| /* |
| * Copyright (c) 2015 The WebM 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. |
| */ |
| |
| #ifndef VP10_ENCODER_PALETTE_H_ |
| #define VP10_ENCODER_PALETTE_H_ |
| |
| #include "av1/common/blockd.h" |
| |
| #ifdef __cplusplus |
| extern "C" { |
| #endif |
| |
| void vp10_calc_indices(const float *data, const float *centroids, |
| uint8_t *indices, int n, int k, int dim); |
| |
| // Given 'data' of size 'n' and initial guess of 'centroids' of size 'k x dim', |
| // runs up to 'max_itr' iterations of k-means algorithm to get updated |
| // 'centroids' and the centroid 'indices' for elements in 'data'. |
| // Note: the output centroids are rounded off to nearest integers. |
| void vp10_k_means(const float *data, float *centroids, uint8_t *indices, int n, |
| int k, int dim, int max_itr); |
| |
| // Given a list of centroids, returns the unique number of centroids 'k', and |
| // puts these unique centroids in first 'k' indices of 'centroids' array. |
| // Ideally, the centroids should be rounded to integers before calling this |
| // method. |
| int vp10_remove_duplicates(float *centroids, int num_centroids); |
| |
| int vp10_count_colors(const uint8_t *src, int stride, int rows, int cols); |
| #if CONFIG_VP9_HIGHBITDEPTH |
| int vp10_count_colors_highbd(const uint8_t *src8, int stride, int rows, |
| int cols, int bit_depth); |
| #endif // CONFIG_VP9_HIGHBITDEPTH |
| |
| #ifdef __cplusplus |
| } // extern "C" |
| #endif |
| |
| #endif /* VP10_ENCODER_PALETTE_H_ */ |