#include "libavutil/opt.h"
#include "libavutil/pixdesc.h"
#include "avfilter.h"
+#include "convolution.h"
#include "formats.h"
#include "internal.h"
#include "video.h"
-enum MatrixMode {
- MATRIX_SQUARE,
- MATRIX_ROW,
- MATRIX_COLUMN,
- MATRIX_NBMODES,
-};
-
-typedef struct ConvolutionContext {
- const AVClass *class;
-
- char *matrix_str[4];
- float rdiv[4];
- float bias[4];
- int mode[4];
- float scale;
- float delta;
- int planes;
-
- int size[4];
- int depth;
- int max;
- int bpc;
- int nb_planes;
- int nb_threads;
- int planewidth[4];
- int planeheight[4];
- int matrix[4][49];
- int matrix_length[4];
- int copy[4];
-
- void (*setup[4])(int radius, const uint8_t *c[], const uint8_t *src, int stride,
- int x, int width, int y, int height, int bpc);
- void (*filter[4])(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);
-} ConvolutionContext;
-
#define OFFSET(x) offsetof(ConvolutionContext, x)
-#define FLAGS AV_OPT_FLAG_VIDEO_PARAM|AV_OPT_FLAG_FILTERING_PARAM
+#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 },
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,
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 dstride, int stride, int size)
{
uint16_t *dst = (uint16_t *)dstp;
int x;
for (x = 0; x < width; x++) {
- int 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;
- int 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;
+ 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 dstride, int stride, int size)
{
uint16_t *dst = (uint16_t *)dstp;
int x;
for (x = 0; x < width; x++) {
- int suma = AV_RN16A(&c[0][2 * x]) * 1 + AV_RN16A(&c[1][2 * x]) * -1;
- int sumb = AV_RN16A(&c[4][2 * x]) * 1 + AV_RN16A(&c[3][2 * x]) * -1;
+ 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_sobel(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 dstride, int stride, int size)
{
uint16_t *dst = (uint16_t *)dstp;
int x;
for (x = 0; x < width; x++) {
- int suma = AV_RN16A(&c[0][2 * x]) * -1 + AV_RN16A(&c[1][2 * x]) * -2 + AV_RN16A(&c[2][2 * x]) * -1 +
- AV_RN16A(&c[6][2 * x]) * 1 + AV_RN16A(&c[7][2 * x]) * 2 + AV_RN16A(&c[8][2 * x]) * 1;
- int sumb = AV_RN16A(&c[0][2 * x]) * -1 + AV_RN16A(&c[2][2 * x]) * 1 + AV_RN16A(&c[3][2 * x]) * -2 +
- AV_RN16A(&c[5][2 * x]) * 2 + AV_RN16A(&c[6][2 * x]) * -1 + AV_RN16A(&c[8][2 * x]) * 1;
+ float suma = AV_RN16A(&c[0][2 * x]) * -1 + AV_RN16A(&c[1][2 * x]) * -2 + AV_RN16A(&c[2][2 * x]) * -1 +
+ AV_RN16A(&c[6][2 * x]) * 1 + AV_RN16A(&c[7][2 * x]) * 2 + 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]) * -2 +
+ AV_RN16A(&c[5][2 * x]) * 2 + 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_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 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];
int x;
for (x = 0; x < width; x++) {
- int suma = c0[x] * -1 + c1[x] * -1 + c2[x] * -1 +
- c6[x] * 1 + c7[x] * 1 + c8[x] * 1;
- int sumb = c0[x] * -1 + c2[x] * 1 + c3[x] * -1 +
- c5[x] * 1 + c6[x] * -1 + c8[x] * 1;
+ 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 dstride, int stride, int size)
{
int x;
for (x = 0; x < width; x++) {
- int suma = c[0][x] * 1 + c[1][x] * -1;
- int sumb = c[4][x] * 1 + c[3][x] * -1;
+ 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_sobel(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 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];
int x;
for (x = 0; x < width; x++) {
- int suma = c0[x] * -1 + c1[x] * -2 + c2[x] * -1 +
- c6[x] * 1 + c7[x] * 2 + c8[x] * 1;
- int sumb = c0[x] * -1 + c2[x] * 1 + c3[x] * -2 +
- c5[x] * 2 + c6[x] * -1 + c8[x] * 1;
+ float suma = c0[x] * -1 + c1[x] * -2 + c2[x] * -1 +
+ c6[x] * 1 + c7[x] * 2 + c8[x] * 1;
+ float sumb = c0[x] * -1 + c2[x] * 1 + c3[x] * -2 +
+ c5[x] * 2 + c6[x] * -1 + c8[x] * 1;
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 dstride, int stride, int size)
{
uint16_t *dst = (uint16_t *)dstp;
int x;
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 dstride, int stride, int size)
{
uint16_t *dst = (uint16_t *)dstp;
int x;
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 dstride, int stride, int size)
{
uint16_t *dst = (uint16_t *)dstp;
int x;
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 dstride, int stride, int size)
{
uint16_t *dst = (uint16_t *)dstp;
int x;
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 dstride, int stride, int size)
{
+ DECLARE_ALIGNED(64, int, sum)[16];
uint16_t *dst = (uint16_t *)dstp;
- int y;
+ const int width = FFMIN(16, size);
- for (y = 0; y < height; y++) {
- int i, sum = 0;
+ for (int y = 0; y < height; y++) {
- for (i = 0; i < 2 * radius + 1; i++)
- sum += AV_RN16A(&c[i][0 + y * stride]) * matrix[i];
+ 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];
+ }
- sum = (int)(sum * rdiv + bias + 0.5f);
- dst[0] = av_clip(sum, 0, peak);
+ 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 dstride, int stride, int size)
{
int x;
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 dstride, int stride, int size)
{
int x;
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 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];
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 dstride, int stride, int size)
{
int x;
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 dstride, int stride, int size)
{
- int y;
+ DECLARE_ALIGNED(64, int, sum)[16];
- for (y = 0; y < height; y++) {
- int i, sum = 0;
+ for (int y = 0; y < height; y++) {
+ memset(sum, 0, sizeof(sum));
- for (i = 0; i < 2 * radius + 1; i++)
- sum += c[i][0 + y * stride] * matrix[i];
+ 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];
+ }
- sum = (int)(sum * rdiv + bias + 0.5f);
- dst[0] = av_clip_uint8(sum);
+ 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;
}
}
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;
width * bpc, slice_end - slice_start);
continue;
}
-
- for (y = slice_start; y < slice_end; y++) {
+ 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 * stride : 0;
+ 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 * stride : 0;
+ 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);
+ 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);
+ 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 * stride : 0;
+ 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);
+ dstride, stride, slice_end - step);
}
if (mode != MATRIX_COLUMN)
dst += dstride;
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++)
if (s->depth > 8)
for (p = 0; p < s->nb_planes; p++)
s->filter[p] = filter16_sobel;
+ } else if (!strcmp(ctx->filter->name, "kirsch")) {
+ if (s->depth > 8)
+ for (p = 0; p < s->nb_planes; p++)
+ s->filter[p] = filter16_kirsch;
}
return 0;
float sum = 0;
p = s->matrix_str[i];
- 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]++;
+ if (p) {
+ s->matrix_length[i] = 0;
+
+ 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]++;
+ }
+
+ 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->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->matrix_length[i] == 9) {
s->size[i] = 3;
- if (!memcmp(matrix, same3x3, sizeof(same3x3)))
+
+ if (!memcmp(matrix, same3x3, sizeof(same3x3))) {
s->copy[i] = 1;
- else
+ } 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)))
+ if (!memcmp(matrix, same5x5, sizeof(same5x5))) {
s->copy[i] = 1;
- else
+ } 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)))
+ if (!memcmp(matrix, same7x7, sizeof(same7x7))) {
s->copy[i] = 1;
- else
+ } else {
s->filter[i] = filter_7x7;
+ s->copy[i] = 0;
+ }
s->setup[i] = setup_7x7;
} else {
return AVERROR(EINVAL);
s->rdiv[i] = s->scale;
s->bias[i] = s->delta;
}
+ } else if (!strcmp(ctx->filter->name, "kirsch")) {
+ for (i = 0; i < 4; i++) {
+ if ((1 << i) & s->planes)
+ s->filter[i] = filter_kirsch;
+ else
+ s->copy[i] = 1;
+ s->size[i] = 3;
+ s->setup[i] = setup_3x3;
+ s->rdiv[i] = s->scale;
+ s->bias[i] = s->delta;
+ }
}
return 0;
}
+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 init(ctx);
+}
+
static const AVFilterPad convolution_inputs[] = {
{
.name = "default",
#if CONFIG_CONVOLUTION_FILTER
-AVFilter ff_vf_convolution = {
+const AVFilter ff_vf_convolution = {
.name = "convolution",
.description = NULL_IF_CONFIG_SMALL("Apply convolution filter."),
.priv_size = sizeof(ConvolutionContext),
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
+ .process_command = process_command,
};
#endif /* CONFIG_CONVOLUTION_FILTER */
-#if CONFIG_PREWITT_FILTER
+#if CONFIG_PREWITT_FILTER || CONFIG_ROBERTS_FILTER || CONFIG_SOBEL_FILTER
-static const AVOption prewitt_options[] = {
+static const AVOption prewitt_roberts_sobel_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 }
};
+#if CONFIG_PREWITT_FILTER
+
+#define prewitt_options prewitt_roberts_sobel_options
AVFILTER_DEFINE_CLASS(prewitt);
-AVFilter ff_vf_prewitt = {
+const AVFilter ff_vf_prewitt = {
.name = "prewitt",
.description = NULL_IF_CONFIG_SMALL("Apply prewitt operator."),
.priv_size = sizeof(ConvolutionContext),
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
+ .process_command = process_command,
};
#endif /* CONFIG_PREWITT_FILTER */
#if CONFIG_SOBEL_FILTER
-static const AVOption sobel_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 }
-};
-
+#define sobel_options prewitt_roberts_sobel_options
AVFILTER_DEFINE_CLASS(sobel);
-AVFilter ff_vf_sobel = {
+const AVFilter ff_vf_sobel = {
.name = "sobel",
.description = NULL_IF_CONFIG_SMALL("Apply sobel operator."),
.priv_size = sizeof(ConvolutionContext),
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
+ .process_command = process_command,
};
#endif /* CONFIG_SOBEL_FILTER */
#if CONFIG_ROBERTS_FILTER
-static const AVOption roberts_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 }
-};
-
+#define roberts_options prewitt_roberts_sobel_options
AVFILTER_DEFINE_CLASS(roberts);
-AVFilter ff_vf_roberts = {
+const AVFilter ff_vf_roberts = {
.name = "roberts",
.description = NULL_IF_CONFIG_SMALL("Apply roberts cross operator."),
.priv_size = sizeof(ConvolutionContext),
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
+ .process_command = process_command,
};
#endif /* CONFIG_ROBERTS_FILTER */
+
+#if CONFIG_KIRSCH_FILTER
+
+#define kirsch_options prewitt_roberts_sobel_options
+AVFILTER_DEFINE_CLASS(kirsch);
+
+const AVFilter ff_vf_kirsch = {
+ .name = "kirsch",
+ .description = NULL_IF_CONFIG_SMALL("Apply kirsch operator."),
+ .priv_size = sizeof(ConvolutionContext),
+ .priv_class = &kirsch_class,
+ .init = init,
+ .query_formats = query_formats,
+ .inputs = convolution_inputs,
+ .outputs = convolution_outputs,
+ .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
+ .process_command = process_command,
+};
+
+#endif /* CONFIG_KIRSCH_FILTER */
+
+#endif /* CONFIG_PREWITT_FILTER || CONFIG_ROBERTS_FILTER || CONFIG_SOBEL_FILTER */
projects / ffmpeg / blobdiff