| Index: third_party/libwebp/enc/analysis.c
|
| diff --git a/third_party/libwebp/enc/analysis.c b/third_party/libwebp/enc/analysis.c
|
| index 22cfb492e72be396a7a610a215e8e599664734da..221e9d064c47a5647eaa5e055899886ed3d38d4b 100644
|
| --- a/third_party/libwebp/enc/analysis.c
|
| +++ b/third_party/libwebp/enc/analysis.c
|
| @@ -23,10 +23,6 @@ extern "C" {
|
|
|
| #define MAX_ITERS_K_MEANS 6
|
|
|
| -static int ClipAlpha(int alpha) {
|
| - return alpha < 0 ? 0 : alpha > 255 ? 255 : alpha;
|
| -}
|
| -
|
| //------------------------------------------------------------------------------
|
| // Smooth the segment map by replacing isolated block by the majority of its
|
| // neighbours.
|
| @@ -72,50 +68,10 @@ static void SmoothSegmentMap(VP8Encoder* const enc) {
|
| }
|
|
|
| //------------------------------------------------------------------------------
|
| -// Finalize Segment probability based on the coding tree
|
| -
|
| -static int GetProba(int a, int b) {
|
| - int proba;
|
| - const int total = a + b;
|
| - if (total == 0) return 255; // that's the default probability.
|
| - proba = (255 * a + total / 2) / total;
|
| - return proba;
|
| -}
|
| -
|
| -static void SetSegmentProbas(VP8Encoder* const enc) {
|
| - int p[NUM_MB_SEGMENTS] = { 0 };
|
| - int n;
|
| -
|
| - for (n = 0; n < enc->mb_w_ * enc->mb_h_; ++n) {
|
| - const VP8MBInfo* const mb = &enc->mb_info_[n];
|
| - p[mb->segment_]++;
|
| - }
|
| - if (enc->pic_->stats) {
|
| - for (n = 0; n < NUM_MB_SEGMENTS; ++n) {
|
| - enc->pic_->stats->segment_size[n] = p[n];
|
| - }
|
| - }
|
| - if (enc->segment_hdr_.num_segments_ > 1) {
|
| - uint8_t* const probas = enc->proba_.segments_;
|
| - probas[0] = GetProba(p[0] + p[1], p[2] + p[3]);
|
| - probas[1] = GetProba(p[0], p[1]);
|
| - probas[2] = GetProba(p[2], p[3]);
|
| -
|
| - enc->segment_hdr_.update_map_ =
|
| - (probas[0] != 255) || (probas[1] != 255) || (probas[2] != 255);
|
| - enc->segment_hdr_.size_ =
|
| - p[0] * (VP8BitCost(0, probas[0]) + VP8BitCost(0, probas[1])) +
|
| - p[1] * (VP8BitCost(0, probas[0]) + VP8BitCost(1, probas[1])) +
|
| - p[2] * (VP8BitCost(1, probas[0]) + VP8BitCost(0, probas[2])) +
|
| - p[3] * (VP8BitCost(1, probas[0]) + VP8BitCost(1, probas[2]));
|
| - } else {
|
| - enc->segment_hdr_.update_map_ = 0;
|
| - enc->segment_hdr_.size_ = 0;
|
| - }
|
| -}
|
| +// set segment susceptibility alpha_ / beta_
|
|
|
| static WEBP_INLINE int clip(int v, int m, int M) {
|
| - return v < m ? m : v > M ? M : v;
|
| + return (v < m) ? m : (v > M) ? M : v;
|
| }
|
|
|
| static void SetSegmentAlphas(VP8Encoder* const enc,
|
| @@ -142,22 +98,63 @@ static void SetSegmentAlphas(VP8Encoder* const enc,
|
| }
|
|
|
| //------------------------------------------------------------------------------
|
| +// Compute susceptibility based on DCT-coeff histograms:
|
| +// the higher, the "easier" the macroblock is to compress.
|
| +
|
| +#define MAX_ALPHA 255 // 8b of precision for susceptibilities.
|
| +#define ALPHA_SCALE (2 * MAX_ALPHA) // scaling factor for alpha.
|
| +#define DEFAULT_ALPHA (-1)
|
| +#define IS_BETTER_ALPHA(alpha, best_alpha) ((alpha) > (best_alpha))
|
| +
|
| +static int FinalAlphaValue(int alpha) {
|
| + alpha = MAX_ALPHA - alpha;
|
| + return clip(alpha, 0, MAX_ALPHA);
|
| +}
|
| +
|
| +static int GetAlpha(const VP8Histogram* const histo) {
|
| + int max_value = 0, last_non_zero = 1;
|
| + int k;
|
| + int alpha;
|
| + for (k = 0; k <= MAX_COEFF_THRESH; ++k) {
|
| + const int value = histo->distribution[k];
|
| + if (value > 0) {
|
| + if (value > max_value) max_value = value;
|
| + last_non_zero = k;
|
| + }
|
| + }
|
| + // 'alpha' will later be clipped to [0..MAX_ALPHA] range, clamping outer
|
| + // values which happen to be mostly noise. This leaves the maximum precision
|
| + // for handling the useful small values which contribute most.
|
| + alpha = (max_value > 1) ? ALPHA_SCALE * last_non_zero / max_value : 0;
|
| + return alpha;
|
| +}
|
| +
|
| +static void MergeHistograms(const VP8Histogram* const in,
|
| + VP8Histogram* const out) {
|
| + int i;
|
| + for (i = 0; i <= MAX_COEFF_THRESH; ++i) {
|
| + out->distribution[i] += in->distribution[i];
|
| + }
|
| +}
|
| +
|
| +//------------------------------------------------------------------------------
|
| // Simplified k-Means, to assign Nb segments based on alpha-histogram
|
|
|
| -static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
|
| +static void AssignSegments(VP8Encoder* const enc,
|
| + const int alphas[MAX_ALPHA + 1]) {
|
| const int nb = enc->segment_hdr_.num_segments_;
|
| int centers[NUM_MB_SEGMENTS];
|
| int weighted_average = 0;
|
| - int map[256];
|
| + int map[MAX_ALPHA + 1];
|
| int a, n, k;
|
| - int min_a = 0, max_a = 255, range_a;
|
| + int min_a = 0, max_a = MAX_ALPHA, range_a;
|
| // 'int' type is ok for histo, and won't overflow
|
| int accum[NUM_MB_SEGMENTS], dist_accum[NUM_MB_SEGMENTS];
|
|
|
| // bracket the input
|
| - for (n = 0; n < 256 && alphas[n] == 0; ++n) {}
|
| + for (n = 0; n <= MAX_ALPHA && alphas[n] == 0; ++n) {}
|
| min_a = n;
|
| - for (n = 255; n > min_a && alphas[n] == 0; --n) {}
|
| + for (n = MAX_ALPHA; n > min_a && alphas[n] == 0; --n) {}
|
| max_a = n;
|
| range_a = max_a - min_a;
|
|
|
| @@ -210,7 +207,7 @@ static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
|
| VP8MBInfo* const mb = &enc->mb_info_[n];
|
| const int alpha = mb->alpha_;
|
| mb->segment_ = map[alpha];
|
| - mb->alpha_ = centers[map[alpha]]; // just for the record.
|
| + mb->alpha_ = centers[map[alpha]]; // for the record.
|
| }
|
|
|
| if (nb > 1) {
|
| @@ -218,7 +215,6 @@ static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
|
| if (smooth) SmoothSegmentMap(enc);
|
| }
|
|
|
| - SetSegmentProbas(enc); // Assign final proba
|
| SetSegmentAlphas(enc, centers, weighted_average); // pick some alphas.
|
| }
|
|
|
| @@ -227,24 +223,32 @@ static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
|
| // susceptibility and set best modes for this macroblock.
|
| // Segment assignment is done later.
|
|
|
| -// Number of modes to inspect for alpha_ evaluation. For high-quality settings,
|
| -// we don't need to test all the possible modes during the analysis phase.
|
| +// Number of modes to inspect for alpha_ evaluation. For high-quality settings
|
| +// (method >= FAST_ANALYSIS_METHOD) we don't need to test all the possible modes
|
| +// during the analysis phase.
|
| +#define FAST_ANALYSIS_METHOD 4 // method above which we do partial analysis
|
| #define MAX_INTRA16_MODE 2
|
| #define MAX_INTRA4_MODE 2
|
| #define MAX_UV_MODE 2
|
|
|
| static int MBAnalyzeBestIntra16Mode(VP8EncIterator* const it) {
|
| - const int max_mode = (it->enc_->method_ >= 3) ? MAX_INTRA16_MODE : 4;
|
| + const int max_mode =
|
| + (it->enc_->method_ >= FAST_ANALYSIS_METHOD) ? MAX_INTRA16_MODE
|
| + : NUM_PRED_MODES;
|
| int mode;
|
| - int best_alpha = -1;
|
| + int best_alpha = DEFAULT_ALPHA;
|
| int best_mode = 0;
|
|
|
| VP8MakeLuma16Preds(it);
|
| for (mode = 0; mode < max_mode; ++mode) {
|
| - const int alpha = VP8CollectHistogram(it->yuv_in_ + Y_OFF,
|
| - it->yuv_p_ + VP8I16ModeOffsets[mode],
|
| - 0, 16);
|
| - if (alpha > best_alpha) {
|
| + VP8Histogram histo = { { 0 } };
|
| + int alpha;
|
| +
|
| + VP8CollectHistogram(it->yuv_in_ + Y_OFF,
|
| + it->yuv_p_ + VP8I16ModeOffsets[mode],
|
| + 0, 16, &histo);
|
| + alpha = GetAlpha(&histo);
|
| + if (IS_BETTER_ALPHA(alpha, best_alpha)) {
|
| best_alpha = alpha;
|
| best_mode = mode;
|
| }
|
| @@ -256,46 +260,63 @@ static int MBAnalyzeBestIntra16Mode(VP8EncIterator* const it) {
|
| static int MBAnalyzeBestIntra4Mode(VP8EncIterator* const it,
|
| int best_alpha) {
|
| uint8_t modes[16];
|
| - const int max_mode = (it->enc_->method_ >= 3) ? MAX_INTRA4_MODE : NUM_BMODES;
|
| - int i4_alpha = 0;
|
| + const int max_mode =
|
| + (it->enc_->method_ >= FAST_ANALYSIS_METHOD) ? MAX_INTRA4_MODE
|
| + : NUM_BMODES;
|
| + int i4_alpha;
|
| + VP8Histogram total_histo = { { 0 } };
|
| + int cur_histo = 0;
|
| +
|
| VP8IteratorStartI4(it);
|
| do {
|
| int mode;
|
| - int best_mode_alpha = -1;
|
| + int best_mode_alpha = DEFAULT_ALPHA;
|
| + VP8Histogram histos[2];
|
| const uint8_t* const src = it->yuv_in_ + Y_OFF + VP8Scan[it->i4_];
|
|
|
| VP8MakeIntra4Preds(it);
|
| for (mode = 0; mode < max_mode; ++mode) {
|
| - const int alpha = VP8CollectHistogram(src,
|
| - it->yuv_p_ + VP8I4ModeOffsets[mode],
|
| - 0, 1);
|
| - if (alpha > best_mode_alpha) {
|
| + int alpha;
|
| +
|
| + memset(&histos[cur_histo], 0, sizeof(histos[cur_histo]));
|
| + VP8CollectHistogram(src, it->yuv_p_ + VP8I4ModeOffsets[mode],
|
| + 0, 1, &histos[cur_histo]);
|
| + alpha = GetAlpha(&histos[cur_histo]);
|
| + if (IS_BETTER_ALPHA(alpha, best_mode_alpha)) {
|
| best_mode_alpha = alpha;
|
| modes[it->i4_] = mode;
|
| + cur_histo ^= 1; // keep track of best histo so far.
|
| }
|
| }
|
| - i4_alpha += best_mode_alpha;
|
| + // accumulate best histogram
|
| + MergeHistograms(&histos[cur_histo ^ 1], &total_histo);
|
| // Note: we reuse the original samples for predictors
|
| } while (VP8IteratorRotateI4(it, it->yuv_in_ + Y_OFF));
|
|
|
| - if (i4_alpha > best_alpha) {
|
| + i4_alpha = GetAlpha(&total_histo);
|
| + if (IS_BETTER_ALPHA(i4_alpha, best_alpha)) {
|
| VP8SetIntra4Mode(it, modes);
|
| - best_alpha = ClipAlpha(i4_alpha);
|
| + best_alpha = i4_alpha;
|
| }
|
| return best_alpha;
|
| }
|
|
|
| static int MBAnalyzeBestUVMode(VP8EncIterator* const it) {
|
| - int best_alpha = -1;
|
| + int best_alpha = DEFAULT_ALPHA;
|
| int best_mode = 0;
|
| - const int max_mode = (it->enc_->method_ >= 3) ? MAX_UV_MODE : 4;
|
| + const int max_mode =
|
| + (it->enc_->method_ >= FAST_ANALYSIS_METHOD) ? MAX_UV_MODE
|
| + : NUM_PRED_MODES;
|
| int mode;
|
| VP8MakeChroma8Preds(it);
|
| for (mode = 0; mode < max_mode; ++mode) {
|
| - const int alpha = VP8CollectHistogram(it->yuv_in_ + U_OFF,
|
| - it->yuv_p_ + VP8UVModeOffsets[mode],
|
| - 16, 16 + 4 + 4);
|
| - if (alpha > best_alpha) {
|
| + VP8Histogram histo = { { 0 } };
|
| + int alpha;
|
| + VP8CollectHistogram(it->yuv_in_ + U_OFF,
|
| + it->yuv_p_ + VP8UVModeOffsets[mode],
|
| + 16, 16 + 4 + 4, &histo);
|
| + alpha = GetAlpha(&histo);
|
| + if (IS_BETTER_ALPHA(alpha, best_alpha)) {
|
| best_alpha = alpha;
|
| best_mode = mode;
|
| }
|
| @@ -305,7 +326,8 @@ static int MBAnalyzeBestUVMode(VP8EncIterator* const it) {
|
| }
|
|
|
| static void MBAnalyze(VP8EncIterator* const it,
|
| - int alphas[256], int* const uv_alpha) {
|
| + int alphas[MAX_ALPHA + 1],
|
| + int* const alpha, int* const uv_alpha) {
|
| const VP8Encoder* const enc = it->enc_;
|
| int best_alpha, best_uv_alpha;
|
|
|
| @@ -314,7 +336,7 @@ static void MBAnalyze(VP8EncIterator* const it,
|
| VP8SetSegment(it, 0); // default segment, spec-wise.
|
|
|
| best_alpha = MBAnalyzeBestIntra16Mode(it);
|
| - if (enc->method_ != 3) {
|
| + if (enc->method_ >= 5) {
|
| // We go and make a fast decision for intra4/intra16.
|
| // It's usually not a good and definitive pick, but helps seeding the stats
|
| // about level bit-cost.
|
| @@ -324,10 +346,22 @@ static void MBAnalyze(VP8EncIterator* const it,
|
| best_uv_alpha = MBAnalyzeBestUVMode(it);
|
|
|
| // Final susceptibility mix
|
| - best_alpha = (best_alpha + best_uv_alpha + 1) / 2;
|
| + best_alpha = (3 * best_alpha + best_uv_alpha + 2) >> 2;
|
| + best_alpha = FinalAlphaValue(best_alpha);
|
| alphas[best_alpha]++;
|
| + it->mb_->alpha_ = best_alpha; // for later remapping.
|
| +
|
| + // Accumulate for later complexity analysis.
|
| + *alpha += best_alpha; // mixed susceptibility (not just luma)
|
| *uv_alpha += best_uv_alpha;
|
| - it->mb_->alpha_ = best_alpha; // Informative only.
|
| +}
|
| +
|
| +static void DefaultMBInfo(VP8MBInfo* const mb) {
|
| + mb->type_ = 1; // I16x16
|
| + mb->uv_mode_ = 0;
|
| + mb->skip_ = 0; // not skipped
|
| + mb->segment_ = 0; // default segment
|
| + mb->alpha_ = 0;
|
| }
|
|
|
| //------------------------------------------------------------------------------
|
| @@ -340,22 +374,43 @@ static void MBAnalyze(VP8EncIterator* const it,
|
| // and decide intra4/intra16, but that's usually almost always a bad choice at
|
| // this stage.
|
|
|
| +static void ResetAllMBInfo(VP8Encoder* const enc) {
|
| + int n;
|
| + for (n = 0; n < enc->mb_w_ * enc->mb_h_; ++n) {
|
| + DefaultMBInfo(&enc->mb_info_[n]);
|
| + }
|
| + // Default susceptibilities.
|
| + enc->dqm_[0].alpha_ = 0;
|
| + enc->dqm_[0].beta_ = 0;
|
| + // Note: we can't compute this alpha_ / uv_alpha_.
|
| + WebPReportProgress(enc->pic_, enc->percent_ + 20, &enc->percent_);
|
| +}
|
| +
|
| int VP8EncAnalyze(VP8Encoder* const enc) {
|
| int ok = 1;
|
| - int alphas[256] = { 0 };
|
| - VP8EncIterator it;
|
| -
|
| - VP8IteratorInit(enc, &it);
|
| + const int do_segments =
|
| + enc->config_->emulate_jpeg_size || // We need the complexity evaluation.
|
| + (enc->segment_hdr_.num_segments_ > 1) ||
|
| + (enc->method_ == 0); // for method 0, we need preds_[] to be filled.
|
| + enc->alpha_ = 0;
|
| enc->uv_alpha_ = 0;
|
| - do {
|
| - VP8IteratorImport(&it);
|
| - MBAnalyze(&it, alphas, &enc->uv_alpha_);
|
| - ok = VP8IteratorProgress(&it, 20);
|
| - // Let's pretend we have perfect lossless reconstruction.
|
| - } while (ok && VP8IteratorNext(&it, it.yuv_in_));
|
| - enc->uv_alpha_ /= enc->mb_w_ * enc->mb_h_;
|
| - if (ok) AssignSegments(enc, alphas);
|
| -
|
| + if (do_segments) {
|
| + int alphas[MAX_ALPHA + 1] = { 0 };
|
| + VP8EncIterator it;
|
| +
|
| + VP8IteratorInit(enc, &it);
|
| + do {
|
| + VP8IteratorImport(&it);
|
| + MBAnalyze(&it, alphas, &enc->alpha_, &enc->uv_alpha_);
|
| + ok = VP8IteratorProgress(&it, 20);
|
| + // Let's pretend we have perfect lossless reconstruction.
|
| + } while (ok && VP8IteratorNext(&it, it.yuv_in_));
|
| + enc->alpha_ /= enc->mb_w_ * enc->mb_h_;
|
| + enc->uv_alpha_ /= enc->mb_w_ * enc->mb_h_;
|
| + if (ok) AssignSegments(enc, alphas);
|
| + } else { // Use only one default segment.
|
| + ResetAllMBInfo(enc);
|
| + }
|
| return ok;
|
| }
|
|
|
|
|