return;
}
if (yo % 2 == parity) {
// Don't modify the primary field
dst[yo*dst_pitch+xo] = tex2D<T>(cur, xo, yo);
return;
}
T a = tex2D<T>(cur, xo - 3, yo - 1);
T b = tex2D<T>(cur, xo - 2, yo - 1);
T c = tex2D<T>(cur, xo - 1, yo - 1);
T d = tex2D<T>(cur, xo - 0, yo - 1);
T e = tex2D<T>(cur, xo + 1, yo - 1);
T f = tex2D<T>(cur, xo + 2, yo - 1);
T g = tex2D<T>(cur, xo + 3, yo - 1);
T h = tex2D<T>(cur, xo - 3, yo + 1);
T i = tex2D<T>(cur, xo - 2, yo + 1);
T j = tex2D<T>(cur, xo - 1, yo + 1);
T k = tex2D<T>(cur, xo - 0, yo + 1);
T l = tex2D<T>(cur, xo + 1, yo + 1);
T m = tex2D<T>(cur, xo + 2, yo + 1);
T n = tex2D<T>(cur, xo + 3, yo + 1);
T spatial_pred = {
spatial_predictor(a.x, b.x, c.x, d.x, e.x, f.x, g.x, h.x, i.x, j.x, k.x, l.x, m.x, n.x),
spatial_predictor(a.y, b.y, c.y, d.y, e.y, f.y, g.y, h.y, i.y, j.y, k.y, l.y, m.y, n.y) };
// Calculate temporal prediction
int is_second_field = !(parity ^ tff);
cudaTextureObject_t prev2 = prev;
cudaTextureObject_t prev1 = is_second_field ? cur : prev;
cudaTextureObject_t next1 = is_second_field ? next : cur;
cudaTextureObject_t next2 = next;
T A = tex2D<T>(prev2, xo, yo - 1);
T B = tex2D<T>(prev2, xo, yo + 1);
T C = tex2D<T>(prev1, xo, yo - 2);
T D = tex2D<T>(prev1, xo, yo + 0);
T E = tex2D<T>(prev1, xo, yo + 2);
T F = tex2D<T>(cur, xo, yo - 1);
T G = tex2D<T>(cur, xo, yo + 1);
T H = tex2D<T>(next1, xo, yo - 2);
T I = tex2D<T>(next1, xo, yo + 0);
T J = tex2D<T>(next1, xo, yo + 2);
T K = tex2D<T>(next2, xo, yo - 1);
T L = tex2D<T>(next2, xo, yo + 1);
spatial_pred = {
temporal_predictor(A.x, B.x, C.x, D.x, E.x, F.x, G.x, H.x, I.x, J.x, K.x, L.x,
spatial_pred.x, skip_spatial_check),
temporal_predictor(A.y, B.y, C.y, D.y, E.y, F.y, G.y, H.y, I.y, J.y, K.y, L.y,
spatial_pred.y, skip_spatial_check) };
dst[yo*dst_pitch+xo] = spatial_pred;
}
extern "C" {
__global__ void yadif_uchar(unsigned char *dst,
cudaTextureObject_t prev,
cudaTextureObject_t cur,
cudaTextureObject_t next,
int dst_width, int dst_height, int dst_pitch,
int src_width, int src_height,
int parity, int tff, bool skip_spatial_check)
{
yadif_single(dst, prev, cur, next,
dst_width, dst_height, dst_pitch,
src_width, src_height,
parity, tff, skip_spatial_check);
}
__global__ void yadif_ushort(unsigned short *dst,
cudaTextureObject_t prev,
cudaTextureObject_t cur,
cudaTextureObject_t next,
int dst_width, int dst_height, int dst_pitch,
int src_width, int src_height,
int parity, int tff, bool skip_spatial_check)
{
yadif_single(dst, prev, cur, next,
dst_width, dst_height, dst_pitch,
src_width, src_height,
parity, tff, skip_spatial_check);
}
__global__ void yadif_uchar2(uchar2 *dst,
cudaTextureObject_t prev,
cudaTextureObject_t cur,
cudaTextureObject_t next,
int dst_width, int dst_height, int dst_pitch,
int src_width, int src_height,
int parity, int tff, bool skip_spatial_check)
{
yadif_double(dst, prev, cur, next,
dst_width, dst_height, dst_pitch,
src_width, src_height,
parity, tff, skip_spatial_check);
}
__global__ void yadif_ushort2(ushort2 *dst,
cudaTextureObject_t prev,
cudaTextureObject_t cur,
cudaTextureObject_t next,
int dst_width, int dst_height, int dst_pitch,
int src_width, int src_height,
int parity, int tff, bool skip_spatial_check)
{
yadif_double(dst, prev, cur, next,
dst_width, dst_height, dst_pitch,
src_width, src_height,
parity, tff, skip_spatial_check);
}
} /* extern "C" */