57 uint8_t *dest_cr,
int mb_x,
int mb_y)
60 int dc, dcu, dcv, y, i;
61 for (i = 0; i < 4; i++) {
62 dc = s->
dc_val[0][mb_x * 2 + (i & 1) + (mb_y * 2 + (i >> 1)) * s->
b8_stride];
67 for (y = 0; y < 8; y++) {
69 for (x = 0; x < 8; x++)
70 dest_y[x + (i & 1) * 8 + (y + (i >> 1) * 8) * linesize[0]] = dc / 8;
83 for (y = 0; y < 8; y++) {
85 for (x = 0; x < 8; x++) {
86 dest_cb[x + y * linesize[1]] = dcu / 8;
87 dest_cr[x + y * linesize[2]] = dcv / 8;
97 for (y = 1; y < height - 1; y++) {
98 int prev_dc = data[0 + y *
stride];
100 for (x = 1; x < width - 1; x++) {
103 data[x + y *
stride] * 8 -
105 dc = (dc * 10923 + 32768) >> 16;
106 prev_dc = data[x + y *
stride];
107 data[x + y *
stride] = dc;
112 for (x = 1; x < width - 1; x++) {
113 int prev_dc = data[x];
115 for (y = 1; y < height - 1; y++) {
119 data[x + y *
stride] * 8 -
120 data[x + (y + 1) * stride];
121 dc = (dc * 10923 + 32768) >> 16;
122 prev_dc = data[x + y *
stride];
123 data[x + y *
stride] = dc;
134 int h,
int stride,
int is_luma)
138 for (b_y = 0; b_y < h; b_y++) {
139 for (b_x = 0; b_x < w; b_x++) {
140 int color[4] = { 1024, 1024, 1024, 1024 };
141 int distance[4] = { 9999, 9999, 9999, 9999 };
142 int mb_index, error, j;
143 int64_t guess, weight_sum;
144 mb_index = (b_x >> is_luma) + (b_y >> is_luma) * s->
mb_stride;
153 for (j = b_x + 1; j < w; j++) {
154 int mb_index_j = (j >> is_luma) + (b_y >> is_luma) * s->
mb_stride;
157 if (intra_j == 0 || !(error_j & ER_DC_ERROR)) {
158 color[0] = dc[j + b_y *
stride];
159 distance[0] = j - b_x;
165 for (j = b_x - 1; j >= 0; j--) {
166 int mb_index_j = (j >> is_luma) + (b_y >> is_luma) * s->
mb_stride;
169 if (intra_j == 0 || !(error_j & ER_DC_ERROR)) {
170 color[1] = dc[j + b_y *
stride];
171 distance[1] = b_x - j;
177 for (j = b_y + 1; j < h; j++) {
178 int mb_index_j = (b_x >> is_luma) + (j >> is_luma) * s->
mb_stride;
182 if (intra_j == 0 || !(error_j & ER_DC_ERROR)) {
183 color[2] = dc[b_x + j *
stride];
184 distance[2] = j - b_y;
190 for (j = b_y - 1; j >= 0; j--) {
191 int mb_index_j = (b_x >> is_luma) + (j >> is_luma) * s->
mb_stride;
194 if (intra_j == 0 || !(error_j & ER_DC_ERROR)) {
195 color[3] = dc[b_x + j *
stride];
196 distance[3] = b_y - j;
203 for (j = 0; j < 4; j++) {
204 int64_t weight = 256 * 256 * 256 * 16 / distance[j];
205 guess += weight * (int64_t) color[j];
206 weight_sum += weight;
208 guess = (guess + weight_sum / 2) / weight_sum;
209 dc[b_x + b_y *
stride] = guess;
220 int h,
int stride,
int is_luma)
222 int b_x, b_y, mvx_stride, mvy_stride;
225 mvx_stride >>= is_luma;
226 mvy_stride *= mvx_stride;
228 for (b_y = 0; b_y < h; b_y++) {
229 for (b_x = 0; b_x < w - 1; b_x++) {
237 int offset = b_x * 8 + b_y * stride * 8;
239 int16_t *right_mv = s->
cur_pic->
f.
motion_val[0][mvy_stride * b_y + mvx_stride * (b_x + 1)];
240 if (!(left_damage || right_damage))
242 if ((!left_intra) && (!right_intra) &&
243 FFABS(left_mv[0] - right_mv[0]) +
244 FFABS(left_mv[1] + right_mv[1]) < 2)
247 for (y = 0; y < 8; y++) {
250 a = dst[offset + 7 + y *
stride] - dst[offset + 6 + y *
stride];
251 b = dst[offset + 8 + y *
stride] - dst[offset + 7 + y *
stride];
252 c = dst[offset + 9 + y *
stride] - dst[offset + 8 + y *
stride];
262 if (!(left_damage && right_damage))
266 dst[offset + 7 + y *
stride] = cm[dst[offset + 7 + y *
stride] + ((d * 7) >> 4)];
267 dst[offset + 6 + y *
stride] = cm[dst[offset + 6 + y *
stride] + ((d * 5) >> 4)];
268 dst[offset + 5 + y *
stride] = cm[dst[offset + 5 + y *
stride] + ((d * 3) >> 4)];
269 dst[offset + 4 + y *
stride] = cm[dst[offset + 4 + y *
stride] + ((d * 1) >> 4)];
272 dst[offset + 8 + y *
stride] = cm[dst[offset + 8 + y *
stride] - ((d * 7) >> 4)];
273 dst[offset + 9 + y *
stride] = cm[dst[offset + 9 + y *
stride] - ((d * 5) >> 4)];
274 dst[offset + 10+ y *
stride] = cm[dst[offset + 10 + y *
stride] - ((d * 3) >> 4)];
275 dst[offset + 11+ y *
stride] = cm[dst[offset + 11 + y *
stride] - ((d * 1) >> 4)];
290 int b_x, b_y, mvx_stride, mvy_stride;
293 mvx_stride >>= is_luma;
294 mvy_stride *= mvx_stride;
296 for (b_y = 0; b_y < h - 1; b_y++) {
297 for (b_x = 0; b_x < w; b_x++) {
305 int offset = b_x * 8 + b_y * stride * 8;
308 int16_t *bottom_mv = s->
cur_pic->
f.
motion_val[0][mvy_stride * (b_y + 1) + mvx_stride * b_x];
310 if (!(top_damage || bottom_damage))
313 if ((!top_intra) && (!bottom_intra) &&
314 FFABS(top_mv[0] - bottom_mv[0]) +
315 FFABS(top_mv[1] + bottom_mv[1]) < 2)
318 for (x = 0; x < 8; x++) {
321 a = dst[offset + x + 7 *
stride] - dst[offset + x + 6 *
stride];
322 b = dst[offset + x + 8 *
stride] - dst[offset + x + 7 *
stride];
323 c = dst[offset + x + 9 *
stride] - dst[offset + x + 8 *
stride];
333 if (!(top_damage && bottom_damage))
337 dst[offset + x + 7 *
stride] = cm[dst[offset + x + 7 *
stride] + ((d * 7) >> 4)];
338 dst[offset + x + 6 *
stride] = cm[dst[offset + x + 6 *
stride] + ((d * 5) >> 4)];
339 dst[offset + x + 5 *
stride] = cm[dst[offset + x + 5 *
stride] + ((d * 3) >> 4)];
340 dst[offset + x + 4 *
stride] = cm[dst[offset + x + 4 *
stride] + ((d * 1) >> 4)];
343 dst[offset + x + 8 *
stride] = cm[dst[offset + x + 8 *
stride] - ((d * 7) >> 4)];
344 dst[offset + x + 9 *
stride] = cm[dst[offset + x + 9 *
stride] - ((d * 5) >> 4)];
345 dst[offset + x + 10 *
stride] = cm[dst[offset + x + 10 *
stride] - ((d * 3) >> 4)];
346 dst[offset + x + 11 *
stride] = cm[dst[offset + x + 11 *
stride] - ((d * 1) >> 4)];
358 #define MV_UNCHANGED 1
362 int i, depth, num_avail;
363 int mb_x, mb_y, mot_step, mot_stride;
368 for (i = 0; i < s->
mb_num; i++) {
384 num_avail <= mb_width / 2) {
385 for (mb_y = 0; mb_y < s->
mb_height; mb_y++) {
386 for (mb_x = 0; mb_x < s->
mb_width; mb_x++) {
387 const int mb_xy = mb_x + mb_y * s->
mb_stride;
404 for (depth = 0; ; depth++) {
405 int changed,
pass, none_left;
409 for (pass = 0; (changed || pass < 2) && pass < 10; pass++) {
414 for (mb_y = 0; mb_y < s->
mb_height; mb_y++) {
415 for (mb_x = 0; mb_x < s->
mb_width; mb_x++) {
416 const int mb_xy = mb_x + mb_y * s->
mb_stride;
417 int mv_predictor[8][2] = { { 0 } };
421 int best_score = 256 * 256 * 256 * 64;
423 const int mot_index = (mb_x + mb_y * mot_stride) * mot_step;
424 int prev_x, prev_y, prev_ref;
426 if ((mb_x ^ mb_y ^ pass) & 1)
435 if (mb_x > 0 && fixed[mb_xy - 1] ==
MV_FROZEN)
437 if (mb_x + 1 < mb_width && fixed[mb_xy + 1] ==
MV_FROZEN)
439 if (mb_y > 0 && fixed[mb_xy - mb_stride] ==
MV_FROZEN)
441 if (mb_y + 1 < mb_height && fixed[mb_xy + mb_stride] ==
MV_FROZEN)
447 if (mb_x > 0 && fixed[mb_xy - 1 ] ==
MV_CHANGED)
449 if (mb_x + 1 < mb_width && fixed[mb_xy + 1 ] ==
MV_CHANGED)
451 if (mb_y > 0 && fixed[mb_xy - mb_stride] ==
MV_CHANGED)
453 if (mb_y + 1 < mb_height && fixed[mb_xy + mb_stride] ==
MV_CHANGED)
455 if (j == 0 && pass > 1)
460 if (mb_x > 0 && fixed[mb_xy - 1]) {
461 mv_predictor[pred_count][0] =
463 mv_predictor[pred_count][1] =
469 if (mb_x + 1 < mb_width && fixed[mb_xy + 1]) {
470 mv_predictor[pred_count][0] =
472 mv_predictor[pred_count][1] =
478 if (mb_y > 0 && fixed[mb_xy - mb_stride]) {
479 mv_predictor[pred_count][0] =
481 mv_predictor[pred_count][1] =
487 if (mb_y + 1<mb_height && fixed[mb_xy + mb_stride]) {
488 mv_predictor[pred_count][0] =
490 mv_predictor[pred_count][1] =
499 if (pred_count > 1) {
500 int sum_x = 0, sum_y = 0, sum_r = 0;
501 int max_x, max_y, min_x, min_y, max_r, min_r;
503 for (j = 0; j < pred_count; j++) {
504 sum_x += mv_predictor[j][0];
505 sum_y += mv_predictor[j][1];
507 if (j && ref[j] != ref[j - 1])
508 goto skip_mean_and_median;
512 mv_predictor[pred_count][0] = sum_x / j;
513 mv_predictor[pred_count][1] = sum_y / j;
514 ref[pred_count] = sum_r / j;
517 if (pred_count >= 3) {
518 min_y = min_x = min_r = 99999;
519 max_y = max_x = max_r = -99999;
521 min_x = min_y = max_x = max_y = min_r = max_r = 0;
523 for (j = 0; j < pred_count; j++) {
524 max_x =
FFMAX(max_x, mv_predictor[j][0]);
525 max_y =
FFMAX(max_y, mv_predictor[j][1]);
526 max_r =
FFMAX(max_r, ref[j]);
527 min_x =
FFMIN(min_x, mv_predictor[j][0]);
528 min_y =
FFMIN(min_y, mv_predictor[j][1]);
529 min_r =
FFMIN(min_r, ref[j]);
531 mv_predictor[pred_count + 1][0] = sum_x - max_x - min_x;
532 mv_predictor[pred_count + 1][1] = sum_y - max_y - min_y;
533 ref[pred_count + 1] = sum_r - max_r - min_r;
535 if (pred_count == 4) {
536 mv_predictor[pred_count + 1][0] /= 2;
537 mv_predictor[pred_count + 1][1] /= 2;
538 ref[pred_count + 1] /= 2;
543 skip_mean_and_median:
567 mv_predictor[pred_count][0] = prev_x;
568 mv_predictor[pred_count][1] = prev_y;
569 ref[pred_count] = prev_ref;
574 for (j = 0; j < pred_count; j++) {
578 mb_x * 16 + mb_y * 16 * linesize[0];
581 s->
mv[0][0][0] = mv_predictor[j][0];
583 s->
mv[0][0][1] = mv_predictor[j][1];
592 if (mb_x > 0 && fixed[mb_xy - 1]) {
594 for (k = 0; k < 16; k++)
595 score +=
FFABS(src[k * linesize[0] - 1] -
596 src[k * linesize[0]]);
598 if (mb_x + 1 < mb_width && fixed[mb_xy + 1]) {
600 for (k = 0; k < 16; k++)
601 score +=
FFABS(src[k * linesize[0] + 15] -
602 src[k * linesize[0] + 16]);
604 if (mb_y > 0 && fixed[mb_xy - mb_stride]) {
606 for (k = 0; k < 16; k++)
607 score +=
FFABS(src[k - linesize[0]] - src[k]);
609 if (mb_y + 1 < mb_height && fixed[mb_xy + mb_stride]) {
611 for (k = 0; k < 16; k++)
612 score +=
FFABS(src[k + linesize[0] * 15] -
613 src[k + linesize[0] * 16]);
616 if (score <= best_score) {
621 score_sum += best_score;
622 s->
mv[0][0][0] = mv_predictor[best_pred][0];
623 s->
mv[0][0][1] = mv_predictor[best_pred][1];
625 for (i = 0; i < mot_step; i++)
626 for (j = 0; j < mot_step; j++) {
635 if (s->
mv[0][0][0] != prev_x || s->
mv[0][0][1] != prev_y) {
647 for (i = 0; i < s->
mb_num; i++) {
657 int is_intra_likely, i, j, undamaged_count, skip_amount, mb_x, mb_y;
663 for (i = 0; i < s->
mb_num; i++) {
673 if (undamaged_count < 5)
682 skip_amount =
FFMAX(undamaged_count / 50, 1);
686 for (mb_y = 0; mb_y < s->
mb_height - 1; mb_y++) {
687 for (mb_x = 0; mb_x < s->
mb_width; mb_x++) {
689 const int mb_xy = mb_x + mb_y * s->
mb_stride;
697 if ((j % skip_amount) != 0)
703 mb_x * 16 + mb_y * 16 * linesize[0];
705 mb_x * 16 + mb_y * 16 * linesize[0];
712 is_intra_likely += s->
dsp->
sad[0](
NULL, last_mb_ptr, mb_ptr,
714 is_intra_likely -= s->
dsp->
sad[0](
NULL, last_mb_ptr,
715 last_mb_ptr + linesize[0] * 16,
725 return is_intra_likely > 0;
747 int endx,
int endy,
int status)
749 const int start_i = av_clip(startx + starty * s->
mb_width, 0, s->
mb_num - 1);
750 const int end_i = av_clip(endx + endy * s->
mb_width, 0, s->
mb_num);
758 if (start_i > end_i || start_xy > end_xy) {
760 "internal error, slice end before start\n");
788 (end_xy - start_xy) *
sizeof(
uint8_t));
791 for (i = start_xy; i < end_xy; i++)
817 int i, mb_x, mb_y, error, error_type, dc_error, mv_error, ac_error;
819 int threshold_part[4] = { 100, 100, 100 };
838 for (i = 0; i < 2; i++) {
847 for (mb_y = 0; mb_y < s->
mb_height; mb_y++) {
848 for (mb_x = 0; mb_x < s->
mb_width; mb_x++) {
858 for (error_type = 1; error_type <= 3; error_type++) {
861 for (i = s->
mb_num - 1; i >= 0; i--) {
865 if (error & (1 << error_type))
867 if (error & (8 << error_type))
882 for (i = s->
mb_num - 1; i >= 0; i--) {
929 for (error_type = 1; error_type <= 3; error_type++) {
930 for (i = s->
mb_num - 1; i >= 0; i--) {
936 if (error & (1 << error_type))
940 if (distance < threshold_part[error_type - 1])
943 if (distance < threshold)
954 for (i = 0; i < s->
mb_num; i++) {
968 for (i = 0; i < s->
mb_num; i++) {
977 dc_error = ac_error = mv_error = 0;
978 for (i = 0; i < s->
mb_num; i++) {
989 dc_error, ac_error, mv_error);
994 for (i = 0; i < s->
mb_num; i++) {
1000 if (is_intra_likely)
1009 for (i = 0; i < s->
mb_num; i++) {
1016 for (mb_y = 0; mb_y < s->
mb_height; mb_y++) {
1017 for (mb_x = 0; mb_x < s->
mb_width; mb_x++) {
1018 const int mb_xy = mb_x + mb_y * s->
mb_stride;
1034 int mb_index = mb_x * 2 + mb_y * 2 * s->
b8_stride;
1037 for (j = 0; j < 4; j++) {
1048 mv_dir, mv_type, &s->
mv, mb_x, mb_y, 0, 0);
1054 for (mb_y = 0; mb_y < s->
mb_height; mb_y++) {
1055 for (mb_x = 0; mb_x < s->
mb_width; mb_x++) {
1056 int xy = mb_x * 2 + mb_y * 2 * s->
b8_stride;
1057 const int mb_xy = mb_x + mb_y * s->
mb_stride;
1106 for (mb_y = 0; mb_y < s->
mb_height; mb_y++) {
1107 for (mb_x = 0; mb_x < s->
mb_width; mb_x++) {
1108 int dc, dcu, dcv, y, n;
1110 uint8_t *dest_y, *dest_cb, *dest_cr;
1111 const int mb_xy = mb_x + mb_y * s->
mb_stride;
1121 dest_y = s->
cur_pic->
f.
data[0] + mb_x * 16 + mb_y * 16 * linesize[0];
1122 dest_cb = s->
cur_pic->
f.
data[1] + mb_x * 8 + mb_y * 8 * linesize[1];
1123 dest_cr = s->
cur_pic->
f.
data[2] + mb_x * 8 + mb_y * 8 * linesize[2];
1126 for (n = 0; n < 4; n++) {
1128 for (y = 0; y < 8; y++) {
1130 for (x = 0; x < 8; x++)
1131 dc += dest_y[x + (n & 1) * 8 +
1132 (y + (n >> 1) * 8) * linesize[0]];
1134 dc_ptr[(n & 1) + (n >> 1) * s->
b8_stride] = (dc + 4) >> 3;
1138 for (y = 0; y < 8; y++) {
1140 for (x = 0; x < 8; x++) {
1141 dcu += dest_cb[x + y * linesize[1]];
1142 dcv += dest_cr[x + y * linesize[2]];
1159 for (mb_y = 0; mb_y < s->
mb_height; mb_y++) {
1160 for (mb_x = 0; mb_x < s->
mb_width; mb_x++) {
1161 uint8_t *dest_y, *dest_cb, *dest_cr;
1162 const int mb_xy = mb_x + mb_y * s->
mb_stride;
1172 dest_y = s->
cur_pic->
f.
data[0] + mb_x * 16 + mb_y * 16 * linesize[0];
1173 dest_cb = s->
cur_pic->
f.
data[1] + mb_x * 8 + mb_y * 8 * linesize[1];
1174 dest_cr = s->
cur_pic->
f.
data[2] + mb_x * 8 + mb_y * 8 * linesize[2];
1176 put_dc(s, dest_y, dest_cb, dest_cr, mb_x, mb_y);
1200 for (i = 0; i < s->
mb_num; i++) {
const struct AVCodec * codec
static void put_dc(ERContext *s, uint8_t *dest_y, uint8_t *dest_cb, uint8_t *dest_cr, int mb_x, int mb_y)
Replace the current MB with a flat dc-only version.
void ff_er_frame_end(ERContext *s)
static void v_block_filter(ERContext *s, uint8_t *dst, int w, int h, int stride, int is_luma)
simple vertical deblocking filter used for error resilience
static void filter181(int16_t *data, int width, int height, int stride)
#define CODEC_CAP_HWACCEL_VDPAU
int16_t(*[2] motion_val_base)[2]
#define VP_START
< current MB is the first after a resync marker
int field_picture
whether or not the picture was encoded in separate fields
static void guess_mv(ERContext *s)
struct AVHWAccel * hwaccel
Hardware accelerator in use.
uint8_t motion_subsample_log2
log2 of the size of the block which a single vector in motion_val represents: (4->16x16, 3->8x8, 2-> 4x4, 1-> 2x2)
static void guess_dc(ERContext *s, int16_t *dc, int w, int h, int stride, int is_luma)
guess the dc of blocks which do not have an undamaged dc
void ff_er_add_slice(ERContext *s, int startx, int starty, int endx, int endy, int status)
Add a slice.
Multithreading support functions.
static const uint16_t mask[17]
int error_concealment
error concealment flags
int capabilities
Codec capabilities.
void(* decode_mb)(void *opaque, int ref, int mv_dir, int mv_type, int(*mv)[2][4][2], int mb_x, int mb_y, int mb_intra, int mb_skipped)
struct Picture * next_pic
void av_log(void *avcl, int level, const char *fmt,...)
static float distance(float x, float y, int band)
uint8_t * error_status_table
useful rectangle filling function
enum AVPictureType pict_type
Picture type of the frame, see ?_TYPE below.
struct Picture * last_pic
int err_recognition
Error recognition; may misdetect some more or less valid parts as errors.
int skip_top
Number of macroblock rows at the top which are skipped.
int thread_count
thread count is used to decide how many independent tasks should be passed to execute() ...
int xvmc_acceleration
XVideo Motion Acceleration.
uint32_t * mb_type
macroblock type table mb_type_base + mb_width + 2
#define MV_TYPE_16X16
1 vector for the whole mb
void ff_thread_await_progress(AVFrame *f, int n, int field)
Wait for earlier decoding threads to finish reference pictures.
int linesize[AV_NUM_DATA_POINTERS]
Size, in bytes, of the data for each picture/channel plane.
int16_t(*[2] motion_val)[2]
motion vector table
int8_t * ref_index[2]
motion reference frame index the order in which these are stored can depend on the codec...
int skip_bottom
Number of macroblock rows at the bottom which are skipped.
uint8_t * data[AV_NUM_DATA_POINTERS]
pointer to the picture/channel planes.
static const uint8_t color[]
static int is_intra_more_likely(ERContext *s)
void ff_er_frame_start(ERContext *s)
static void h_block_filter(ERContext *s, uint8_t *dst, int w, int h, int stride, int is_luma)
simple horizontal deblocking filter used for error resilience
#define MV_TYPE_8X8
4 vectors (h263, mpeg4 4MV)
#define CONFIG_MPEG_XVMC_DECODER
void * av_mallocz(size_t size)
Allocate a block of size bytes with alignment suitable for all memory accesses (including vectors if ...
static void set_mv_strides(ERContext *s, int *mv_step, int *stride)
if(!(ptr_align%ac->ptr_align)&&samples_align >=aligned_len)