libwebp-0.6.0-rc1

third_party/libwebp/utils/quant_levels.c

Index: third_party/libwebp/utils/quant_levels.c
diff --git a/third_party/libwebp/utils/quant_levels.c b/third_party/libwebp/utils/quant_levels.c
deleted file mode 100644
index d7c8aab92212394b01a9a359b67ea15e93254fd0..0000000000000000000000000000000000000000
--- a/third_party/libwebp/utils/quant_levels.c
+++ /dev/null
@@ -1,140 +0,0 @@
-// Copyright 2011 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.
-// -----------------------------------------------------------------------------
-//
-// Quantize levels for specified number of quantization-levels ([2, 256]).
-// Min and max values are preserved (usual 0 and 255 for alpha plane).
-//
-// Author: Skal (pascal.massimino@gmail.com)
-
-#include <assert.h>
-
-#include "./quant_levels.h"
-
-#define NUM_SYMBOLS     256
-
-#define MAX_ITER  6             // Maximum number of convergence steps.
-#define ERROR_THRESHOLD 1e-4    // MSE stopping criterion.
-
-// -----------------------------------------------------------------------------
-// Quantize levels.
-
-int QuantizeLevels(uint8_t* const data, int width, int height,
-                   int num_levels, uint64_t* const sse) {
-  int freq[NUM_SYMBOLS] = { 0 };
-  int q_level[NUM_SYMBOLS] = { 0 };
-  double inv_q_level[NUM_SYMBOLS] = { 0 };
-  int min_s = 255, max_s = 0;
-  const size_t data_size = height * width;
-  int i, num_levels_in, iter;
-  double last_err = 1.e38, err = 0.;
-  const double err_threshold = ERROR_THRESHOLD * data_size;
-
-  if (data == NULL) {
-    return 0;
-  }
-
-  if (width <= 0 || height <= 0) {
-    return 0;
-  }
-
-  if (num_levels < 2 || num_levels > 256) {
-    return 0;
-  }
-
-  {
-    size_t n;
-    num_levels_in = 0;
-    for (n = 0; n < data_size; ++n) {
-      num_levels_in += (freq[data[n]] == 0);
-      if (min_s > data[n]) min_s = data[n];
-      if (max_s < data[n]) max_s = data[n];
-      ++freq[data[n]];
-    }
-  }
-
-  if (num_levels_in <= num_levels) goto End;  // nothing to do!
-
-  // Start with uniformly spread centroids.
-  for (i = 0; i < num_levels; ++i) {
-    inv_q_level[i] = min_s + (double)(max_s - min_s) * i / (num_levels - 1);
-  }
-
-  // Fixed values. Won't be changed.
-  q_level[min_s] = 0;
-  q_level[max_s] = num_levels - 1;
-  assert(inv_q_level[0] == min_s);
-  assert(inv_q_level[num_levels - 1] == max_s);
-
-  // k-Means iterations.
-  for (iter = 0; iter < MAX_ITER; ++iter) {
-    double q_sum[NUM_SYMBOLS] = { 0 };
-    double q_count[NUM_SYMBOLS] = { 0 };
-    int s, slot = 0;
-
-    // Assign classes to representatives.
-    for (s = min_s; s <= max_s; ++s) {
-      // Keep track of the nearest neighbour 'slot'
-      while (slot < num_levels - 1 &&
-             2 * s > inv_q_level[slot] + inv_q_level[slot + 1]) {
-        ++slot;
-      }
-      if (freq[s] > 0) {
-        q_sum[slot] += s * freq[s];
-        q_count[slot] += freq[s];
-      }
-      q_level[s] = slot;
-    }
-
-    // Assign new representatives to classes.
-    if (num_levels > 2) {
-      for (slot = 1; slot < num_levels - 1; ++slot) {
-        const double count = q_count[slot];
-        if (count > 0.) {
-          inv_q_level[slot] = q_sum[slot] / count;
-        }
-      }
-    }
-
-    // Compute convergence error.
-    err = 0.;
-    for (s = min_s; s <= max_s; ++s) {
-      const double error = s - inv_q_level[q_level[s]];
-      err += freq[s] * error * error;
-    }
-
-    // Check for convergence: we stop as soon as the error is no
-    // longer improving.
-    if (last_err - err < err_threshold) break;
-    last_err = err;
-  }
-
-  // Remap the alpha plane to quantized values.
-  {
-    // double->int rounding operation can be costly, so we do it
-    // once for all before remapping. We also perform the data[] -> slot
-    // mapping, while at it (avoid one indirection in the final loop).
-    uint8_t map[NUM_SYMBOLS];
-    int s;
-    size_t n;
-    for (s = min_s; s <= max_s; ++s) {
-      const int slot = q_level[s];
-      map[s] = (uint8_t)(inv_q_level[slot] + .5);
-    }
-    // Final pass.
-    for (n = 0; n < data_size; ++n) {
-      data[n] = map[data[n]];
-    }
-  }
- End:
-  // Store sum of squared error if needed.
-  if (sse != NULL) *sse = (uint64_t)err;
-
-  return 1;
-}
-