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Diffstat (limited to 'media/libwebp/src/enc/histogram_enc.c')
| -rw-r--r-- | media/libwebp/src/enc/histogram_enc.c | 1248 |
1 files changed, 1248 insertions, 0 deletions
diff --git a/media/libwebp/src/enc/histogram_enc.c b/media/libwebp/src/enc/histogram_enc.c new file mode 100644 index 0000000000..8418def2e1 --- /dev/null +++ b/media/libwebp/src/enc/histogram_enc.c @@ -0,0 +1,1248 @@ +// Copyright 2012 Google Inc. All Rights Reserved. +// +// Use of this source code is governed by a BSD-style license +// that can be found in the COPYING 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. +// ----------------------------------------------------------------------------- +// +// Author: Jyrki Alakuijala (jyrki@google.com) +// +#ifdef HAVE_CONFIG_H +#include "src/webp/config.h" +#endif + +#include <float.h> +#include <math.h> + +#include "src/dsp/lossless.h" +#include "src/dsp/lossless_common.h" +#include "src/enc/backward_references_enc.h" +#include "src/enc/histogram_enc.h" +#include "src/enc/vp8i_enc.h" +#include "src/utils/utils.h" + +#define MAX_BIT_COST FLT_MAX + +// Number of partitions for the three dominant (literal, red and blue) symbol +// costs. +#define NUM_PARTITIONS 4 +// The size of the bin-hash corresponding to the three dominant costs. +#define BIN_SIZE (NUM_PARTITIONS * NUM_PARTITIONS * NUM_PARTITIONS) +// Maximum number of histograms allowed in greedy combining algorithm. +#define MAX_HISTO_GREEDY 100 + +static void HistogramClear(VP8LHistogram* const p) { + uint32_t* const literal = p->literal_; + const int cache_bits = p->palette_code_bits_; + const int histo_size = VP8LGetHistogramSize(cache_bits); + memset(p, 0, histo_size); + p->palette_code_bits_ = cache_bits; + p->literal_ = literal; +} + +// Swap two histogram pointers. +static void HistogramSwap(VP8LHistogram** const A, VP8LHistogram** const B) { + VP8LHistogram* const tmp = *A; + *A = *B; + *B = tmp; +} + +static void HistogramCopy(const VP8LHistogram* const src, + VP8LHistogram* const dst) { + uint32_t* const dst_literal = dst->literal_; + const int dst_cache_bits = dst->palette_code_bits_; + const int literal_size = VP8LHistogramNumCodes(dst_cache_bits); + const int histo_size = VP8LGetHistogramSize(dst_cache_bits); + assert(src->palette_code_bits_ == dst_cache_bits); + memcpy(dst, src, histo_size); + dst->literal_ = dst_literal; + memcpy(dst->literal_, src->literal_, literal_size * sizeof(*dst->literal_)); +} + +int VP8LGetHistogramSize(int cache_bits) { + const int literal_size = VP8LHistogramNumCodes(cache_bits); + const size_t total_size = sizeof(VP8LHistogram) + sizeof(int) * literal_size; + assert(total_size <= (size_t)0x7fffffff); + return (int)total_size; +} + +void VP8LFreeHistogram(VP8LHistogram* const histo) { + WebPSafeFree(histo); +} + +void VP8LFreeHistogramSet(VP8LHistogramSet* const histo) { + WebPSafeFree(histo); +} + +void VP8LHistogramStoreRefs(const VP8LBackwardRefs* const refs, + VP8LHistogram* const histo) { + VP8LRefsCursor c = VP8LRefsCursorInit(refs); + while (VP8LRefsCursorOk(&c)) { + VP8LHistogramAddSinglePixOrCopy(histo, c.cur_pos, NULL, 0); + VP8LRefsCursorNext(&c); + } +} + +void VP8LHistogramCreate(VP8LHistogram* const p, + const VP8LBackwardRefs* const refs, + int palette_code_bits) { + if (palette_code_bits >= 0) { + p->palette_code_bits_ = palette_code_bits; + } + HistogramClear(p); + VP8LHistogramStoreRefs(refs, p); +} + +void VP8LHistogramInit(VP8LHistogram* const p, int palette_code_bits, + int init_arrays) { + p->palette_code_bits_ = palette_code_bits; + if (init_arrays) { + HistogramClear(p); + } else { + p->trivial_symbol_ = 0; + p->bit_cost_ = 0.; + p->literal_cost_ = 0.; + p->red_cost_ = 0.; + p->blue_cost_ = 0.; + memset(p->is_used_, 0, sizeof(p->is_used_)); + } +} + +VP8LHistogram* VP8LAllocateHistogram(int cache_bits) { + VP8LHistogram* histo = NULL; + const int total_size = VP8LGetHistogramSize(cache_bits); + uint8_t* const memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory)); + if (memory == NULL) return NULL; + histo = (VP8LHistogram*)memory; + // literal_ won't necessary be aligned. + histo->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram)); + VP8LHistogramInit(histo, cache_bits, /*init_arrays=*/ 0); + return histo; +} + +// Resets the pointers of the histograms to point to the bit buffer in the set. +static void HistogramSetResetPointers(VP8LHistogramSet* const set, + int cache_bits) { + int i; + const int histo_size = VP8LGetHistogramSize(cache_bits); + uint8_t* memory = (uint8_t*) (set->histograms); + memory += set->max_size * sizeof(*set->histograms); + for (i = 0; i < set->max_size; ++i) { + memory = (uint8_t*) WEBP_ALIGN(memory); + set->histograms[i] = (VP8LHistogram*) memory; + // literal_ won't necessary be aligned. + set->histograms[i]->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram)); + memory += histo_size; + } +} + +// Returns the total size of the VP8LHistogramSet. +static size_t HistogramSetTotalSize(int size, int cache_bits) { + const int histo_size = VP8LGetHistogramSize(cache_bits); + return (sizeof(VP8LHistogramSet) + size * (sizeof(VP8LHistogram*) + + histo_size + WEBP_ALIGN_CST)); +} + +VP8LHistogramSet* VP8LAllocateHistogramSet(int size, int cache_bits) { + int i; + VP8LHistogramSet* set; + const size_t total_size = HistogramSetTotalSize(size, cache_bits); + uint8_t* memory = (uint8_t*)WebPSafeMalloc(total_size, sizeof(*memory)); + if (memory == NULL) return NULL; + + set = (VP8LHistogramSet*)memory; + memory += sizeof(*set); + set->histograms = (VP8LHistogram**)memory; + set->max_size = size; + set->size = size; + HistogramSetResetPointers(set, cache_bits); + for (i = 0; i < size; ++i) { + VP8LHistogramInit(set->histograms[i], cache_bits, /*init_arrays=*/ 0); + } + return set; +} + +void VP8LHistogramSetClear(VP8LHistogramSet* const set) { + int i; + const int cache_bits = set->histograms[0]->palette_code_bits_; + const int size = set->max_size; + const size_t total_size = HistogramSetTotalSize(size, cache_bits); + uint8_t* memory = (uint8_t*)set; + + memset(memory, 0, total_size); + memory += sizeof(*set); + set->histograms = (VP8LHistogram**)memory; + set->max_size = size; + set->size = size; + HistogramSetResetPointers(set, cache_bits); + for (i = 0; i < size; ++i) { + set->histograms[i]->palette_code_bits_ = cache_bits; + } +} + +// Removes the histogram 'i' from 'set' by setting it to NULL. +static void HistogramSetRemoveHistogram(VP8LHistogramSet* const set, int i, + int* const num_used) { + assert(set->histograms[i] != NULL); + set->histograms[i] = NULL; + --*num_used; + // If we remove the last valid one, shrink until the next valid one. + if (i == set->size - 1) { + while (set->size >= 1 && set->histograms[set->size - 1] == NULL) { + --set->size; + } + } +} + +// ----------------------------------------------------------------------------- + +void VP8LHistogramAddSinglePixOrCopy(VP8LHistogram* const histo, + const PixOrCopy* const v, + int (*const distance_modifier)(int, int), + int distance_modifier_arg0) { + if (PixOrCopyIsLiteral(v)) { + ++histo->alpha_[PixOrCopyLiteral(v, 3)]; + ++histo->red_[PixOrCopyLiteral(v, 2)]; + ++histo->literal_[PixOrCopyLiteral(v, 1)]; + ++histo->blue_[PixOrCopyLiteral(v, 0)]; + } else if (PixOrCopyIsCacheIdx(v)) { + const int literal_ix = + NUM_LITERAL_CODES + NUM_LENGTH_CODES + PixOrCopyCacheIdx(v); + assert(histo->palette_code_bits_ != 0); + ++histo->literal_[literal_ix]; + } else { + int code, extra_bits; + VP8LPrefixEncodeBits(PixOrCopyLength(v), &code, &extra_bits); + ++histo->literal_[NUM_LITERAL_CODES + code]; + if (distance_modifier == NULL) { + VP8LPrefixEncodeBits(PixOrCopyDistance(v), &code, &extra_bits); + } else { + VP8LPrefixEncodeBits( + distance_modifier(distance_modifier_arg0, PixOrCopyDistance(v)), + &code, &extra_bits); + } + ++histo->distance_[code]; + } +} + +// ----------------------------------------------------------------------------- +// Entropy-related functions. + +static WEBP_INLINE float BitsEntropyRefine(const VP8LBitEntropy* entropy) { + float mix; + if (entropy->nonzeros < 5) { + if (entropy->nonzeros <= 1) { + return 0; + } + // Two symbols, they will be 0 and 1 in a Huffman code. + // Let's mix in a bit of entropy to favor good clustering when + // distributions of these are combined. + if (entropy->nonzeros == 2) { + return 0.99f * entropy->sum + 0.01f * entropy->entropy; + } + // No matter what the entropy says, we cannot be better than min_limit + // with Huffman coding. I am mixing a bit of entropy into the + // min_limit since it produces much better (~0.5 %) compression results + // perhaps because of better entropy clustering. + if (entropy->nonzeros == 3) { + mix = 0.95f; + } else { + mix = 0.7f; // nonzeros == 4. + } + } else { + mix = 0.627f; + } + + { + float min_limit = 2.f * entropy->sum - entropy->max_val; + min_limit = mix * min_limit + (1.f - mix) * entropy->entropy; + return (entropy->entropy < min_limit) ? min_limit : entropy->entropy; + } +} + +float VP8LBitsEntropy(const uint32_t* const array, int n) { + VP8LBitEntropy entropy; + VP8LBitsEntropyUnrefined(array, n, &entropy); + + return BitsEntropyRefine(&entropy); +} + +static float InitialHuffmanCost(void) { + // Small bias because Huffman code length is typically not stored in + // full length. + static const int kHuffmanCodeOfHuffmanCodeSize = CODE_LENGTH_CODES * 3; + static const float kSmallBias = 9.1f; + return kHuffmanCodeOfHuffmanCodeSize - kSmallBias; +} + +// Finalize the Huffman cost based on streak numbers and length type (<3 or >=3) +static float FinalHuffmanCost(const VP8LStreaks* const stats) { + // The constants in this function are experimental and got rounded from + // their original values in 1/8 when switched to 1/1024. + float retval = InitialHuffmanCost(); + // Second coefficient: Many zeros in the histogram are covered efficiently + // by a run-length encode. Originally 2/8. + retval += stats->counts[0] * 1.5625f + 0.234375f * stats->streaks[0][1]; + // Second coefficient: Constant values are encoded less efficiently, but still + // RLE'ed. Originally 6/8. + retval += stats->counts[1] * 2.578125f + 0.703125f * stats->streaks[1][1]; + // 0s are usually encoded more efficiently than non-0s. + // Originally 15/8. + retval += 1.796875f * stats->streaks[0][0]; + // Originally 26/8. + retval += 3.28125f * stats->streaks[1][0]; + return retval; +} + +// Get the symbol entropy for the distribution 'population'. +// Set 'trivial_sym', if there's only one symbol present in the distribution. +static float PopulationCost(const uint32_t* const population, int length, + uint32_t* const trivial_sym, + uint8_t* const is_used) { + VP8LBitEntropy bit_entropy; + VP8LStreaks stats; + VP8LGetEntropyUnrefined(population, length, &bit_entropy, &stats); + if (trivial_sym != NULL) { + *trivial_sym = (bit_entropy.nonzeros == 1) ? bit_entropy.nonzero_code + : VP8L_NON_TRIVIAL_SYM; + } + // The histogram is used if there is at least one non-zero streak. + *is_used = (stats.streaks[1][0] != 0 || stats.streaks[1][1] != 0); + + return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats); +} + +// trivial_at_end is 1 if the two histograms only have one element that is +// non-zero: both the zero-th one, or both the last one. +static WEBP_INLINE float GetCombinedEntropy(const uint32_t* const X, + const uint32_t* const Y, int length, + int is_X_used, int is_Y_used, + int trivial_at_end) { + VP8LStreaks stats; + if (trivial_at_end) { + // This configuration is due to palettization that transforms an indexed + // pixel into 0xff000000 | (pixel << 8) in VP8LBundleColorMap. + // BitsEntropyRefine is 0 for histograms with only one non-zero value. + // Only FinalHuffmanCost needs to be evaluated. + memset(&stats, 0, sizeof(stats)); + // Deal with the non-zero value at index 0 or length-1. + stats.streaks[1][0] = 1; + // Deal with the following/previous zero streak. + stats.counts[0] = 1; + stats.streaks[0][1] = length - 1; + return FinalHuffmanCost(&stats); + } else { + VP8LBitEntropy bit_entropy; + if (is_X_used) { + if (is_Y_used) { + VP8LGetCombinedEntropyUnrefined(X, Y, length, &bit_entropy, &stats); + } else { + VP8LGetEntropyUnrefined(X, length, &bit_entropy, &stats); + } + } else { + if (is_Y_used) { + VP8LGetEntropyUnrefined(Y, length, &bit_entropy, &stats); + } else { + memset(&stats, 0, sizeof(stats)); + stats.counts[0] = 1; + stats.streaks[0][length > 3] = length; + VP8LBitEntropyInit(&bit_entropy); + } + } + + return BitsEntropyRefine(&bit_entropy) + FinalHuffmanCost(&stats); + } +} + +// Estimates the Entropy + Huffman + other block overhead size cost. +float VP8LHistogramEstimateBits(VP8LHistogram* const p) { + return + PopulationCost(p->literal_, VP8LHistogramNumCodes(p->palette_code_bits_), + NULL, &p->is_used_[0]) + + PopulationCost(p->red_, NUM_LITERAL_CODES, NULL, &p->is_used_[1]) + + PopulationCost(p->blue_, NUM_LITERAL_CODES, NULL, &p->is_used_[2]) + + PopulationCost(p->alpha_, NUM_LITERAL_CODES, NULL, &p->is_used_[3]) + + PopulationCost(p->distance_, NUM_DISTANCE_CODES, NULL, &p->is_used_[4]) + + VP8LExtraCost(p->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES) + + VP8LExtraCost(p->distance_, NUM_DISTANCE_CODES); +} + +// ----------------------------------------------------------------------------- +// Various histogram combine/cost-eval functions + +static int GetCombinedHistogramEntropy(const VP8LHistogram* const a, + const VP8LHistogram* const b, + float cost_threshold, float* cost) { + const int palette_code_bits = a->palette_code_bits_; + int trivial_at_end = 0; + assert(a->palette_code_bits_ == b->palette_code_bits_); + *cost += GetCombinedEntropy(a->literal_, b->literal_, + VP8LHistogramNumCodes(palette_code_bits), + a->is_used_[0], b->is_used_[0], 0); + *cost += VP8LExtraCostCombined(a->literal_ + NUM_LITERAL_CODES, + b->literal_ + NUM_LITERAL_CODES, + NUM_LENGTH_CODES); + if (*cost > cost_threshold) return 0; + + if (a->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM && + a->trivial_symbol_ == b->trivial_symbol_) { + // A, R and B are all 0 or 0xff. + const uint32_t color_a = (a->trivial_symbol_ >> 24) & 0xff; + const uint32_t color_r = (a->trivial_symbol_ >> 16) & 0xff; + const uint32_t color_b = (a->trivial_symbol_ >> 0) & 0xff; + if ((color_a == 0 || color_a == 0xff) && + (color_r == 0 || color_r == 0xff) && + (color_b == 0 || color_b == 0xff)) { + trivial_at_end = 1; + } + } + + *cost += + GetCombinedEntropy(a->red_, b->red_, NUM_LITERAL_CODES, a->is_used_[1], + b->is_used_[1], trivial_at_end); + if (*cost > cost_threshold) return 0; + + *cost += + GetCombinedEntropy(a->blue_, b->blue_, NUM_LITERAL_CODES, a->is_used_[2], + b->is_used_[2], trivial_at_end); + if (*cost > cost_threshold) return 0; + + *cost += + GetCombinedEntropy(a->alpha_, b->alpha_, NUM_LITERAL_CODES, + a->is_used_[3], b->is_used_[3], trivial_at_end); + if (*cost > cost_threshold) return 0; + + *cost += + GetCombinedEntropy(a->distance_, b->distance_, NUM_DISTANCE_CODES, + a->is_used_[4], b->is_used_[4], 0); + *cost += + VP8LExtraCostCombined(a->distance_, b->distance_, NUM_DISTANCE_CODES); + if (*cost > cost_threshold) return 0; + + return 1; +} + +static WEBP_INLINE void HistogramAdd(const VP8LHistogram* const a, + const VP8LHistogram* const b, + VP8LHistogram* const out) { + VP8LHistogramAdd(a, b, out); + out->trivial_symbol_ = (a->trivial_symbol_ == b->trivial_symbol_) + ? a->trivial_symbol_ + : VP8L_NON_TRIVIAL_SYM; +} + +// Performs out = a + b, computing the cost C(a+b) - C(a) - C(b) while comparing +// to the threshold value 'cost_threshold'. The score returned is +// Score = C(a+b) - C(a) - C(b), where C(a) + C(b) is known and fixed. +// Since the previous score passed is 'cost_threshold', we only need to compare +// the partial cost against 'cost_threshold + C(a) + C(b)' to possibly bail-out +// early. +static float HistogramAddEval(const VP8LHistogram* const a, + const VP8LHistogram* const b, + VP8LHistogram* const out, float cost_threshold) { + float cost = 0; + const float sum_cost = a->bit_cost_ + b->bit_cost_; + cost_threshold += sum_cost; + + if (GetCombinedHistogramEntropy(a, b, cost_threshold, &cost)) { + HistogramAdd(a, b, out); + out->bit_cost_ = cost; + out->palette_code_bits_ = a->palette_code_bits_; + } + + return cost - sum_cost; +} + +// Same as HistogramAddEval(), except that the resulting histogram +// is not stored. Only the cost C(a+b) - C(a) is evaluated. We omit +// the term C(b) which is constant over all the evaluations. +static float HistogramAddThresh(const VP8LHistogram* const a, + const VP8LHistogram* const b, + float cost_threshold) { + float cost; + assert(a != NULL && b != NULL); + cost = -a->bit_cost_; + GetCombinedHistogramEntropy(a, b, cost_threshold, &cost); + return cost; +} + +// ----------------------------------------------------------------------------- + +// The structure to keep track of cost range for the three dominant entropy +// symbols. +typedef struct { + float literal_max_; + float literal_min_; + float red_max_; + float red_min_; + float blue_max_; + float blue_min_; +} DominantCostRange; + +static void DominantCostRangeInit(DominantCostRange* const c) { + c->literal_max_ = 0.; + c->literal_min_ = MAX_BIT_COST; + c->red_max_ = 0.; + c->red_min_ = MAX_BIT_COST; + c->blue_max_ = 0.; + c->blue_min_ = MAX_BIT_COST; +} + +static void UpdateDominantCostRange( + const VP8LHistogram* const h, DominantCostRange* const c) { + if (c->literal_max_ < h->literal_cost_) c->literal_max_ = h->literal_cost_; + if (c->literal_min_ > h->literal_cost_) c->literal_min_ = h->literal_cost_; + if (c->red_max_ < h->red_cost_) c->red_max_ = h->red_cost_; + if (c->red_min_ > h->red_cost_) c->red_min_ = h->red_cost_; + if (c->blue_max_ < h->blue_cost_) c->blue_max_ = h->blue_cost_; + if (c->blue_min_ > h->blue_cost_) c->blue_min_ = h->blue_cost_; +} + +static void UpdateHistogramCost(VP8LHistogram* const h) { + uint32_t alpha_sym, red_sym, blue_sym; + const float alpha_cost = + PopulationCost(h->alpha_, NUM_LITERAL_CODES, &alpha_sym, &h->is_used_[3]); + const float distance_cost = + PopulationCost(h->distance_, NUM_DISTANCE_CODES, NULL, &h->is_used_[4]) + + VP8LExtraCost(h->distance_, NUM_DISTANCE_CODES); + const int num_codes = VP8LHistogramNumCodes(h->palette_code_bits_); + h->literal_cost_ = + PopulationCost(h->literal_, num_codes, NULL, &h->is_used_[0]) + + VP8LExtraCost(h->literal_ + NUM_LITERAL_CODES, NUM_LENGTH_CODES); + h->red_cost_ = + PopulationCost(h->red_, NUM_LITERAL_CODES, &red_sym, &h->is_used_[1]); + h->blue_cost_ = + PopulationCost(h->blue_, NUM_LITERAL_CODES, &blue_sym, &h->is_used_[2]); + h->bit_cost_ = h->literal_cost_ + h->red_cost_ + h->blue_cost_ + + alpha_cost + distance_cost; + if ((alpha_sym | red_sym | blue_sym) == VP8L_NON_TRIVIAL_SYM) { + h->trivial_symbol_ = VP8L_NON_TRIVIAL_SYM; + } else { + h->trivial_symbol_ = + ((uint32_t)alpha_sym << 24) | (red_sym << 16) | (blue_sym << 0); + } +} + +static int GetBinIdForEntropy(float min, float max, float val) { + const float range = max - min; + if (range > 0.) { + const float delta = val - min; + return (int)((NUM_PARTITIONS - 1e-6) * delta / range); + } else { + return 0; + } +} + +static int GetHistoBinIndex(const VP8LHistogram* const h, + const DominantCostRange* const c, int low_effort) { + int bin_id = GetBinIdForEntropy(c->literal_min_, c->literal_max_, + h->literal_cost_); + assert(bin_id < NUM_PARTITIONS); + if (!low_effort) { + bin_id = bin_id * NUM_PARTITIONS + + GetBinIdForEntropy(c->red_min_, c->red_max_, h->red_cost_); + bin_id = bin_id * NUM_PARTITIONS + + GetBinIdForEntropy(c->blue_min_, c->blue_max_, h->blue_cost_); + assert(bin_id < BIN_SIZE); + } + return bin_id; +} + +// Construct the histograms from backward references. +static void HistogramBuild( + int xsize, int histo_bits, const VP8LBackwardRefs* const backward_refs, + VP8LHistogramSet* const image_histo) { + int x = 0, y = 0; + const int histo_xsize = VP8LSubSampleSize(xsize, histo_bits); + VP8LHistogram** const histograms = image_histo->histograms; + VP8LRefsCursor c = VP8LRefsCursorInit(backward_refs); + assert(histo_bits > 0); + VP8LHistogramSetClear(image_histo); + while (VP8LRefsCursorOk(&c)) { + const PixOrCopy* const v = c.cur_pos; + const int ix = (y >> histo_bits) * histo_xsize + (x >> histo_bits); + VP8LHistogramAddSinglePixOrCopy(histograms[ix], v, NULL, 0); + x += PixOrCopyLength(v); + while (x >= xsize) { + x -= xsize; + ++y; + } + VP8LRefsCursorNext(&c); + } +} + +// Copies the histograms and computes its bit_cost. +static const uint16_t kInvalidHistogramSymbol = (uint16_t)(-1); +static void HistogramCopyAndAnalyze(VP8LHistogramSet* const orig_histo, + VP8LHistogramSet* const image_histo, + int* const num_used, + uint16_t* const histogram_symbols) { + int i, cluster_id; + int num_used_orig = *num_used; + VP8LHistogram** const orig_histograms = orig_histo->histograms; + VP8LHistogram** const histograms = image_histo->histograms; + assert(image_histo->max_size == orig_histo->max_size); + for (cluster_id = 0, i = 0; i < orig_histo->max_size; ++i) { + VP8LHistogram* const histo = orig_histograms[i]; + UpdateHistogramCost(histo); + + // Skip the histogram if it is completely empty, which can happen for tiles + // with no information (when they are skipped because of LZ77). + if (!histo->is_used_[0] && !histo->is_used_[1] && !histo->is_used_[2] + && !histo->is_used_[3] && !histo->is_used_[4]) { + // The first histogram is always used. If an histogram is empty, we set + // its id to be the same as the previous one: this will improve + // compressibility for later LZ77. + assert(i > 0); + HistogramSetRemoveHistogram(image_histo, i, num_used); + HistogramSetRemoveHistogram(orig_histo, i, &num_used_orig); + histogram_symbols[i] = kInvalidHistogramSymbol; + } else { + // Copy histograms from orig_histo[] to image_histo[]. + HistogramCopy(histo, histograms[i]); + histogram_symbols[i] = cluster_id++; + assert(cluster_id <= image_histo->max_size); + } + } +} + +// Partition histograms to different entropy bins for three dominant (literal, +// red and blue) symbol costs and compute the histogram aggregate bit_cost. +static void HistogramAnalyzeEntropyBin(VP8LHistogramSet* const image_histo, + uint16_t* const bin_map, + int low_effort) { + int i; + VP8LHistogram** const histograms = image_histo->histograms; + const int histo_size = image_histo->size; + DominantCostRange cost_range; + DominantCostRangeInit(&cost_range); + + // Analyze the dominant (literal, red and blue) entropy costs. + for (i = 0; i < histo_size; ++i) { + if (histograms[i] == NULL) continue; + UpdateDominantCostRange(histograms[i], &cost_range); + } + + // bin-hash histograms on three of the dominant (literal, red and blue) + // symbol costs and store the resulting bin_id for each histogram. + for (i = 0; i < histo_size; ++i) { + // bin_map[i] is not set to a special value as its use will later be guarded + // by another (histograms[i] == NULL). + if (histograms[i] == NULL) continue; + bin_map[i] = GetHistoBinIndex(histograms[i], &cost_range, low_effort); + } +} + +// Merges some histograms with same bin_id together if it's advantageous. +// Sets the remaining histograms to NULL. +static void HistogramCombineEntropyBin( + VP8LHistogramSet* const image_histo, int* num_used, + const uint16_t* const clusters, uint16_t* const cluster_mappings, + VP8LHistogram* cur_combo, const uint16_t* const bin_map, int num_bins, + float combine_cost_factor, int low_effort) { + VP8LHistogram** const histograms = image_histo->histograms; + int idx; + struct { + int16_t first; // position of the histogram that accumulates all + // histograms with the same bin_id + uint16_t num_combine_failures; // number of combine failures per bin_id + } bin_info[BIN_SIZE]; + + assert(num_bins <= BIN_SIZE); + for (idx = 0; idx < num_bins; ++idx) { + bin_info[idx].first = -1; + bin_info[idx].num_combine_failures = 0; + } + + // By default, a cluster matches itself. + for (idx = 0; idx < *num_used; ++idx) cluster_mappings[idx] = idx; + for (idx = 0; idx < image_histo->size; ++idx) { + int bin_id, first; + if (histograms[idx] == NULL) continue; + bin_id = bin_map[idx]; + first = bin_info[bin_id].first; + if (first == -1) { + bin_info[bin_id].first = idx; + } else if (low_effort) { + HistogramAdd(histograms[idx], histograms[first], histograms[first]); + HistogramSetRemoveHistogram(image_histo, idx, num_used); + cluster_mappings[clusters[idx]] = clusters[first]; + } else { + // try to merge #idx into #first (both share the same bin_id) + const float bit_cost = histograms[idx]->bit_cost_; + const float bit_cost_thresh = -bit_cost * combine_cost_factor; + const float curr_cost_diff = HistogramAddEval( + histograms[first], histograms[idx], cur_combo, bit_cost_thresh); + if (curr_cost_diff < bit_cost_thresh) { + // Try to merge two histograms only if the combo is a trivial one or + // the two candidate histograms are already non-trivial. + // For some images, 'try_combine' turns out to be false for a lot of + // histogram pairs. In that case, we fallback to combining + // histograms as usual to avoid increasing the header size. + const int try_combine = + (cur_combo->trivial_symbol_ != VP8L_NON_TRIVIAL_SYM) || + ((histograms[idx]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM) && + (histograms[first]->trivial_symbol_ == VP8L_NON_TRIVIAL_SYM)); + const int max_combine_failures = 32; + if (try_combine || + bin_info[bin_id].num_combine_failures >= max_combine_failures) { + // move the (better) merged histogram to its final slot + HistogramSwap(&cur_combo, &histograms[first]); + HistogramSetRemoveHistogram(image_histo, idx, num_used); + cluster_mappings[clusters[idx]] = clusters[first]; + } else { + ++bin_info[bin_id].num_combine_failures; + } + } + } + } + if (low_effort) { + // for low_effort case, update the final cost when everything is merged + for (idx = 0; idx < image_histo->size; ++idx) { + if (histograms[idx] == NULL) continue; + UpdateHistogramCost(histograms[idx]); + } + } +} + +// Implement a Lehmer random number generator with a multiplicative constant of +// 48271 and a modulo constant of 2^31 - 1. +static uint32_t MyRand(uint32_t* const seed) { + *seed = (uint32_t)(((uint64_t)(*seed) * 48271u) % 2147483647u); + assert(*seed > 0); + return *seed; +} + +// ----------------------------------------------------------------------------- +// Histogram pairs priority queue + +// Pair of histograms. Negative idx1 value means that pair is out-of-date. +typedef struct { + int idx1; + int idx2; + float cost_diff; + float cost_combo; +} HistogramPair; + +typedef struct { + HistogramPair* queue; + int size; + int max_size; +} HistoQueue; + +static int HistoQueueInit(HistoQueue* const histo_queue, const int max_size) { + histo_queue->size = 0; + histo_queue->max_size = max_size; + // We allocate max_size + 1 because the last element at index "size" is + // used as temporary data (and it could be up to max_size). + histo_queue->queue = (HistogramPair*)WebPSafeMalloc( + histo_queue->max_size + 1, sizeof(*histo_queue->queue)); + return histo_queue->queue != NULL; +} + +static void HistoQueueClear(HistoQueue* const histo_queue) { + assert(histo_queue != NULL); + WebPSafeFree(histo_queue->queue); + histo_queue->size = 0; + histo_queue->max_size = 0; +} + +// Pop a specific pair in the queue by replacing it with the last one +// and shrinking the queue. +static void HistoQueuePopPair(HistoQueue* const histo_queue, + HistogramPair* const pair) { + assert(pair >= histo_queue->queue && + pair < (histo_queue->queue + histo_queue->size)); + assert(histo_queue->size > 0); + *pair = histo_queue->queue[histo_queue->size - 1]; + --histo_queue->size; +} + +// Check whether a pair in the queue should be updated as head or not. +static void HistoQueueUpdateHead(HistoQueue* const histo_queue, + HistogramPair* const pair) { + assert(pair->cost_diff < 0.); + assert(pair >= histo_queue->queue && + pair < (histo_queue->queue + histo_queue->size)); + assert(histo_queue->size > 0); + if (pair->cost_diff < histo_queue->queue[0].cost_diff) { + // Replace the best pair. + const HistogramPair tmp = histo_queue->queue[0]; + histo_queue->queue[0] = *pair; + *pair = tmp; + } +} + +// Update the cost diff and combo of a pair of histograms. This needs to be +// called when the the histograms have been merged with a third one. +static void HistoQueueUpdatePair(const VP8LHistogram* const h1, + const VP8LHistogram* const h2, float threshold, + HistogramPair* const pair) { + const float sum_cost = h1->bit_cost_ + h2->bit_cost_; + pair->cost_combo = 0.; + GetCombinedHistogramEntropy(h1, h2, sum_cost + threshold, &pair->cost_combo); + pair->cost_diff = pair->cost_combo - sum_cost; +} + +// Create a pair from indices "idx1" and "idx2" provided its cost +// is inferior to "threshold", a negative entropy. +// It returns the cost of the pair, or 0. if it superior to threshold. +static float HistoQueuePush(HistoQueue* const histo_queue, + VP8LHistogram** const histograms, int idx1, + int idx2, float threshold) { + const VP8LHistogram* h1; + const VP8LHistogram* h2; + HistogramPair pair; + + // Stop here if the queue is full. + if (histo_queue->size == histo_queue->max_size) return 0.; + assert(threshold <= 0.); + if (idx1 > idx2) { + const int tmp = idx2; + idx2 = idx1; + idx1 = tmp; + } + pair.idx1 = idx1; + pair.idx2 = idx2; + h1 = histograms[idx1]; + h2 = histograms[idx2]; + + HistoQueueUpdatePair(h1, h2, threshold, &pair); + + // Do not even consider the pair if it does not improve the entropy. + if (pair.cost_diff >= threshold) return 0.; + + histo_queue->queue[histo_queue->size++] = pair; + HistoQueueUpdateHead(histo_queue, &histo_queue->queue[histo_queue->size - 1]); + + return pair.cost_diff; +} + +// ----------------------------------------------------------------------------- + +// Combines histograms by continuously choosing the one with the highest cost +// reduction. +static int HistogramCombineGreedy(VP8LHistogramSet* const image_histo, + int* const num_used) { + int ok = 0; + const int image_histo_size = image_histo->size; + int i, j; + VP8LHistogram** const histograms = image_histo->histograms; + // Priority queue of histogram pairs. + HistoQueue histo_queue; + + // image_histo_size^2 for the queue size is safe. If you look at + // HistogramCombineGreedy, and imagine that UpdateQueueFront always pushes + // data to the queue, you insert at most: + // - image_histo_size*(image_histo_size-1)/2 (the first two for loops) + // - image_histo_size - 1 in the last for loop at the first iteration of + // the while loop, image_histo_size - 2 at the second iteration ... + // therefore image_histo_size*(image_histo_size-1)/2 overall too + if (!HistoQueueInit(&histo_queue, image_histo_size * image_histo_size)) { + goto End; + } + + for (i = 0; i < image_histo_size; ++i) { + if (image_histo->histograms[i] == NULL) continue; + for (j = i + 1; j < image_histo_size; ++j) { + // Initialize queue. + if (image_histo->histograms[j] == NULL) continue; + HistoQueuePush(&histo_queue, histograms, i, j, 0.); + } + } + + while (histo_queue.size > 0) { + const int idx1 = histo_queue.queue[0].idx1; + const int idx2 = histo_queue.queue[0].idx2; + HistogramAdd(histograms[idx2], histograms[idx1], histograms[idx1]); + histograms[idx1]->bit_cost_ = histo_queue.queue[0].cost_combo; + + // Remove merged histogram. + HistogramSetRemoveHistogram(image_histo, idx2, num_used); + + // Remove pairs intersecting the just combined best pair. + for (i = 0; i < histo_queue.size;) { + HistogramPair* const p = histo_queue.queue + i; + if (p->idx1 == idx1 || p->idx2 == idx1 || + p->idx1 == idx2 || p->idx2 == idx2) { + HistoQueuePopPair(&histo_queue, p); + } else { + HistoQueueUpdateHead(&histo_queue, p); + ++i; + } + } + + // Push new pairs formed with combined histogram to the queue. + for (i = 0; i < image_histo->size; ++i) { + if (i == idx1 || image_histo->histograms[i] == NULL) continue; + HistoQueuePush(&histo_queue, image_histo->histograms, idx1, i, 0.); + } + } + + ok = 1; + + End: + HistoQueueClear(&histo_queue); + return ok; +} + +// Perform histogram aggregation using a stochastic approach. +// 'do_greedy' is set to 1 if a greedy approach needs to be performed +// afterwards, 0 otherwise. +static int PairComparison(const void* idx1, const void* idx2) { + // To be used with bsearch: <0 when *idx1<*idx2, >0 if >, 0 when ==. + return (*(int*) idx1 - *(int*) idx2); +} +static int HistogramCombineStochastic(VP8LHistogramSet* const image_histo, + int* const num_used, int min_cluster_size, + int* const do_greedy) { + int j, iter; + uint32_t seed = 1; + int tries_with_no_success = 0; + const int outer_iters = *num_used; + const int num_tries_no_success = outer_iters / 2; + VP8LHistogram** const histograms = image_histo->histograms; + // Priority queue of histogram pairs. Its size of 'kHistoQueueSize' + // impacts the quality of the compression and the speed: the smaller the + // faster but the worse for the compression. + HistoQueue histo_queue; + const int kHistoQueueSize = 9; + int ok = 0; + // mapping from an index in image_histo with no NULL histogram to the full + // blown image_histo. + int* mappings; + + if (*num_used < min_cluster_size) { + *do_greedy = 1; + return 1; + } + + mappings = (int*) WebPSafeMalloc(*num_used, sizeof(*mappings)); + if (mappings == NULL) return 0; + if (!HistoQueueInit(&histo_queue, kHistoQueueSize)) goto End; + // Fill the initial mapping. + for (j = 0, iter = 0; iter < image_histo->size; ++iter) { + if (histograms[iter] == NULL) continue; + mappings[j++] = iter; + } + assert(j == *num_used); + + // Collapse similar histograms in 'image_histo'. + for (iter = 0; + iter < outer_iters && *num_used >= min_cluster_size && + ++tries_with_no_success < num_tries_no_success; + ++iter) { + int* mapping_index; + float best_cost = + (histo_queue.size == 0) ? 0.f : histo_queue.queue[0].cost_diff; + int best_idx1 = -1, best_idx2 = 1; + const uint32_t rand_range = (*num_used - 1) * (*num_used); + // (*num_used) / 2 was chosen empirically. Less means faster but worse + // compression. + const int num_tries = (*num_used) / 2; + + // Pick random samples. + for (j = 0; *num_used >= 2 && j < num_tries; ++j) { + float curr_cost; + // Choose two different histograms at random and try to combine them. + const uint32_t tmp = MyRand(&seed) % rand_range; + uint32_t idx1 = tmp / (*num_used - 1); + uint32_t idx2 = tmp % (*num_used - 1); + if (idx2 >= idx1) ++idx2; + idx1 = mappings[idx1]; + idx2 = mappings[idx2]; + + // Calculate cost reduction on combination. + curr_cost = + HistoQueuePush(&histo_queue, histograms, idx1, idx2, best_cost); + if (curr_cost < 0) { // found a better pair? + best_cost = curr_cost; + // Empty the queue if we reached full capacity. + if (histo_queue.size == histo_queue.max_size) break; + } + } + if (histo_queue.size == 0) continue; + + // Get the best histograms. + best_idx1 = histo_queue.queue[0].idx1; + best_idx2 = histo_queue.queue[0].idx2; + assert(best_idx1 < best_idx2); + // Pop best_idx2 from mappings. + mapping_index = (int*) bsearch(&best_idx2, mappings, *num_used, + sizeof(best_idx2), &PairComparison); + assert(mapping_index != NULL); + memmove(mapping_index, mapping_index + 1, sizeof(*mapping_index) * + ((*num_used) - (mapping_index - mappings) - 1)); + // Merge the histograms and remove best_idx2 from the queue. + HistogramAdd(histograms[best_idx2], histograms[best_idx1], + histograms[best_idx1]); + histograms[best_idx1]->bit_cost_ = histo_queue.queue[0].cost_combo; + HistogramSetRemoveHistogram(image_histo, best_idx2, num_used); + // Parse the queue and update each pair that deals with best_idx1, + // best_idx2 or image_histo_size. + for (j = 0; j < histo_queue.size;) { + HistogramPair* const p = histo_queue.queue + j; + const int is_idx1_best = p->idx1 == best_idx1 || p->idx1 == best_idx2; + const int is_idx2_best = p->idx2 == best_idx1 || p->idx2 == best_idx2; + int do_eval = 0; + // The front pair could have been duplicated by a random pick so + // check for it all the time nevertheless. + if (is_idx1_best && is_idx2_best) { + HistoQueuePopPair(&histo_queue, p); + continue; + } + // Any pair containing one of the two best indices should only refer to + // best_idx1. Its cost should also be updated. + if (is_idx1_best) { + p->idx1 = best_idx1; + do_eval = 1; + } else if (is_idx2_best) { + p->idx2 = best_idx1; + do_eval = 1; + } + // Make sure the index order is respected. + if (p->idx1 > p->idx2) { + const int tmp = p->idx2; + p->idx2 = p->idx1; + p->idx1 = tmp; + } + if (do_eval) { + // Re-evaluate the cost of an updated pair. + HistoQueueUpdatePair(histograms[p->idx1], histograms[p->idx2], 0., p); + if (p->cost_diff >= 0.) { + HistoQueuePopPair(&histo_queue, p); + continue; + } + } + HistoQueueUpdateHead(&histo_queue, p); + ++j; + } + tries_with_no_success = 0; + } + *do_greedy = (*num_used <= min_cluster_size); + ok = 1; + + End: + HistoQueueClear(&histo_queue); + WebPSafeFree(mappings); + return ok; +} + +// ----------------------------------------------------------------------------- +// Histogram refinement + +// Find the best 'out' histogram for each of the 'in' histograms. +// At call-time, 'out' contains the histograms of the clusters. +// Note: we assume that out[]->bit_cost_ is already up-to-date. +static void HistogramRemap(const VP8LHistogramSet* const in, + VP8LHistogramSet* const out, + uint16_t* const symbols) { + int i; + VP8LHistogram** const in_histo = in->histograms; + VP8LHistogram** const out_histo = out->histograms; + const int in_size = out->max_size; + const int out_size = out->size; + if (out_size > 1) { + for (i = 0; i < in_size; ++i) { + int best_out = 0; + float best_bits = MAX_BIT_COST; + int k; + if (in_histo[i] == NULL) { + // Arbitrarily set to the previous value if unused to help future LZ77. + symbols[i] = symbols[i - 1]; + continue; + } + for (k = 0; k < out_size; ++k) { + float cur_bits; + cur_bits = HistogramAddThresh(out_histo[k], in_histo[i], best_bits); + if (k == 0 || cur_bits < best_bits) { + best_bits = cur_bits; + best_out = k; + } + } + symbols[i] = best_out; + } + } else { + assert(out_size == 1); + for (i = 0; i < in_size; ++i) { + symbols[i] = 0; + } + } + + // Recompute each out based on raw and symbols. + VP8LHistogramSetClear(out); + out->size = out_size; + + for (i = 0; i < in_size; ++i) { + int idx; + if (in_histo[i] == NULL) continue; + idx = symbols[i]; + HistogramAdd(in_histo[i], out_histo[idx], out_histo[idx]); + } +} + +static float GetCombineCostFactor(int histo_size, int quality) { + float combine_cost_factor = 0.16f; + if (quality < 90) { + if (histo_size > 256) combine_cost_factor /= 2.f; + if (histo_size > 512) combine_cost_factor /= 2.f; + if (histo_size > 1024) combine_cost_factor /= 2.f; + if (quality <= 50) combine_cost_factor /= 2.f; + } + return combine_cost_factor; +} + +// Given a HistogramSet 'set', the mapping of clusters 'cluster_mapping' and the +// current assignment of the cells in 'symbols', merge the clusters and +// assign the smallest possible clusters values. +static void OptimizeHistogramSymbols(const VP8LHistogramSet* const set, + uint16_t* const cluster_mappings, + int num_clusters, + uint16_t* const cluster_mappings_tmp, + uint16_t* const symbols) { + int i, cluster_max; + int do_continue = 1; + // First, assign the lowest cluster to each pixel. + while (do_continue) { + do_continue = 0; + for (i = 0; i < num_clusters; ++i) { + int k; + k = cluster_mappings[i]; + while (k != cluster_mappings[k]) { + cluster_mappings[k] = cluster_mappings[cluster_mappings[k]]; + k = cluster_mappings[k]; + } + if (k != cluster_mappings[i]) { + do_continue = 1; + cluster_mappings[i] = k; + } + } + } + // Create a mapping from a cluster id to its minimal version. + cluster_max = 0; + memset(cluster_mappings_tmp, 0, + set->max_size * sizeof(*cluster_mappings_tmp)); + assert(cluster_mappings[0] == 0); + // Re-map the ids. + for (i = 0; i < set->max_size; ++i) { + int cluster; + if (symbols[i] == kInvalidHistogramSymbol) continue; + cluster = cluster_mappings[symbols[i]]; + assert(symbols[i] < num_clusters); + if (cluster > 0 && cluster_mappings_tmp[cluster] == 0) { + ++cluster_max; + cluster_mappings_tmp[cluster] = cluster_max; + } + symbols[i] = cluster_mappings_tmp[cluster]; + } + + // Make sure all cluster values are used. + cluster_max = 0; + for (i = 0; i < set->max_size; ++i) { + if (symbols[i] == kInvalidHistogramSymbol) continue; + if (symbols[i] <= cluster_max) continue; + ++cluster_max; + assert(symbols[i] == cluster_max); + } +} + +static void RemoveEmptyHistograms(VP8LHistogramSet* const image_histo) { + uint32_t size; + int i; + for (i = 0, size = 0; i < image_histo->size; ++i) { + if (image_histo->histograms[i] == NULL) continue; + image_histo->histograms[size++] = image_histo->histograms[i]; + } + image_histo->size = size; +} + +int VP8LGetHistoImageSymbols(int xsize, int ysize, + const VP8LBackwardRefs* const refs, int quality, + int low_effort, int histogram_bits, int cache_bits, + VP8LHistogramSet* const image_histo, + VP8LHistogram* const tmp_histo, + uint16_t* const histogram_symbols, + const WebPPicture* const pic, int percent_range, + int* const percent) { + const int histo_xsize = + histogram_bits ? VP8LSubSampleSize(xsize, histogram_bits) : 1; + const int histo_ysize = + histogram_bits ? VP8LSubSampleSize(ysize, histogram_bits) : 1; + const int image_histo_raw_size = histo_xsize * histo_ysize; + VP8LHistogramSet* const orig_histo = + VP8LAllocateHistogramSet(image_histo_raw_size, cache_bits); + // Don't attempt linear bin-partition heuristic for + // histograms of small sizes (as bin_map will be very sparse) and + // maximum quality q==100 (to preserve the compression gains at that level). + const int entropy_combine_num_bins = low_effort ? NUM_PARTITIONS : BIN_SIZE; + int entropy_combine; + uint16_t* const map_tmp = + WebPSafeMalloc(2 * image_histo_raw_size, sizeof(map_tmp)); + uint16_t* const cluster_mappings = map_tmp + image_histo_raw_size; + int num_used = image_histo_raw_size; + if (orig_histo == NULL || map_tmp == NULL) { + WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY); + goto Error; + } + + // Construct the histograms from backward references. + HistogramBuild(xsize, histogram_bits, refs, orig_histo); + // Copies the histograms and computes its bit_cost. + // histogram_symbols is optimized + HistogramCopyAndAnalyze(orig_histo, image_histo, &num_used, + histogram_symbols); + + entropy_combine = + (num_used > entropy_combine_num_bins * 2) && (quality < 100); + + if (entropy_combine) { + uint16_t* const bin_map = map_tmp; + const float combine_cost_factor = + GetCombineCostFactor(image_histo_raw_size, quality); + const uint32_t num_clusters = num_used; + + HistogramAnalyzeEntropyBin(image_histo, bin_map, low_effort); + // Collapse histograms with similar entropy. + HistogramCombineEntropyBin( + image_histo, &num_used, histogram_symbols, cluster_mappings, tmp_histo, + bin_map, entropy_combine_num_bins, combine_cost_factor, low_effort); + OptimizeHistogramSymbols(image_histo, cluster_mappings, num_clusters, + map_tmp, histogram_symbols); + } + + // Don't combine the histograms using stochastic and greedy heuristics for + // low-effort compression mode. + if (!low_effort || !entropy_combine) { + const float x = quality / 100.f; + // cubic ramp between 1 and MAX_HISTO_GREEDY: + const int threshold_size = (int)(1 + (x * x * x) * (MAX_HISTO_GREEDY - 1)); + int do_greedy; + if (!HistogramCombineStochastic(image_histo, &num_used, threshold_size, + &do_greedy)) { + WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY); + goto Error; + } + if (do_greedy) { + RemoveEmptyHistograms(image_histo); + if (!HistogramCombineGreedy(image_histo, &num_used)) { + WebPEncodingSetError(pic, VP8_ENC_ERROR_OUT_OF_MEMORY); + goto Error; + } + } + } + + // Find the optimal map from original histograms to the final ones. + RemoveEmptyHistograms(image_histo); + HistogramRemap(orig_histo, image_histo, histogram_symbols); + + if (!WebPReportProgress(pic, *percent + percent_range, percent)) { + goto Error; + } + + Error: + VP8LFreeHistogramSet(orig_histo); + WebPSafeFree(map_tmp); + return (pic->error_code == VP8_ENC_OK); +} |