前言
本篇文章的丢帧是依据编码后的码率和目标码率来决定丢帧，
而下一篇文章介绍的丢帧依据是目标帧率。
由此可对丢帧策略分类如下：
- 编码后的码率和目标码率来决定丢帧
- 目标帧率决定丢帧
整个帧率控制多次使用的算法---指数权重滤波（暂且如此命名）
在exp_filter.cc文件中：
#include "webrtc/base/exp_filter.h"
#include <math.h>
namespace rtc {
const float ExpFilter::kValueUndefined = -1.0f;
void ExpFilter::Reset(float alpha) {
alpha_ = alpha;
filtered_ = kValueUndefined;
}
float ExpFilter::Apply(float exp, float sample) {
if (filtered_ == kValueUndefined) {
// Initialize filtered value.
filtered_ = sample;
} else if (exp == 1.0) {
filtered_ = alpha_ * filtered_ + (1 - alpha_) * sample;
} else {
float alpha = pow(alpha_, exp);
filtered_ = alpha * filtered_ + (1 - alpha) * sample;
}
if (max_ != kValueUndefined && filtered_ > max_) {
filtered_ = max_;
}
return filtered_;
}
void ExpFilter::UpdateBase(float alpha) {
alpha_ = alpha;
}
} // namespace rtc
这个文件的大概思想就是对历史值和当前值做指数加权求和。公式为：
f(x)=alpha*f(x-1)+(1-alpha)*sample;
alpha=pow(alpha_, exp);
其中alpha_为设定常量，exp为幂次方，sample为最新样点值。
后面还有：
f(x)=min(f(x),max);即不要超过max。
调用丢帧
bool MediaOptimization::DropFrame() {
CriticalSectionScoped lock(crit_sect_.get());
UpdateIncomingFrameRate();
// Leak appropriate number of bytes.
frame_dropper_->Leak((uint32_t)(InputFrameRateInternal() + 0.5f));
if (video_suspended_) {
return true; // Drop all frames when muted.
}
return frame_dropper_->DropFrame();
}
解释：
- UpdateIncomingFrameRate();更新采集出来的帧率。
- frame_dropper_->Leak((uint32_t)(InputFrameRateInternal() + 0.5f));这里主要利用采集帧率，去更新丢帧比率等关键丢帧信息。
- return frame_dropper_->DropFrame();这里就是根据前面计算的丢帧比率等去实现均匀丢帧。
这些函数的具体实现后面会一一介绍。
更新采集出来的帧率
void MediaOptimization::UpdateIncomingFrameRate() {
int64_t now = clock_->TimeInMilliseconds();
if (incoming_frame_times_[0] == 0) {
// No shifting if this is the first time.
} else {
// Shift all times one step.
for (int32_t i = (kFrameCountHistorySize - 2); i >= 0; i--) {
incoming_frame_times_[i + 1] = incoming_frame_times_[i];
}
}
incoming_frame_times_[0] = now;
ProcessIncomingFrameRate(now);
}
//framerate=n/t
void MediaOptimization::ProcessIncomingFrameRate(int64_t now) {
int32_t num = 0;
int32_t nr_of_frames = 0;
for (num = 1; num < (kFrameCountHistorySize - 1); ++num) {
if (incoming_frame_times_[num] <= 0 ||
// don't use data older than 2 s
now - incoming_frame_times_[num] > kFrameHistoryWinMs) {
break;
} else {
nr_of_frames++;
}
}
if (num > 1) {
const int64_t diff = now - incoming_frame_times_[num - 1];
incoming_frame_rate_ = 1.0;
if (diff > 0) {
incoming_frame_rate_ = nr_of_frames * 1000.0f / static_cast<float>(diff);
}
}
}
解释：
这一段比较好理解，就是根据每一帧到来的时间，最多2秒钟的统计，利用公式：
incoming_frame_rate_ = nr_of_frames * 1000.0f / static_cast<float>(diff);
得到这一段时间的采集帧率。
对于统计数据，
for (int32_t i = (kFrameCountHistorySize - 2); i >= 0; i--) {
incoming_frame_times_[i + 1] = incoming_frame_times_[i];
}
可见这是一个滑动窗口，即总是用最新的kFrameCountHistorySize 大小的数据。
丢帧算法主要实现
丢帧算法全部在frame_dropper.cc文件中，下面先通过代码解读，在细说算法实现。
此为frame_dropper.cc文件内容，及注释
/*
* Copyright (c) 2011 The WebRTC project authors. All Rights Reserved.
*
* Use of this source code is governed by a BSD-style license
* that can be found in the LICENSE file in the root of the source
* tree. An additional intellectual property rights grant can be found
* in the file PATENTS. All contributing project authors may
* be found in the AUTHORS file in the root of the source tree.
*/
#include "webrtc/modules/video_coding/utility/include/frame_dropper.h"
#include "webrtc/system_wrappers/interface/trace.h"
namespace webrtc
{
const float kDefaultKeyFrameSizeAvgKBits = 0.9f;
const float kDefaultKeyFrameRatio = 0.99f;
const float kDefaultDropRatioAlpha = 0.9f;
const float kDefaultDropRatioMax = 0.96f;
const float kDefaultMaxTimeToDropFrames = 4.0f; // In seconds.
FrameDropper::FrameDropper()
:
_keyFrameSizeAvgKbits(kDefaultKeyFrameSizeAvgKBits),
_keyFrameRatio(kDefaultKeyFrameRatio),
_dropRatio(kDefaultDropRatioAlpha, kDefaultDropRatioMax),
_enabled(true),
_max_time_drops(kDefaultMaxTimeToDropFrames)
{
Reset();
}
FrameDropper::FrameDropper(float max_time_drops)
:
_keyFrameSizeAvgKbits(kDefaultKeyFrameSizeAvgKBits),
_keyFrameRatio(kDefaultKeyFrameRatio),
_dropRatio(kDefaultDropRatioAlpha, kDefaultDropRatioMax),
_enabled(true),
_max_time_drops(max_time_drops)
{
Reset();
}
void
FrameDropper::Reset()
{
_keyFrameRatio.Reset(0.99f);
_keyFrameRatio.Apply(1.0f, 1.0f/300.0f); // 1 key frame every 10th second in 30 fps
_keyFrameSizeAvgKbits.Reset(0.9f);
_keyFrameCount = 0;
_accumulator = 0.0f;
_accumulatorMax = 150.0f; // assume 300 kb/s and 0.5 s window
_targetBitRate = 300.0f;
_incoming_frame_rate = 30;
_keyFrameSpreadFrames = 0.5f * _incoming_frame_rate;
_dropNext = false;
_dropRatio.Reset(0.9f);
_dropRatio.Apply(0.0f, 0.0f); // Initialize to 0
_dropCount = 0;
_windowSize = 0.5f;
_wasBelowMax = true;
_fastMode = false; // start with normal (non-aggressive) mode
// Cap for the encoder buffer level/accumulator, in secs.
_cap_buffer_size = 3.0f;
// Cap on maximum amount of dropped frames between kept frames, in secs.
_max_time_drops = 4.0f;
}
void
FrameDropper::Enable(bool enable)
{
_enabled = enable;
}
//deltaFrame : 0:key frame 1:P frame
void
FrameDropper::Fill(size_t frameSizeBytes, bool deltaFrame)
{
if (!_enabled)
{
return;
}
float frameSizeKbits = 8.0f * static_cast<float>(frameSizeBytes) / 1000.0f;
if (!deltaFrame && !_fastMode) // fast mode does not treat key-frames any different//非fast_mode而且key_frame
{
//exp=1.0时，filtered_ = alpha_ * filtered_ + (1 - alpha_) * sample;当alpha_=0.8或0.9时，则更偏重于历史值，而非当前sample
_keyFrameSizeAvgKbits.Apply(1, frameSizeKbits);
_keyFrameRatio.Apply(1.0, 1.0);//_keyFrameRatio同样偏重于历史值，而当前值设置为1，因为当前为key frame ，所以值为1
if (frameSizeKbits > _keyFrameSizeAvgKbits.filtered())//当前值大于均值
{
// Remove the average key frame size since we
// compensate for key frames when adding delta
// frames.
frameSizeKbits -= _keyFrameSizeAvgKbits.filtered();//超出均值的部分
}
else
{
// Shouldn't be negative, so zero is the lower bound.
frameSizeKbits = 0;
}
if (_keyFrameRatio.filtered() > 1e-5 &&
1 / _keyFrameRatio.filtered() < _keyFrameSpreadFrames) //_keyFrameSpreadFrames = 0.5f * inputFrameRate;
{
// We are sending key frames more often than our upper bound for
// how much we allow the key frame compensation to be spread
// out in time. Therefor we must use the key frame ratio rather
// than keyFrameSpreadFrames.
_keyFrameCount =
static_cast<int32_t>(1 / _keyFrameRatio.filtered() + 0.5);//每一秒关键帧的数量？
}
else
{
// Compensate for the key frame the following frames
_keyFrameCount = static_cast<int32_t>(_keyFrameSpreadFrames + 0.5);
}
}
else
{
// Decrease the keyFrameRatio
_keyFrameRatio.Apply(1.0, 0.0);//因为这是P帧，降低_keyFrameRatio的fileter值，因为sample=0
}
// Change the level of the accumulator (bucket)
_accumulator += frameSizeKbits; //_accumulator是frameSizeKbits的累加器，表示超过均值的bit值累加
CapAccumulator();//max_accumulator = _targetBitRate * _cap_buffer_size;累加器最多为max_accumulator,3倍目标码率
}
void
FrameDropper::Leak(uint32_t inputFrameRate)
{
if (!_enabled)
{
return;
}
if (inputFrameRate < 1)
{
return;
}
if (_targetBitRate < 0.0f)
{
return;
}
_keyFrameSpreadFrames = 0.5f * inputFrameRate;
// T is the expected bits per frame (target). If all frames were the same size,
// we would get T bits per frame. Notice that T is also weighted to be able to
// force a lower frame rate if wanted.
float T = _targetBitRate / inputFrameRate;//T:每一帧期望的bit大小，从下面内容，明显这个T代表的是每个P帧期望的大小，K帧是另外补偿的
if (_keyFrameCount > 0)
{
// Perform the key frame compensation
if (_keyFrameRatio.filtered() > 0 &&
1 / _keyFrameRatio.filtered() < _keyFrameSpreadFrames)
{
T -= _keyFrameSizeAvgKbits.filtered() * _keyFrameRatio.filtered();//_keyFrameSizeAvgKbits.filtered() * _keyFrameRatio.filtered()为keyframe在每一帧均摊的占用的kbit
}
else
{
T -= _keyFrameSizeAvgKbits.filtered() / _keyFrameSpreadFrames;//
}
_keyFrameCount--;//补偿一个关键帧，则关键帧数-1.
}
_accumulator -= T;//累加器在编码后增加，在编码前减去当前帧占用的大小
if (_accumulator < 0.0f)
{
_accumulator = 0.0f;
}
UpdateRatio();
}
void
FrameDropper::UpdateNack(uint32_t nackBytes)
{
if (!_enabled)
{
return;
}
_accumulator += static_cast<float>(nackBytes) * 8.0f / 1000.0f;
}
void
FrameDropper::FillBucket(float inKbits, float outKbits)
{
_accumulator += (inKbits - outKbits);
}
void
FrameDropper::UpdateRatio()
{
if (_accumulator > 1.3f * _accumulatorMax)//_accumulatorMax = bitRate * _windowSize;累加器过大之后，减小alpha值，_dropRatio更偏重当前值
{
// Too far above accumulator max, react faster
_dropRatio.UpdateBase(0.8f);
}
else
{
// Go back to normal reaction
_dropRatio.UpdateBase(0.9f);
}
if (_accumulator > _accumulatorMax)
{
// We are above accumulator max, and should ideally
// drop a frame. Increase the dropRatio and drop
// the frame later.
if (_wasBelowMax)//_wasBelowMax = _accumulator < _accumulatorMax;上一次小于_accumulatorMax
{
_dropNext = true;//丢掉下一帧
}
if (_fastMode)
{
// always drop in aggressive mode
_dropNext = true;
}
_dropRatio.Apply(1.0f, 1.0f);//因为丢帧，所以sample为1
_dropRatio.UpdateBase(0.9f);
}
else
{
_dropRatio.Apply(1.0f, 0.0f);//不丢帧，sample为0
}
_wasBelowMax = _accumulator < _accumulatorMax;
}
// This function signals when to drop frames to the caller. It makes use of the dropRatio
// to smooth out the drops over time.
bool
FrameDropper::DropFrame()
{
if (!_enabled)
{
return false;
}
if (_dropNext)
{
_dropNext = false;
_dropCount = 0;
}
if (_dropRatio.filtered() >= 0.5f) // Drops per keep//>=0.5表示当前帧不丢，下一帧一定丢，即2个至少丢一个
{
// limit is the number of frames we should drop between each kept frame
// to keep our drop ratio. limit is positive in this case.
float denom = 1.0f - _dropRatio.filtered();//denom:分母，表示不丢的比率
if (denom < 1e-5)
{
denom = (float)1e-5;
}
int32_t limit = static_cast<int32_t>(1.0f / denom - 1.0f + 0.5f);//这里注释意思limit代表需要丢掉的帧数，即如果当前帧不丢，则后面有limit帧需要丢掉
// Put a bound on the max amount of dropped frames between each kept
// frame, in terms of frame rate and window size (secs).
int max_limit = static_cast<int>(_incoming_frame_rate *
_max_time_drops);//4倍帧率，max_limit则表示连续丢掉4倍帧率的帧，明显太大了
if (limit > max_limit) {
limit = max_limit;
}
if (_dropCount < 0)//_dropCount表示当前这一轮丢帧，已经丢掉的帧数
{
// Reset the _dropCount since it was negative and should be positive.
if (_dropRatio.filtered() > 0.4f)
{
_dropCount = -_dropCount;
}
else
{
_dropCount = 0;
}
}
if (_dropCount < limit)//直到丢掉limit帧
{
// As long we are below the limit we should drop frames.
_dropCount++;
return true;
}
else
{
// Only when we reset _dropCount a frame should be kept.
_dropCount = 0;
return false;
}
}
else if (_dropRatio.filtered() > 0.0f &&
_dropRatio.filtered() < 0.5f) // Keeps per drop//表示当前帧不丢，下一帧可能丢，也可能不丢，即每隔若干帧丢一帧
{
// limit is the number of frames we should keep between each drop
// in order to keep the drop ratio. limit is negative in this case,
// and the _dropCount is also negative.
float denom = _dropRatio.filtered();
if (denom < 1e-5)
{
denom = (float)1e-5;
}
int32_t limit = -static_cast<int32_t>(1.0f / denom - 1.0f + 0.5f);
if (_dropCount > 0)
{
// Reset the _dropCount since we have a positive
// _dropCount, and it should be negative.
if (_dropRatio.filtered() < 0.6f)
{
_dropCount = -_dropCount;
}
else
{
_dropCount = 0;
}
}
if (_dropCount > limit)
{
if (_dropCount == 0)
{
// Drop frames when we reset _dropCount.
_dropCount--;
return true;//丢，明显每次只丢一帧
}
else
{
// Keep frames as long as we haven't reached limit.
_dropCount--;
return false;//不丢，直到_dropCount > limit，则重新置_dropCount = 0;开始新一轮丢帧
}
}
else
{
_dropCount = 0;
return false;
}
}
_dropCount = 0;
return false;
// A simpler version, unfiltered and quicker
//bool dropNext = _dropNext;
//_dropNext = false;
//return dropNext;
}
void
FrameDropper::SetRates(float bitRate, float incoming_frame_rate)
{
// Bit rate of -1 means infinite bandwidth.
_accumulatorMax = bitRate * _windowSize; // bitRate * windowSize (in seconds)
if (_targetBitRate > 0.0f && bitRate < _targetBitRate && _accumulator > _accumulatorMax)
{
// Rescale the accumulator level if the accumulator max decreases
_accumulator = bitRate / _targetBitRate * _accumulator;
}
_targetBitRate = bitRate;
CapAccumulator();
_incoming_frame_rate = incoming_frame_rate;
}
float
FrameDropper::ActualFrameRate(uint32_t inputFrameRate) const
{
if (!_enabled)
{
return static_cast<float>(inputFrameRate);
}
return inputFrameRate * (1.0f - _dropRatio.filtered());//实际编码帧率
}
// Put a cap on the accumulator, i.e., don't let it grow beyond some level.
// This is a temporary fix for screencasting where very large frames from
// encoder will cause very slow response (too many frame drops).
void FrameDropper::CapAccumulator() {
float max_accumulator = _targetBitRate * _cap_buffer_size;
if (_accumulator > max_accumulator) {
_accumulator = max_accumulator;
}
}
}
1、丢帧的决定因素在_dropRatio.Apply(1.0f, 1.0f);通过给_dropRatio赋值，使得_dropRatio不为0.而_dropRatio.Apply(1.0f, 1.0f);调用的起因，还在
int32_t VCMEncodedFrameCallback::Encoded
->int32_t MediaOptimization::UpdateWithEncodedData
->FrameDropper::Fill(size_t frameSizeBytes, bool deltaFrame)
通过Fill函数中的_accumulator（累加器），再通过
FrameDropper::Leak(uint32_t inputFrameRate)
->FrameDropper::UpdateRatio()
来最终调用_dropRatio.Apply(1.0f, 1.0f)或_dropRatio.Apply(1.0f, 0.0f)
2、丢帧的方法
在FrameDropper::DropFrame()函数中，通过上面注释的代码也可以理解。
drop.png
就是当dropRatio>=0.5时，两个帧之间可能丢多个；当dropRatio<0.5时，两个帧之间最多丢一个。
3、调用丢帧的地方
- int32_t VideoSender::AddVideoFrame()帧数据加入encoder之前
4、如何从_accumulator控制帧率
- FrameDropper::Fill()中，每编码完一帧数据，就将数据的大小累加到_accumulator，其中P帧全部累加，K帧只加超出均值的部分。
- 每个采集后，即将给到编码器的帧，利用_targetBitRate / inputFrameRate;得到每一帧期望占用的bit大小，其中K帧单独计算：
_keyFrameSizeAvgKbits.filtered() * _keyFrameRatio.filtered();
疑问：
为什么_accumulator累加时，K帧只加超出均值的部分，而不是全部。
```
5、什么时候丢帧
_accumulator > _accumulatorMax；
其中，_accumulatorMax = bitRate * _windowSize;（_windowSize=0.5f）
##编码完后，更新_accumulator
这一部分只是说明编码完后怎么去更新_accumulator 的流程，比较容易看懂。
```
int32_t VCMEncodedFrameCallback::Encoded(
const EncodedImage& encodedImage,
const CodecSpecificInfo* codecSpecificInfo,
const RTPFragmentationHeader* fragmentationHeader) {
post_encode_callback_->Encoded(encodedImage, NULL, NULL);
if (_sendCallback == NULL) {
return VCM_UNINITIALIZED;
}
RTPVideoHeader rtpVideoHeader;
memset(&rtpVideoHeader, 0, sizeof(RTPVideoHeader));
RTPVideoHeader* rtpVideoHeaderPtr = &rtpVideoHeader;
CopyCodecSpecific(codecSpecificInfo, &rtpVideoHeaderPtr);
int32_t callbackReturn = _sendCallback->SendData(
_payloadType, encodedImage, *fragmentationHeader, rtpVideoHeaderPtr);
if (callbackReturn < 0) {
return callbackReturn;
}
if (_mediaOpt != NULL) {
//编码后的统计信息更新
_mediaOpt->UpdateWithEncodedData(encodedImage);
if (_internalSource)
return _mediaOpt->DropFrame(); // Signal to encoder to drop next frame.
}
return VCM_OK;
}
```
```
int32_t MediaOptimization::UpdateWithEncodedData(
const EncodedImage& encoded_image) {
size_t encoded_length = encoded_image._length;
uint32_t timestamp = encoded_image._timeStamp;
CriticalSectionScoped lock(crit_sect_.get());
const int64_t now_ms = clock_->TimeInMilliseconds();
PurgeOldFrameSamples(now_ms);
if (encoded_frame_samples_.size() > 0 &&
encoded_frame_samples_.back().timestamp == timestamp) {
// Frames having the same timestamp are generated from the same input
// frame. We don't want to double count them, but only increment the
// size_bytes.
encoded_frame_samples_.back().size_bytes += encoded_length;
encoded_frame_samples_.back().time_complete_ms = now_ms;
} else {
encoded_frame_samples_.push_back(
EncodedFrameSample(encoded_length, timestamp, now_ms));
}
UpdateSentBitrate(now_ms);
UpdateSentFramerate();
if (encoded_length > 0) {
const bool delta_frame = encoded_image._frameType != kKeyFrame;//0:key 1:P
//这里将每次编码完的数据长度Fill到frame_dropper
frame_dropper_->Fill(encoded_length, delta_frame);
if (max_payload_size_ > 0 && encoded_length > 0) {
const float min_packets_per_frame =
encoded_length / static_cast<float>(max_payload_size_);
if (delta_frame) {
loss_prot_logic_->UpdatePacketsPerFrame(min_packets_per_frame,
clock_->TimeInMilliseconds());
} else {
loss_prot_logic_->UpdatePacketsPerFrameKey(
min_packets_per_frame, clock_->TimeInMilliseconds());
}
if (enable_qm_) {
// Update quality select with encoded length.
qm_resolution_->UpdateEncodedSize(encoded_length);
}
}
if (!delta_frame && encoded_length > 0) {
loss_prot_logic_->UpdateKeyFrameSize(static_cast<float>(encoded_length));
}
// Updating counters.
if (delta_frame) {
delta_frame_cnt_++;
} else {
key_frame_cnt_++;
}
}
return VCM_OK;
}
```
解释：
编码完后的数据都是经过callback回调的，
```
int32_t VCMEncodedFrameCallback::Encoded
->int32_t MediaOptimization::UpdateWithEncodedData
->frame_dropper_->Fill(encoded_length, delta_frame);
```
经过这个流程，每次编码后，送给发送的数据都要去更新frame_dropper_。
后记：
作者对于这一个算法的机制原理，也不是很明白，只能从代码中体会算法实现，不免有错误理解，如有更好理解或者不同见解的道友，敬请赐教，不胜感激！