/* * Copyright (c) 2012-2013 Oka Motofumi (chikuzen.mo at gmail dot com) * Copyright (c) 2015 Paul B Mahol * * This file is part of FFmpeg. * * FFmpeg is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * FFmpeg is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with FFmpeg; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config_components.h" #include "libavutil/avstring.h" #include "libavutil/imgutils.h" #include "libavutil/intreadwrite.h" #include "libavutil/mem.h" #include "libavutil/mem_internal.h" #include "libavutil/opt.h" #include "libavutil/pixdesc.h" #include "avfilter.h" #include "convolution.h" #include "internal.h" #include "video.h" #define OFFSET(x) offsetof(ConvolutionContext, x) #define FLAGS AV_OPT_FLAG_VIDEO_PARAM|AV_OPT_FLAG_FILTERING_PARAM|AV_OPT_FLAG_RUNTIME_PARAM static const AVOption convolution_options[] = { { "0m", "set matrix for 1st plane", OFFSET(matrix_str[0]), AV_OPT_TYPE_STRING, {.str="0 0 0 0 1 0 0 0 0"}, 0, 0, FLAGS }, { "1m", "set matrix for 2nd plane", OFFSET(matrix_str[1]), AV_OPT_TYPE_STRING, {.str="0 0 0 0 1 0 0 0 0"}, 0, 0, FLAGS }, { "2m", "set matrix for 3rd plane", OFFSET(matrix_str[2]), AV_OPT_TYPE_STRING, {.str="0 0 0 0 1 0 0 0 0"}, 0, 0, FLAGS }, { "3m", "set matrix for 4th plane", OFFSET(matrix_str[3]), AV_OPT_TYPE_STRING, {.str="0 0 0 0 1 0 0 0 0"}, 0, 0, FLAGS }, { "0rdiv", "set rdiv for 1st plane", OFFSET(user_rdiv[0]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS}, { "1rdiv", "set rdiv for 2nd plane", OFFSET(user_rdiv[1]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS}, { "2rdiv", "set rdiv for 3rd plane", OFFSET(user_rdiv[2]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS}, { "3rdiv", "set rdiv for 4th plane", OFFSET(user_rdiv[3]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS}, { "0bias", "set bias for 1st plane", OFFSET(bias[0]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS}, { "1bias", "set bias for 2nd plane", OFFSET(bias[1]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS}, { "2bias", "set bias for 3rd plane", OFFSET(bias[2]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS}, { "3bias", "set bias for 4th plane", OFFSET(bias[3]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS}, { "0mode", "set matrix mode for 1st plane", OFFSET(mode[0]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, .unit = "mode" }, { "1mode", "set matrix mode for 2nd plane", OFFSET(mode[1]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, .unit = "mode" }, { "2mode", "set matrix mode for 3rd plane", OFFSET(mode[2]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, .unit = "mode" }, { "3mode", "set matrix mode for 4th plane", OFFSET(mode[3]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, .unit = "mode" }, { "square", "square matrix", 0, AV_OPT_TYPE_CONST, {.i64=MATRIX_SQUARE}, 0, 0, FLAGS, .unit = "mode" }, { "row", "single row matrix", 0, AV_OPT_TYPE_CONST, {.i64=MATRIX_ROW} , 0, 0, FLAGS, .unit = "mode" }, { "column", "single column matrix", 0, AV_OPT_TYPE_CONST, {.i64=MATRIX_COLUMN}, 0, 0, FLAGS, .unit = "mode" }, { NULL } }; AVFILTER_DEFINE_CLASS(convolution); static const int same3x3[9] = {0, 0, 0, 0, 1, 0, 0, 0, 0}; static const int same5x5[25] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; static const int same7x7[49] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; static const enum AVPixelFormat pix_fmts[] = { AV_PIX_FMT_YUVA444P, AV_PIX_FMT_YUV444P, AV_PIX_FMT_YUV440P, AV_PIX_FMT_YUVJ444P, AV_PIX_FMT_YUVJ440P, AV_PIX_FMT_YUVA422P, AV_PIX_FMT_YUV422P, AV_PIX_FMT_YUVA420P, AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUVJ422P, AV_PIX_FMT_YUVJ420P, AV_PIX_FMT_YUVJ411P, AV_PIX_FMT_YUV411P, AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV420P9, AV_PIX_FMT_YUV422P9, AV_PIX_FMT_YUV444P9, AV_PIX_FMT_YUV420P10, AV_PIX_FMT_YUV422P10, AV_PIX_FMT_YUV444P10, AV_PIX_FMT_YUV420P12, AV_PIX_FMT_YUV422P12, AV_PIX_FMT_YUV444P12, AV_PIX_FMT_YUV440P12, AV_PIX_FMT_YUV420P14, AV_PIX_FMT_YUV422P14, AV_PIX_FMT_YUV444P14, AV_PIX_FMT_YUV420P16, AV_PIX_FMT_YUV422P16, AV_PIX_FMT_YUV444P16, AV_PIX_FMT_YUVA420P9, AV_PIX_FMT_YUVA422P9, AV_PIX_FMT_YUVA444P9, AV_PIX_FMT_YUVA420P10, AV_PIX_FMT_YUVA422P10, AV_PIX_FMT_YUVA444P10, AV_PIX_FMT_YUVA422P12, AV_PIX_FMT_YUVA444P12, AV_PIX_FMT_YUVA420P16, AV_PIX_FMT_YUVA422P16, AV_PIX_FMT_YUVA444P16, AV_PIX_FMT_GBRP, AV_PIX_FMT_GBRP9, AV_PIX_FMT_GBRP10, AV_PIX_FMT_GBRP12, AV_PIX_FMT_GBRP14, AV_PIX_FMT_GBRP16, AV_PIX_FMT_GBRAP, AV_PIX_FMT_GBRAP10, AV_PIX_FMT_GBRAP12, AV_PIX_FMT_GBRAP16, AV_PIX_FMT_GRAY8, AV_PIX_FMT_GRAY9, AV_PIX_FMT_GRAY10, AV_PIX_FMT_GRAY12, AV_PIX_FMT_GRAY14, AV_PIX_FMT_GRAY16, AV_PIX_FMT_NONE }; typedef struct ThreadData { AVFrame *in, *out; } ThreadData; static void filter16_prewitt(uint8_t *dstp, int width, float scale, float delta, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { uint16_t *dst = (uint16_t *)dstp; int x; for (x = 0; x < width; x++) { float suma = AV_RN16A(&c[0][2 * x]) * -1 + AV_RN16A(&c[1][2 * x]) * -1 + AV_RN16A(&c[2][2 * x]) * -1 + AV_RN16A(&c[6][2 * x]) * 1 + AV_RN16A(&c[7][2 * x]) * 1 + AV_RN16A(&c[8][2 * x]) * 1; float sumb = AV_RN16A(&c[0][2 * x]) * -1 + AV_RN16A(&c[2][2 * x]) * 1 + AV_RN16A(&c[3][2 * x]) * -1 + AV_RN16A(&c[5][2 * x]) * 1 + AV_RN16A(&c[6][2 * x]) * -1 + AV_RN16A(&c[8][2 * x]) * 1; dst[x] = av_clip(sqrtf(suma*suma + sumb*sumb) * scale + delta, 0, peak); } } static void filter16_roberts(uint8_t *dstp, int width, float scale, float delta, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { uint16_t *dst = (uint16_t *)dstp; int x; for (x = 0; x < width; x++) { float suma = AV_RN16A(&c[0][2 * x]) * 1 + AV_RN16A(&c[1][2 * x]) * -1; float sumb = AV_RN16A(&c[4][2 * x]) * 1 + AV_RN16A(&c[3][2 * x]) * -1; dst[x] = av_clip(sqrtf(suma*suma + sumb*sumb) * scale + delta, 0, peak); } } static void filter16_scharr(uint8_t *dstp, int width, float scale, float delta, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { uint16_t *dst = (uint16_t *)dstp; int x; for (x = 0; x < width; x++) { float suma = AV_RN16A(&c[0][2 * x]) * -47 + AV_RN16A(&c[1][2 * x]) * -162 + AV_RN16A(&c[2][2 * x]) * -47 + AV_RN16A(&c[6][2 * x]) * 47 + AV_RN16A(&c[7][2 * x]) * 162 + AV_RN16A(&c[8][2 * x]) * 47; float sumb = AV_RN16A(&c[0][2 * x]) * -47 + AV_RN16A(&c[2][2 * x]) * 47 + AV_RN16A(&c[3][2 * x]) * -162 + AV_RN16A(&c[5][2 * x]) * 162 + AV_RN16A(&c[6][2 * x]) * -47 + AV_RN16A(&c[8][2 * x]) * 47; suma /= 256.f; sumb /= 256.f; dst[x] = av_clip(sqrtf(suma*suma + sumb*sumb) * scale + delta, 0, peak); } } static void filter16_kirsch(uint8_t *dstp, int width, float scale, float delta, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { uint16_t *dst = (uint16_t *)dstp; const uint16_t *c0 = (const uint16_t *)c[0], *c1 = (const uint16_t *)c[1], *c2 = (const uint16_t *)c[2]; const uint16_t *c3 = (const uint16_t *)c[3], *c5 = (const uint16_t *)c[5]; const uint16_t *c6 = (const uint16_t *)c[6], *c7 = (const uint16_t *)c[7], *c8 = (const uint16_t *)c[8]; int x; for (x = 0; x < width; x++) { int sum0 = c0[x] * 5 + c1[x] * 5 + c2[x] * 5 + c3[x] * -3 + c5[x] * -3 + c6[x] * -3 + c7[x] * -3 + c8[x] * -3; int sum1 = c0[x] * -3 + c1[x] * 5 + c2[x] * 5 + c3[x] * 5 + c5[x] * -3 + c6[x] * -3 + c7[x] * -3 + c8[x] * -3; int sum2 = c0[x] * -3 + c1[x] * -3 + c2[x] * 5 + c3[x] * 5 + c5[x] * 5 + c6[x] * -3 + c7[x] * -3 + c8[x] * -3; int sum3 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 + c3[x] * 5 + c5[x] * 5 + c6[x] * 5 + c7[x] * -3 + c8[x] * -3; int sum4 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 + c3[x] * -3 + c5[x] * 5 + c6[x] * 5 + c7[x] * 5 + c8[x] * -3; int sum5 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 + c3[x] * -3 + c5[x] * -3 + c6[x] * 5 + c7[x] * 5 + c8[x] * 5; int sum6 = c0[x] * 5 + c1[x] * -3 + c2[x] * -3 + c3[x] * -3 + c5[x] * -3 + c6[x] * -3 + c7[x] * 5 + c8[x] * 5; int sum7 = c0[x] * 5 + c1[x] * 5 + c2[x] * -3 + c3[x] * -3 + c5[x] * -3 + c6[x] * -3 + c7[x] * -3 + c8[x] * 5; sum0 = FFMAX(sum0, sum1); sum2 = FFMAX(sum2, sum3); sum4 = FFMAX(sum4, sum5); sum6 = FFMAX(sum6, sum7); sum0 = FFMAX(sum0, sum2); sum4 = FFMAX(sum4, sum6); sum0 = FFMAX(sum0, sum4); dst[x] = av_clip(FFABS(sum0) * scale + delta, 0, peak); } } static void filter_prewitt(uint8_t *dst, int width, float scale, float delta, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { const uint8_t *c0 = c[0], *c1 = c[1], *c2 = c[2]; const uint8_t *c3 = c[3], *c5 = c[5]; const uint8_t *c6 = c[6], *c7 = c[7], *c8 = c[8]; int x; for (x = 0; x < width; x++) { float suma = c0[x] * -1 + c1[x] * -1 + c2[x] * -1 + c6[x] * 1 + c7[x] * 1 + c8[x] * 1; float sumb = c0[x] * -1 + c2[x] * 1 + c3[x] * -1 + c5[x] * 1 + c6[x] * -1 + c8[x] * 1; dst[x] = av_clip_uint8(sqrtf(suma*suma + sumb*sumb) * scale + delta); } } static void filter_roberts(uint8_t *dst, int width, float scale, float delta, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { int x; for (x = 0; x < width; x++) { float suma = c[0][x] * 1 + c[1][x] * -1; float sumb = c[4][x] * 1 + c[3][x] * -1; dst[x] = av_clip_uint8(sqrtf(suma*suma + sumb*sumb) * scale + delta); } } static void filter_scharr(uint8_t *dst, int width, float scale, float delta, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { const uint8_t *c0 = c[0], *c1 = c[1], *c2 = c[2]; const uint8_t *c3 = c[3], *c5 = c[5]; const uint8_t *c6 = c[6], *c7 = c[7], *c8 = c[8]; int x; for (x = 0; x < width; x++) { float suma = c0[x] * -47 + c1[x] * -162 + c2[x] * -47 + c6[x] * 47 + c7[x] * 162 + c8[x] * 47; float sumb = c0[x] * -47 + c2[x] * 47 + c3[x] * -162 + c5[x] * 162 + c6[x] * -47 + c8[x] * 47; suma /= 256.f; sumb /= 256.f; dst[x] = av_clip_uint8(sqrtf(suma*suma + sumb*sumb) * scale + delta); } } static void filter_kirsch(uint8_t *dst, int width, float scale, float delta, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { const uint8_t *c0 = c[0], *c1 = c[1], *c2 = c[2]; const uint8_t *c3 = c[3], *c5 = c[5]; const uint8_t *c6 = c[6], *c7 = c[7], *c8 = c[8]; int x; for (x = 0; x < width; x++) { int sum0 = c0[x] * 5 + c1[x] * 5 + c2[x] * 5 + c3[x] * -3 + c5[x] * -3 + c6[x] * -3 + c7[x] * -3 + c8[x] * -3; int sum1 = c0[x] * -3 + c1[x] * 5 + c2[x] * 5 + c3[x] * 5 + c5[x] * -3 + c6[x] * -3 + c7[x] * -3 + c8[x] * -3; int sum2 = c0[x] * -3 + c1[x] * -3 + c2[x] * 5 + c3[x] * 5 + c5[x] * 5 + c6[x] * -3 + c7[x] * -3 + c8[x] * -3; int sum3 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 + c3[x] * 5 + c5[x] * 5 + c6[x] * 5 + c7[x] * -3 + c8[x] * -3; int sum4 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 + c3[x] * -3 + c5[x] * 5 + c6[x] * 5 + c7[x] * 5 + c8[x] * -3; int sum5 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 + c3[x] * -3 + c5[x] * -3 + c6[x] * 5 + c7[x] * 5 + c8[x] * 5; int sum6 = c0[x] * 5 + c1[x] * -3 + c2[x] * -3 + c3[x] * -3 + c5[x] * -3 + c6[x] * -3 + c7[x] * 5 + c8[x] * 5; int sum7 = c0[x] * 5 + c1[x] * 5 + c2[x] * -3 + c3[x] * -3 + c5[x] * -3 + c6[x] * -3 + c7[x] * -3 + c8[x] * 5; sum0 = FFMAX(sum0, sum1); sum2 = FFMAX(sum2, sum3); sum4 = FFMAX(sum4, sum5); sum6 = FFMAX(sum6, sum7); sum0 = FFMAX(sum0, sum2); sum4 = FFMAX(sum4, sum6); sum0 = FFMAX(sum0, sum4); dst[x] = av_clip_uint8(FFABS(sum0) * scale + delta); } } static void filter16_3x3(uint8_t *dstp, int width, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { uint16_t *dst = (uint16_t *)dstp; int x; for (x = 0; x < width; x++) { int sum = AV_RN16A(&c[0][2 * x]) * matrix[0] + AV_RN16A(&c[1][2 * x]) * matrix[1] + AV_RN16A(&c[2][2 * x]) * matrix[2] + AV_RN16A(&c[3][2 * x]) * matrix[3] + AV_RN16A(&c[4][2 * x]) * matrix[4] + AV_RN16A(&c[5][2 * x]) * matrix[5] + AV_RN16A(&c[6][2 * x]) * matrix[6] + AV_RN16A(&c[7][2 * x]) * matrix[7] + AV_RN16A(&c[8][2 * x]) * matrix[8]; sum = (int)(sum * rdiv + bias + 0.5f); dst[x] = av_clip(sum, 0, peak); } } static void filter16_5x5(uint8_t *dstp, int width, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { uint16_t *dst = (uint16_t *)dstp; int x; for (x = 0; x < width; x++) { int i, sum = 0; for (i = 0; i < 25; i++) sum += AV_RN16A(&c[i][2 * x]) * matrix[i]; sum = (int)(sum * rdiv + bias + 0.5f); dst[x] = av_clip(sum, 0, peak); } } static void filter16_7x7(uint8_t *dstp, int width, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { uint16_t *dst = (uint16_t *)dstp; int x; for (x = 0; x < width; x++) { int i, sum = 0; for (i = 0; i < 49; i++) sum += AV_RN16A(&c[i][2 * x]) * matrix[i]; sum = (int)(sum * rdiv + bias + 0.5f); dst[x] = av_clip(sum, 0, peak); } } static void filter16_row(uint8_t *dstp, int width, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { uint16_t *dst = (uint16_t *)dstp; int x; for (x = 0; x < width; x++) { int i, sum = 0; for (i = 0; i < 2 * radius + 1; i++) sum += AV_RN16A(&c[i][2 * x]) * matrix[i]; sum = (int)(sum * rdiv + bias + 0.5f); dst[x] = av_clip(sum, 0, peak); } } static void filter16_column(uint8_t *dstp, int height, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { DECLARE_ALIGNED(64, int, sum)[16]; uint16_t *dst = (uint16_t *)dstp; const int width = FFMIN(16, size); for (int y = 0; y < height; y++) { memset(sum, 0, sizeof(sum)); for (int i = 0; i < 2 * radius + 1; i++) { for (int off16 = 0; off16 < width; off16++) sum[off16] += AV_RN16A(&c[i][0 + y * stride + off16 * 2]) * matrix[i]; } for (int off16 = 0; off16 < width; off16++) { sum[off16] = (int)(sum[off16] * rdiv + bias + 0.5f); dst[off16] = av_clip(sum[off16], 0, peak); } dst += dstride / 2; } } static void filter_7x7(uint8_t *dst, int width, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { int x; for (x = 0; x < width; x++) { int i, sum = 0; for (i = 0; i < 49; i++) sum += c[i][x] * matrix[i]; sum = (int)(sum * rdiv + bias + 0.5f); dst[x] = av_clip_uint8(sum); } } static void filter_5x5(uint8_t *dst, int width, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { int x; for (x = 0; x < width; x++) { int i, sum = 0; for (i = 0; i < 25; i++) sum += c[i][x] * matrix[i]; sum = (int)(sum * rdiv + bias + 0.5f); dst[x] = av_clip_uint8(sum); } } static void filter_3x3(uint8_t *dst, int width, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { const uint8_t *c0 = c[0], *c1 = c[1], *c2 = c[2]; const uint8_t *c3 = c[3], *c4 = c[4], *c5 = c[5]; const uint8_t *c6 = c[6], *c7 = c[7], *c8 = c[8]; int x; for (x = 0; x < width; x++) { int sum = c0[x] * matrix[0] + c1[x] * matrix[1] + c2[x] * matrix[2] + c3[x] * matrix[3] + c4[x] * matrix[4] + c5[x] * matrix[5] + c6[x] * matrix[6] + c7[x] * matrix[7] + c8[x] * matrix[8]; sum = (int)(sum * rdiv + bias + 0.5f); dst[x] = av_clip_uint8(sum); } } static void filter_row(uint8_t *dst, int width, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { int x; for (x = 0; x < width; x++) { int i, sum = 0; for (i = 0; i < 2 * radius + 1; i++) sum += c[i][x] * matrix[i]; sum = (int)(sum * rdiv + bias + 0.5f); dst[x] = av_clip_uint8(sum); } } static void filter_column(uint8_t *dst, int height, float rdiv, float bias, const int *const matrix, const uint8_t *c[], int peak, int radius, int dstride, int stride, int size) { DECLARE_ALIGNED(64, int, sum)[16]; for (int y = 0; y < height; y++) { memset(sum, 0, sizeof(sum)); for (int i = 0; i < 2 * radius + 1; i++) { for (int off16 = 0; off16 < 16; off16++) sum[off16] += c[i][0 + y * stride + off16] * matrix[i]; } for (int off16 = 0; off16 < 16; off16++) { sum[off16] = (int)(sum[off16] * rdiv + bias + 0.5f); dst[off16] = av_clip_uint8(sum[off16]); } dst += dstride; } } static void setup_5x5(int radius, const uint8_t *c[], const uint8_t *src, int stride, int x, int w, int y, int h, int bpc) { int i; for (i = 0; i < 25; i++) { int xoff = FFABS(x + ((i % 5) - 2)); int yoff = FFABS(y + (i / 5) - 2); xoff = xoff >= w ? 2 * w - 1 - xoff : xoff; yoff = yoff >= h ? 2 * h - 1 - yoff : yoff; c[i] = src + xoff * bpc + yoff * stride; } } static void setup_7x7(int radius, const uint8_t *c[], const uint8_t *src, int stride, int x, int w, int y, int h, int bpc) { int i; for (i = 0; i < 49; i++) { int xoff = FFABS(x + ((i % 7) - 3)); int yoff = FFABS(y + (i / 7) - 3); xoff = xoff >= w ? 2 * w - 1 - xoff : xoff; yoff = yoff >= h ? 2 * h - 1 - yoff : yoff; c[i] = src + xoff * bpc + yoff * stride; } } static void setup_row(int radius, const uint8_t *c[], const uint8_t *src, int stride, int x, int w, int y, int h, int bpc) { int i; for (i = 0; i < radius * 2 + 1; i++) { int xoff = FFABS(x + i - radius); xoff = xoff >= w ? 2 * w - 1 - xoff : xoff; c[i] = src + xoff * bpc + y * stride; } } static void setup_column(int radius, const uint8_t *c[], const uint8_t *src, int stride, int x, int w, int y, int h, int bpc) { int i; for (i = 0; i < radius * 2 + 1; i++) { int xoff = FFABS(x + i - radius); xoff = xoff >= h ? 2 * h - 1 - xoff : xoff; c[i] = src + y * bpc + xoff * stride; } } static int filter_slice(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs) { ConvolutionContext *s = ctx->priv; ThreadData *td = arg; AVFrame *in = td->in; AVFrame *out = td->out; int plane; for (plane = 0; plane < s->nb_planes; plane++) { const int mode = s->mode[plane]; const int bpc = s->bpc; const int radius = s->size[plane] / 2; const int height = s->planeheight[plane]; const int width = s->planewidth[plane]; const int stride = in->linesize[plane]; const int dstride = out->linesize[plane]; const int sizeh = mode == MATRIX_COLUMN ? width : height; const int sizew = mode == MATRIX_COLUMN ? height : width; const int slice_start = (sizeh * jobnr) / nb_jobs; const int slice_end = (sizeh * (jobnr+1)) / nb_jobs; const float rdiv = s->rdiv[plane]; const float bias = s->bias[plane]; const uint8_t *src = in->data[plane]; const int dst_pos = slice_start * (mode == MATRIX_COLUMN ? bpc : dstride); uint8_t *dst = out->data[plane] + dst_pos; const int *matrix = s->matrix[plane]; const int step = mode == MATRIX_COLUMN ? 16 : 1; const uint8_t *c[49]; int y, x; if (s->copy[plane]) { if (mode == MATRIX_COLUMN) av_image_copy_plane(dst, dstride, src + slice_start * bpc, stride, (slice_end - slice_start) * bpc, height); else av_image_copy_plane(dst, dstride, src + slice_start * stride, stride, width * bpc, slice_end - slice_start); continue; } for (y = slice_start; y < slice_end; y += step) { const int xoff = mode == MATRIX_COLUMN ? (y - slice_start) * bpc : radius * bpc; const int yoff = mode == MATRIX_COLUMN ? radius * dstride : 0; for (x = 0; x < radius; x++) { const int xoff = mode == MATRIX_COLUMN ? (y - slice_start) * bpc : x * bpc; const int yoff = mode == MATRIX_COLUMN ? x * dstride : 0; s->setup[plane](radius, c, src, stride, x, width, y, height, bpc); s->filter[plane](dst + yoff + xoff, 1, rdiv, bias, matrix, c, s->max, radius, dstride, stride, slice_end - step); } s->setup[plane](radius, c, src, stride, radius, width, y, height, bpc); s->filter[plane](dst + yoff + xoff, sizew - 2 * radius, rdiv, bias, matrix, c, s->max, radius, dstride, stride, slice_end - step); for (x = sizew - radius; x < sizew; x++) { const int xoff = mode == MATRIX_COLUMN ? (y - slice_start) * bpc : x * bpc; const int yoff = mode == MATRIX_COLUMN ? x * dstride : 0; s->setup[plane](radius, c, src, stride, x, width, y, height, bpc); s->filter[plane](dst + yoff + xoff, 1, rdiv, bias, matrix, c, s->max, radius, dstride, stride, slice_end - step); } if (mode != MATRIX_COLUMN) dst += dstride; } } return 0; } static int param_init(AVFilterContext *ctx) { ConvolutionContext *s = ctx->priv; AVFilterLink *inlink = ctx->inputs[0]; const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format); int p, i; s->depth = desc->comp[0].depth; s->max = (1 << s->depth) - 1; s->planewidth[1] = s->planewidth[2] = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w); s->planewidth[0] = s->planewidth[3] = inlink->w; s->planeheight[1] = s->planeheight[2] = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h); s->planeheight[0] = s->planeheight[3] = inlink->h; s->nb_planes = av_pix_fmt_count_planes(inlink->format); s->nb_threads = ff_filter_get_nb_threads(ctx); s->bpc = (s->depth + 7) / 8; if (!strcmp(ctx->filter->name, "convolution")) { for (i = 0; i < 4; i++) { int *matrix = (int *)s->matrix[i]; char *orig, *p, *arg, *saveptr = NULL; float sum = 1.f; p = orig = av_strdup(s->matrix_str[i]); if (p) { s->matrix_length[i] = 0; s->rdiv[i] = s->user_rdiv[i]; sum = 0.f; while (s->matrix_length[i] < 49) { if (!(arg = av_strtok(p, " |", &saveptr))) break; p = NULL; sscanf(arg, "%d", &matrix[s->matrix_length[i]]); sum += matrix[s->matrix_length[i]]; s->matrix_length[i]++; } av_freep(&orig); if (!(s->matrix_length[i] & 1)) { av_log(ctx, AV_LOG_ERROR, "number of matrix elements must be odd\n"); return AVERROR(EINVAL); } } if (s->mode[i] == MATRIX_ROW) { s->filter[i] = filter_row; s->setup[i] = setup_row; s->size[i] = s->matrix_length[i]; } else if (s->mode[i] == MATRIX_COLUMN) { s->filter[i] = filter_column; s->setup[i] = setup_column; s->size[i] = s->matrix_length[i]; } else if (s->matrix_length[i] == 9) { s->size[i] = 3; if (!memcmp(matrix, same3x3, sizeof(same3x3))) { s->copy[i] = 1; } else { s->filter[i] = filter_3x3; s->copy[i] = 0; } s->setup[i] = setup_3x3; } else if (s->matrix_length[i] == 25) { s->size[i] = 5; if (!memcmp(matrix, same5x5, sizeof(same5x5))) { s->copy[i] = 1; } else { s->filter[i] = filter_5x5; s->copy[i] = 0; } s->setup[i] = setup_5x5; } else if (s->matrix_length[i] == 49) { s->size[i] = 7; if (!memcmp(matrix, same7x7, sizeof(same7x7))) { s->copy[i] = 1; } else { s->filter[i] = filter_7x7; s->copy[i] = 0; } s->setup[i] = setup_7x7; } else { return AVERROR(EINVAL); } if (sum == 0) sum = 1; if (s->rdiv[i] == 0) s->rdiv[i] = 1. / sum; if (s->copy[i] && (s->rdiv[i] != 1. || s->bias[i] != 0.)) s->copy[i] = 0; } } else if (!strcmp(ctx->filter->name, "prewitt")) { for (i = 0; i < 4; i++) { s->filter[i] = filter_prewitt; s->copy[i] = !((1 << i) & s->planes); s->size[i] = 3; s->setup[i] = setup_3x3; s->rdiv[i] = s->scale; s->bias[i] = s->delta; } } else if (!strcmp(ctx->filter->name, "roberts")) { for (i = 0; i < 4; i++) { s->filter[i] = filter_roberts; s->copy[i] = !((1 << i) & s->planes); s->size[i] = 3; s->setup[i] = setup_3x3; s->rdiv[i] = s->scale; s->bias[i] = s->delta; } #if CONFIG_SOBEL_FILTER } else if (!strcmp(ctx->filter->name, "sobel")) { ff_sobel_init(s, s->depth, s->nb_planes); #endif } else if (!strcmp(ctx->filter->name, "kirsch")) { for (i = 0; i < 4; i++) { s->filter[i] = filter_kirsch; s->copy[i] = !((1 << i) & s->planes); s->size[i] = 3; s->setup[i] = setup_3x3; s->rdiv[i] = s->scale; s->bias[i] = s->delta; } } else if (!strcmp(ctx->filter->name, "scharr")) { for (i = 0; i < 4; i++) { s->filter[i] = filter_scharr; s->copy[i] = !((1 << i) & s->planes); s->size[i] = 3; s->setup[i] = setup_3x3; s->rdiv[i] = s->scale; s->bias[i] = s->delta; } } if (!strcmp(ctx->filter->name, "convolution")) { if (s->depth > 8) { for (p = 0; p < s->nb_planes; p++) { if (s->mode[p] == MATRIX_ROW) s->filter[p] = filter16_row; else if (s->mode[p] == MATRIX_COLUMN) s->filter[p] = filter16_column; else if (s->size[p] == 3) s->filter[p] = filter16_3x3; else if (s->size[p] == 5) s->filter[p] = filter16_5x5; else if (s->size[p] == 7) s->filter[p] = filter16_7x7; } } #if CONFIG_CONVOLUTION_FILTER && ARCH_X86_64 ff_convolution_init_x86(s); #endif } else if (!strcmp(ctx->filter->name, "prewitt")) { if (s->depth > 8) for (p = 0; p < s->nb_planes; p++) s->filter[p] = filter16_prewitt; } else if (!strcmp(ctx->filter->name, "roberts")) { if (s->depth > 8) for (p = 0; p < s->nb_planes; p++) s->filter[p] = filter16_roberts; } else if (!strcmp(ctx->filter->name, "kirsch")) { if (s->depth > 8) for (p = 0; p < s->nb_planes; p++) s->filter[p] = filter16_kirsch; } else if (!strcmp(ctx->filter->name, "scharr")) { if (s->depth > 8) for (p = 0; p < s->nb_planes; p++) s->filter[p] = filter16_scharr; } return 0; } static int config_input(AVFilterLink *inlink) { AVFilterContext *ctx = inlink->dst; return param_init(ctx); } static int filter_frame(AVFilterLink *inlink, AVFrame *in) { AVFilterContext *ctx = inlink->dst; ConvolutionContext *s = ctx->priv; AVFilterLink *outlink = ctx->outputs[0]; AVFrame *out; ThreadData td; out = ff_get_video_buffer(outlink, outlink->w, outlink->h); if (!out) { av_frame_free(&in); return AVERROR(ENOMEM); } av_frame_copy_props(out, in); td.in = in; td.out = out; ff_filter_execute(ctx, filter_slice, &td, NULL, FFMIN3(s->planeheight[1], s->planewidth[1], s->nb_threads)); av_frame_free(&in); return ff_filter_frame(outlink, out); } static int process_command(AVFilterContext *ctx, const char *cmd, const char *args, char *res, int res_len, int flags) { int ret; ret = ff_filter_process_command(ctx, cmd, args, res, res_len, flags); if (ret < 0) return ret; return param_init(ctx); } static const AVFilterPad convolution_inputs[] = { { .name = "default", .type = AVMEDIA_TYPE_VIDEO, .config_props = config_input, .filter_frame = filter_frame, }, }; #if CONFIG_CONVOLUTION_FILTER const AVFilter ff_vf_convolution = { .name = "convolution", .description = NULL_IF_CONFIG_SMALL("Apply convolution filter."), .priv_size = sizeof(ConvolutionContext), .priv_class = &convolution_class, FILTER_INPUTS(convolution_inputs), FILTER_OUTPUTS(ff_video_default_filterpad), FILTER_PIXFMTS_ARRAY(pix_fmts), .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS, .process_command = process_command, }; #endif /* CONFIG_CONVOLUTION_FILTER */ static const AVOption common_options[] = { { "planes", "set planes to filter", OFFSET(planes), AV_OPT_TYPE_INT, {.i64=15}, 0, 15, FLAGS}, { "scale", "set scale", OFFSET(scale), AV_OPT_TYPE_FLOAT, {.dbl=1.0}, 0.0, 65535, FLAGS}, { "delta", "set delta", OFFSET(delta), AV_OPT_TYPE_FLOAT, {.dbl=0}, -65535, 65535, FLAGS}, { NULL } }; AVFILTER_DEFINE_CLASS_EXT(common, "kirsch/prewitt/roberts/scharr/sobel", common_options); #if CONFIG_PREWITT_FILTER const AVFilter ff_vf_prewitt = { .name = "prewitt", .description = NULL_IF_CONFIG_SMALL("Apply prewitt operator."), .priv_size = sizeof(ConvolutionContext), .priv_class = &common_class, FILTER_INPUTS(convolution_inputs), FILTER_OUTPUTS(ff_video_default_filterpad), FILTER_PIXFMTS_ARRAY(pix_fmts), .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS, .process_command = process_command, }; #endif /* CONFIG_PREWITT_FILTER */ #if CONFIG_SOBEL_FILTER const AVFilter ff_vf_sobel = { .name = "sobel", .description = NULL_IF_CONFIG_SMALL("Apply sobel operator."), .priv_size = sizeof(ConvolutionContext), .priv_class = &common_class, FILTER_INPUTS(convolution_inputs), FILTER_OUTPUTS(ff_video_default_filterpad), FILTER_PIXFMTS_ARRAY(pix_fmts), .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS, .process_command = process_command, }; #endif /* CONFIG_SOBEL_FILTER */ #if CONFIG_ROBERTS_FILTER const AVFilter ff_vf_roberts = { .name = "roberts", .description = NULL_IF_CONFIG_SMALL("Apply roberts cross operator."), .priv_size = sizeof(ConvolutionContext), .priv_class = &common_class, FILTER_INPUTS(convolution_inputs), FILTER_OUTPUTS(ff_video_default_filterpad), FILTER_PIXFMTS_ARRAY(pix_fmts), .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS, .process_command = process_command, }; #endif /* CONFIG_ROBERTS_FILTER */ #if CONFIG_KIRSCH_FILTER const AVFilter ff_vf_kirsch = { .name = "kirsch", .description = NULL_IF_CONFIG_SMALL("Apply kirsch operator."), .priv_size = sizeof(ConvolutionContext), .priv_class = &common_class, FILTER_INPUTS(convolution_inputs), FILTER_OUTPUTS(ff_video_default_filterpad), FILTER_PIXFMTS_ARRAY(pix_fmts), .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS, .process_command = process_command, }; #endif /* CONFIG_KIRSCH_FILTER */ #if CONFIG_SCHARR_FILTER const AVFilter ff_vf_scharr = { .name = "scharr", .description = NULL_IF_CONFIG_SMALL("Apply scharr operator."), .priv_size = sizeof(ConvolutionContext), .priv_class = &common_class, FILTER_INPUTS(convolution_inputs), FILTER_OUTPUTS(ff_video_default_filterpad), FILTER_PIXFMTS_ARRAY(pix_fmts), .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS, .process_command = process_command, }; #endif /* CONFIG_SCHARR_FILTER */