This is a significant rewrite.
[melted] / src / modules / motion_est / filter_motion_est.c
1 /*
2 * /brief fast motion estimation filter
3 * /author Zachary Drew, Copyright 2005
4 *
5 * Currently only uses Gamma data for comparisonon (bug or feature?)
6 * Vector optimization coming soon.
7 *
8 * Vector orientation: The vector data that is generated for the current frame specifies
9 * the motion from the previous frame to the current frame. To know how a macroblock
10 * in the current frame will move in the future, the next frame is needed.
11 *
12 * This program is free software; you can redistribute it and/or modify
13 * it under the terms of the GNU General Public License as published by
14 * the Free Software Foundation; either version 2 of the License, or
15 * (at your option) any later version.
16 *
17 * This program is distributed in the hope that it will be useful,
18 * but WITHOUT ANY WARRANTY; without even the implied warranty of
19 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
20 * GNU General Public License for more details.
21 *
22 * You should have received a copy of the GNU General Public License
23 * along with this program; if not, write to the Free Software Foundation,
24 * Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
25 */
26
27
28 #include "filter_motion_est.h"
29 #include <framework/mlt.h>
30 #include <stdio.h>
31 #include <stdlib.h>
32 #include <math.h>
33 #include <string.h>
34 #include <sys/time.h>
35 #include <unistd.h>
36
37 #include "sad_sse.h"
38
39 #define NDEBUG
40 #include <assert.h>
41
42 #undef DEBUG
43 #undef DEBUG_ASM
44 #undef BENCHMARK
45 #undef COUNT_COMPARES
46
47 #define DIAMOND_SEARCH 0x0
48 #define FULL_SEARCH 0x1
49 #define SHIFT 8
50 #define MIN(a,b) ((a) > (b) ? (b) : (a))
51 #define ABS(a) ((a) >= 0 ? (a) : (-(a)))
52
53
54 typedef struct motion_vector_s motion_vector;
55
56 struct motion_est_context_s
57 {
58 int initialized; // true if filter has been initialized
59
60 #ifdef COUNT_COMPARES
61 int compares;
62 #endif
63
64 /* same as mlt_frame's parameters */
65 int width, height;
66
67 /* Operational details */
68 int mb_w, mb_h;
69 int xstride, ystride;
70 uint8_t *cache_image; // Copy of current frame
71 uint8_t *former_image; // Copy of former frame
72 int search_method;
73 int skip_prediction;
74 int shot_change;
75 int limit_x, limit_y; // max x and y of a motion vector
76 int initial_thresh;
77 int check_chroma; // if check_chroma == 1 then compare chroma
78 int denoise;
79 int previous_msad;
80 int show_reconstruction;
81 int toggle_when_paused;
82 int show_residual;
83
84 /* bounds */
85 struct mlt_geometry_item_s bounds; // Current bounds (from filters crop_detect, autotrack rectangle, or other)
86
87 /* bounds in macroblock units; macroblocks are completely contained within the boundry */
88 int left_mb, prev_left_mb, right_mb, prev_right_mb;
89 int top_mb, prev_top_mb, bottom_mb, prev_bottom_mb;
90
91 /* size of our vector buffers */
92 int mv_buffer_height, mv_buffer_width, mv_size;
93
94 /* vector buffers */
95 int former_vectors_valid; //<! true if the previous frame's buffered motion vector data is valid
96 motion_vector *former_vectors;
97 motion_vector *current_vectors;
98 motion_vector *denoise_vectors;
99 mlt_position former_frame_position, current_frame_position;
100
101 /* diagnostic metrics */
102 float predictive_misses; // How often do the prediction motion vectors fail?
103 int comparison_average; // How far does the best estimation deviate from a perfect comparison?
104 int bad_comparisons;
105 int average_length;
106 int average_x, average_y;
107
108 /* run-time configurable comparison functions */
109 int (*compare_reference)(uint8_t *, uint8_t *, int, int, int, int);
110 int (*compare_optimized)(uint8_t *, uint8_t *, int, int, int, int);
111
112 };
113
114 // This is used to constrains pixel operations between two blocks to be within the image boundry
115 inline static int constrain( int *x, int *y, int *w, int *h,
116 const int dx, const int dy,
117 const int left, const int right,
118 const int top, const int bottom)
119 {
120 uint32_t penalty = 1 << SHIFT; // Retain a few extra bits of precision
121 int x2 = *x + dx;
122 int y2 = *y + dy;
123 int w_remains = *w;
124 int h_remains = *h;
125
126 // Origin of macroblock moves left of image boundy
127 if( *x < left || x2 < left ) {
128 w_remains = *w - left + ((*x < x2) ? *x : x2);
129 *x += *w - w_remains;
130 }
131 // Portion of macroblock moves right of image boundry
132 else if( *x + *w > right || x2 + *w > right )
133 w_remains = right - ((*x > x2) ? *x : x2);
134
135 // Origin of macroblock moves above image boundy
136 if( *y < top || y2 < top ) {
137 h_remains = *h - top + ((*y < y2) ? *y : y2);
138 *y += *h - h_remains;
139 }
140 // Portion of macroblock moves bellow image boundry
141 else if( *y + *h > bottom || y2 + *h > bottom )
142 h_remains = bottom - ((*y > y2) ? *y : y2);
143
144 if( w_remains == *w && h_remains == *h ) return penalty;
145 if( w_remains <= 0 || h_remains <= 0) return 0; // Block is clipped out of existance
146 penalty = (*w * *h * penalty)
147 / ( w_remains * h_remains); // Recipricol of the fraction of the block that remains
148
149 assert(*x >= left); assert(x2 + *w - w_remains >= left);
150 assert(*y >= top); assert(y2 + *h - h_remains >= top);
151 assert(*x + w_remains <= right); assert(x2 + w_remains <= right);
152 assert(*y + h_remains <= bottom); assert(y2 + h_remains <= bottom);
153
154 *w = w_remains; // Update the width and height
155 *h = h_remains;
156
157 return penalty;
158 }
159
160 /** /brief Reference Sum of Absolute Differences comparison function
161 *
162 */
163 inline static int sad_reference( uint8_t *block1, uint8_t *block2, const int xstride, const int ystride, const int w, const int h )
164 {
165 int i, j, score = 0;
166 for ( j = 0; j < h; j++ ){
167 for ( i = 0; i < w; i++ ){
168 score += ABS( block1[i*xstride] - block2[i*xstride] );
169 }
170 block1 += ystride;
171 block2 += ystride;
172 }
173
174 return score;
175 }
176
177
178 /** /brief Abstracted block comparison function
179 */
180 inline static int block_compare( uint8_t *block1,
181 uint8_t *block2,
182 int x,
183 int y,
184 int dx,
185 int dy,
186 struct motion_est_context_s *c)
187 {
188
189 #ifdef COUNT_COMPARES
190 c->compares++;
191 #endif
192
193 int score;
194
195 // Default comparison may be overridden by the slower, more capable reference comparison
196 int (*cmp)(uint8_t *, uint8_t *, int, int, int, int) = c->compare_optimized;
197
198 // vector displacement limited has been exceeded
199 if( ABS( dx ) >= c->limit_x || ABS( dy ) >= c->limit_y )
200 return MAX_MSAD;
201
202 int mb_w = c->mb_w; // Some writeable local copies
203 int mb_h = c->mb_h;
204
205 // Determine if either macroblock got clipped
206 int penalty = constrain( &x, &y, &mb_w, &mb_h, dx, dy, 0, c->width, 0, c->height);
207
208 // Some gotchas
209 if( penalty == 0 ) // Clipped out of existance: Return worst score
210 return MAX_MSAD;
211 else if( penalty != 1<<SHIFT ) // Nonstandard macroblock dimensions: Disable SIMD optimizizations.
212 cmp = c->compare_reference;
213
214 // Calculate the memory locations of the macroblocks
215 block1 += x * c->xstride + y * c->ystride;
216 block2 += (x+dx) * c->xstride + (y+dy) * c->ystride;
217
218 #ifdef DEBUG_ASM
219 if( penalty == 1<<SHIFT ){
220 score = c->compare_reference( block1, block2, c->xstride, c->ystride, mb_w, mb_h );
221 int score2 = c->compare_optimized( block1, block2, c->xstride, c->ystride, mb_w, mb_h );
222 if ( score != score2 )
223 fprintf(stderr, "Your assembly doesn't work! Reference: %d Asm: %d\n", score, score2);
224 }
225 else
226 #endif
227
228 score = cmp( block1, block2, c->xstride, c->ystride, mb_w, mb_h );
229
230 return ( score * penalty ) >> SHIFT; // Ditch the extra precision
231 }
232
233 static inline void check_candidates ( uint8_t *ref,
234 uint8_t *candidate_base,
235 const int x,
236 const int y,
237 const motion_vector *candidates,// Contains to_x & to_y
238 const int count, // Number of candidates
239 const int unique, // Sometimes we know the candidates are unique
240 motion_vector *result,
241 struct motion_est_context_s *c )
242 {
243 int score, i, j;
244 /* Scan for the best candidate */
245 for ( i = 0; i < count; i++ )
246 {
247 // this little dohicky ignores duplicate candidates, if they are possible
248 if ( unique == 0 ) {
249 j = 0;
250 while ( j < i )
251 {
252 if ( candidates[j].dx == candidates[i].dx &&
253 candidates[j].dy == candidates[i].dy )
254 goto next_for_loop;
255
256 j++;
257 }
258 }
259
260 // Luma
261 score = block_compare( ref, candidate_base,
262 x, y,
263 candidates[i].dx, // from
264 candidates[i].dy,
265 c);
266
267 if ( score < result->msad ) { // New minimum
268 result->dx = candidates[i].dx;
269 result->dy = candidates[i].dy;
270 result->msad = score;
271 }
272 next_for_loop:;
273 }
274 }
275
276 /* /brief Diamond search
277 * Operates on a single macroblock
278 */
279 static inline void diamond_search(
280 uint8_t *ref, //<! Image data from previous frame
281 uint8_t *candidate_base, //<! Image data in current frame
282 const int x, //<! X upper left corner of macroblock
283 const int y, //<! U upper left corner of macroblock
284 struct motion_vector_s *result, //<! Best predicted mv and eventual result
285 struct motion_est_context_s *c) //<! motion estimation context
286 {
287
288 // diamond search pattern
289 motion_vector candidates[4];
290
291 // Keep track of best and former best candidates
292 motion_vector best, former;
293
294 // The direction of the refinement needs to be known
295 motion_vector current;
296
297 int i, first = 1;
298
299 // Loop through the search pattern
300 while( 1 ) {
301
302 current.dx = result->dx;
303 current.dy = result->dy;
304
305 if ( first == 1 ) // Set the initial pattern
306 {
307 candidates[0].dx = result->dx + 1; candidates[0].dy = result->dy + 0;
308 candidates[1].dx = result->dx + 0; candidates[1].dy = result->dy + 1;
309 candidates[2].dx = result->dx - 1; candidates[2].dy = result->dy + 0;
310 candidates[3].dx = result->dx + 0; candidates[3].dy = result->dy - 1;
311 i = 4;
312 }
313 else // Construct the next portion of the search pattern
314 {
315 candidates[0].dx = result->dx + best.dx;
316 candidates[0].dy = result->dy + best.dy;
317 if (best.dx == former.dx && best.dy == former.dy) {
318 candidates[1].dx = result->dx + best.dy;
319 candidates[1].dy = result->dy + best.dx; // Yes, the wires
320 candidates[2].dx = result->dx - best.dy; // are crossed
321 candidates[2].dy = result->dy - best.dx;
322 i = 3;
323 } else {
324 candidates[1].dx = result->dx + former.dx;
325 candidates[1].dy = result->dy + former.dy;
326 i = 2;
327 }
328
329 former.dx = best.dx; former.dy = best.dy; // Keep track of new former best
330 }
331
332 check_candidates ( ref, candidate_base, x, y, candidates, i, 1, result, c );
333
334 // Which candidate was the best?
335 best.dx = result->dx - current.dx;
336 best.dy = result->dy - current.dy;
337
338 // A better canidate was not found
339 if ( best.dx == 0 && best.dy == 0 )
340 return;
341
342 if ( first == 1 ){
343 first = 0;
344 former.dx = best.dx; former.dy = best.dy; // First iteration, sensible value for former.d*
345 }
346 }
347 }
348
349 /* /brief Full (brute) search
350 * Operates on a single macroblock
351 */
352 __attribute__((used))
353 static void full_search(
354 uint8_t *ref, //<! Image data from previous frame
355 uint8_t *candidate_base, //<! Image data in current frame
356 int x, //<! X upper left corner of macroblock
357 int y, //<! U upper left corner of macroblock
358 struct motion_vector_s *result, //<! Best predicted mv and eventual result
359 struct motion_est_context_s *c) //<! motion estimation context
360 {
361 // Keep track of best candidate
362 int i,j,score;
363
364 // Go loopy
365 for( i = -c->mb_w; i <= c->mb_w; i++ ){
366 for( j = -c->mb_h; j <= c->mb_h; j++ ){
367
368 score = block_compare( ref, candidate_base,
369 x,
370 y,
371 x + i,
372 y + j,
373 c);
374
375 if ( score < result->msad ) {
376 result->dx = i;
377 result->dy = j;
378 result->msad = score;
379 }
380 }
381 }
382 }
383
384 // Macros for pointer calculations
385 #define CURRENT(i,j) ( c->current_vectors + (j)*c->mv_buffer_width + (i) )
386 #define FORMER(i,j) ( c->former_vectors + (j)*c->mv_buffer_width + (i) )
387 #define DENOISE(i,j) ( c->denoise_vectors + (j)*c->mv_buffer_width + (i) )
388
389 int ncompare (const void * a, const void * b)
390 {
391 return ( *(int*)a - *(int*)b );
392 }
393
394 // motion vector denoising
395 // for x and y components seperately,
396 // change the vector to be the median value of the 9 adjacent vectors
397 static void median_denoise( motion_vector *v, struct motion_est_context_s *c )
398 {
399 int xvalues[9], yvalues[9];
400
401 int i,j,n;
402 for( j = c->top_mb; j <= c->bottom_mb; j++ )
403 for( i = c->left_mb; i <= c->right_mb; i++ ){
404 {
405 n = 0;
406
407 xvalues[n ] = CURRENT(i,j)->dx; // Center
408 yvalues[n++] = CURRENT(i,j)->dy;
409
410 if( i > c->left_mb ) // Not in First Column
411 {
412 xvalues[n ] = CURRENT(i-1,j)->dx; // Left
413 yvalues[n++] = CURRENT(i-1,j)->dy;
414
415 if( j > c->top_mb ) {
416 xvalues[n ] = CURRENT(i-1,j-1)->dx; // Upper Left
417 yvalues[n++] = CURRENT(i-1,j-1)->dy;
418 }
419
420 if( j < c->bottom_mb ) {
421 xvalues[n ] = CURRENT(i-1,j+1)->dx; // Bottom Left
422 yvalues[n++] = CURRENT(i-1,j+1)->dy;
423 }
424 }
425 if( i < c->right_mb ) // Not in Last Column
426 {
427 xvalues[n ] = CURRENT(i+1,j)->dx; // Right
428 yvalues[n++] = CURRENT(i+1,j)->dy;
429
430
431 if( j > c->top_mb ) {
432 xvalues[n ] = CURRENT(i+1,j-1)->dx; // Upper Right
433 yvalues[n++] = CURRENT(i+1,j-1)->dy;
434 }
435
436 if( j < c->bottom_mb ) {
437 xvalues[n ] = CURRENT(i+1,j+1)->dx; // Bottom Right
438 yvalues[n++] = CURRENT(i+1,j+1)->dy;
439 }
440 }
441 if( j > c->top_mb ) // Not in First Row
442 {
443 xvalues[n ] = CURRENT(i,j-1)->dx; // Top
444 yvalues[n++] = CURRENT(i,j-1)->dy;
445 }
446
447 if( j < c->bottom_mb ) // Not in Last Row
448 {
449 xvalues[n ] = CURRENT(i,j+1)->dx; // Bottom
450 yvalues[n++] = CURRENT(i,j+1)->dy;
451 }
452
453 qsort (xvalues, n, sizeof(int), ncompare);
454 qsort (yvalues, n, sizeof(int), ncompare);
455
456 if( n % 2 == 1 ) {
457 DENOISE(i,j)->dx = xvalues[n/2];
458 DENOISE(i,j)->dy = yvalues[n/2];
459 }
460 else {
461 DENOISE(i,j)->dx = (xvalues[n/2] + xvalues[n/2+1])/2;
462 DENOISE(i,j)->dy = (yvalues[n/2] + yvalues[n/2+1])/2;
463 }
464 }
465 }
466
467 motion_vector *t = c->current_vectors;
468 c->current_vectors = c->denoise_vectors;
469 c->denoise_vectors = t;
470
471 }
472
473 // Credits: ffmpeg
474 // return the median
475 static inline int median_predictor(int a, int b, int c) {
476 if ( a > b ){
477 if ( c > b ){
478 if ( c > a ) b = a;
479 else b = c;
480 }
481 } else {
482 if ( b > c ){
483 if ( c > a ) b = c;
484 else b = a;
485 }
486 }
487 return b;
488 }
489
490
491 /** /brief Motion search
492 *
493 * For each macroblock in the current frame, estimate the block from the last frame that
494 * matches best.
495 *
496 * Vocab: Colocated - the pixel in the previous frame at the current position
497 *
498 * Based on enhanced predictive zonal search. [Tourapis 2002]
499 */
500 static void motion_search( uint8_t *from, //<! Image data.
501 uint8_t *to, //<! Image data. Rigid grid.
502 struct motion_est_context_s *c) //<! The context
503 {
504
505 #ifdef COUNT_COMPARES
506 compares = 0;
507 #endif
508
509 motion_vector candidates[10];
510 motion_vector *here; // This one gets used alot (about 30 times per macroblock)
511 int n = 0;
512
513 int i, j, count=0;
514
515 // For every macroblock, perform motion vector estimation
516 for( i = c->left_mb; i <= c->right_mb; i++ ){
517 for( j = c->top_mb; j <= c->bottom_mb; j++ ){
518
519 here = CURRENT(i,j);
520 here->valid = 1;
521 here->color = 100;
522 here->msad = MAX_MSAD;
523 count++;
524 n = 0;
525
526
527 /* Stack the predictors [i.e. checked in reverse order] */
528
529 /* Adjacent to collocated */
530 if( c->former_vectors_valid )
531 {
532 // Top of colocated
533 if( j > c->prev_top_mb ){// && COL_TOP->valid ){
534 candidates[n ].dx = FORMER(i,j-1)->dx;
535 candidates[n++].dy = FORMER(i,j-1)->dy;
536 }
537
538 // Left of colocated
539 if( i > c->prev_left_mb ){// && COL_LEFT->valid ){
540 candidates[n ].dx = FORMER(i-1,j)->dx;
541 candidates[n++].dy = FORMER(i-1,j)->dy;
542 }
543
544 // Right of colocated
545 if( i < c->prev_right_mb ){// && COL_RIGHT->valid ){
546 candidates[n ].dx = FORMER(i+1,j)->dx;
547 candidates[n++].dy = FORMER(i+1,j)->dy;
548 }
549
550 // Bottom of colocated
551 if( j < c->prev_bottom_mb ){// && COL_BOTTOM->valid ){
552 candidates[n ].dx = FORMER(i,j+1)->dx;
553 candidates[n++].dy = FORMER(i,j+1)->dy;
554 }
555
556 // And finally, colocated
557 candidates[n ].dx = FORMER(i,j)->dx;
558 candidates[n++].dy = FORMER(i,j)->dy;
559 }
560
561 // For macroblocks not in the top row
562 if ( j > c->top_mb) {
563
564 // Top if ( TOP->valid ) {
565 candidates[n ].dx = CURRENT(i,j-1)->dx;
566 candidates[n++].dy = CURRENT(i,j-1)->dy;
567 //}
568
569 // Top-Right, macroblocks not in the right row
570 if ( i < c->right_mb ){// && TOP_RIGHT->valid ) {
571 candidates[n ].dx = CURRENT(i+1,j-1)->dx;
572 candidates[n++].dy = CURRENT(i+1,j-1)->dy;
573 }
574 }
575
576 // Left, Macroblocks not in the left column
577 if ( i > c->left_mb ){// && LEFT->valid ) {
578 candidates[n ].dx = CURRENT(i-1,j)->dx;
579 candidates[n++].dy = CURRENT(i-1,j)->dy;
580 }
581
582 /* Median predictor vector (median of left, top, and top right adjacent vectors) */
583 if ( i > c->left_mb && j > c->top_mb && i < c->right_mb
584 )//&& LEFT->valid && TOP->valid && TOP_RIGHT->valid )
585 {
586 candidates[n ].dx = median_predictor( CURRENT(i-1,j)->dx, CURRENT(i,j-1)->dx, CURRENT(i+1,j-1)->dx);
587 candidates[n++].dy = median_predictor( CURRENT(i-1,j)->dy, CURRENT(i,j-1)->dy, CURRENT(i+1,j-1)->dy);
588 }
589
590 // Zero vector
591 candidates[n ].dx = 0;
592 candidates[n++].dy = 0;
593
594 int x = i * c->mb_w;
595 int y = j * c->mb_h;
596 check_candidates ( to, from, x, y, candidates, n, 0, here, c );
597
598
599 #ifndef FULLSEARCH
600 diamond_search( to, from, x, y, here, c);
601 #else
602 full_search( to, from, x, y, here, c);
603 #endif
604
605 assert( x + c->mb_w + here->dx > 0 ); // All macroblocks must have area > 0
606 assert( y + c->mb_h + here->dy > 0 );
607 assert( x + here->dx < c->width );
608 assert( y + here->dy < c->height );
609
610 } /* End column loop */
611 } /* End row loop */
612
613 asm volatile ( "emms" );
614
615 #ifdef COUNT_COMPARES
616 fprintf(stderr, "%d comparisons per block were made", compares/count);
617 #endif
618 return;
619 }
620
621 void collect_post_statistics( struct motion_est_context_s *c ) {
622
623 c->comparison_average = 0;
624 c->average_length = 0;
625 c->average_x = 0;
626 c->average_y = 0;
627
628 int i, j, count = 0;
629
630 for ( i = c->left_mb; i <= c->right_mb; i++ ){
631 for ( j = c->top_mb; j <= c->bottom_mb; j++ ){
632
633 count++;
634 c->comparison_average += CURRENT(i,j)->msad;
635 c->average_x += CURRENT(i,j)->dx;
636 c->average_y += CURRENT(i,j)->dy;
637
638
639 }
640 }
641
642 if ( count > 0 )
643 {
644 c->comparison_average /= count;
645 c->average_x /= count;
646 c->average_y /= count;
647 c->average_length = sqrt( c->average_x * c->average_x + c->average_y * c->average_y );
648 }
649
650 }
651
652 static void init_optimizations( struct motion_est_context_s *c )
653 {
654 switch(c->mb_w){
655 case 4: if(c->mb_h == 4) c->compare_optimized = sad_sse_422_luma_4x4;
656 else c->compare_optimized = sad_sse_422_luma_4w;
657 break;
658 case 8: if(c->mb_h == 8) c->compare_optimized = sad_sse_422_luma_8x8;
659 else c->compare_optimized = sad_sse_422_luma_8w;
660 break;
661 case 16: if(c->mb_h == 16) c->compare_optimized = sad_sse_422_luma_16x16;
662 else c->compare_optimized = sad_sse_422_luma_16w;
663 break;
664 case 32: if(c->mb_h == 32) c->compare_optimized = sad_sse_422_luma_32x32;
665 else c->compare_optimized = sad_sse_422_luma_32w;
666 break;
667 case 64: c->compare_optimized = sad_sse_422_luma_64w;
668 break;
669 default: c->compare_optimized = sad_reference;
670 break;
671 }
672 }
673
674 inline static void set_red(uint8_t *image, struct motion_est_context_s *c)
675 {
676 int n;
677 for( n = 0; n < c->width * c->height * 2; n+=4 )
678 {
679 image[n] = 79;
680 image[n+1] = 91;
681 image[n+2] = 79;
682 image[n+3] = 237;
683 }
684
685 }
686
687 static void show_residual( uint8_t *result, struct motion_est_context_s *c )
688 {
689 int i, j;
690 int x,y,w,h;
691 int dx, dy;
692 int tx,ty;
693 uint8_t *b, *r;
694
695 // set_red(result,c);
696
697 for( j = c->top_mb; j <= c->bottom_mb; j++ ){
698 for( i = c->left_mb; i <= c->right_mb; i++ ){
699
700 dx = CURRENT(i,j)->dx;
701 dy = CURRENT(i,j)->dy;
702 w = c->mb_w;
703 h = c->mb_h;
704 x = i * w;
705 y = j * h;
706
707 // Denoise function caused some blocks to be completely clipped, ignore them
708 if (constrain( &x, &y, &w, &h, dx, dy, 0, c->width, 0, c->height) == 0 )
709 continue;
710
711 for( ty = y; ty < y + h ; ty++ ){
712 for( tx = x; tx < x + w ; tx++ ){
713
714 b = c->former_image + (tx+dx)*c->xstride + (ty+dy)*c->ystride;
715 r = result + tx*c->xstride + ty*c->ystride;
716
717 r[0] = 16 + ABS( r[0] - b[0] );
718
719 if( dx % 2 == 0 )
720 r[1] = 128 + ABS( r[1] - b[1] );
721 else
722 // FIXME: may exceed boundies
723 r[1] = 128 + ABS( r[1] - ( *(b-1) + b[3] ) /2 );
724 }
725 }
726 }
727 }
728 }
729
730 static void show_reconstruction( uint8_t *result, struct motion_est_context_s *c )
731 {
732 int i, j;
733 int x,y,w,h;
734 int dx,dy;
735 uint8_t *r, *s;
736 int tx,ty;
737
738 for( i = c->left_mb; i <= c->right_mb; i++ ){
739 for( j = c->top_mb; j <= c->bottom_mb; j++ ){
740
741 dx = CURRENT(i,j)->dx;
742 dy = CURRENT(i,j)->dy;
743 w = c->mb_w;
744 h = c->mb_h;
745 x = i * w;
746 y = j * h;
747
748 // Denoise function caused some blocks to be completely clipped, ignore them
749 if (constrain( &x, &y, &w, &h, dx, dy, 0, c->width, 0, c->height) == 0 )
750 continue;
751
752 for( ty = y; ty < y + h ; ty++ ){
753 for( tx = x; tx < x + w ; tx++ ){
754
755 r = result + tx*c->xstride + ty*c->ystride;
756 s = c->former_image + (tx+dx)*c->xstride + (ty+dy)*c->ystride;
757
758 r[0] = s[0];
759
760 if( dx % 2 == 0 )
761 r[1] = s[1];
762 else
763 // FIXME: may exceed boundies
764 r[1] = ( *(s-1) + s[3] ) /2;
765 }
766 }
767 }
768 }
769 }
770
771 // Image stack(able) method
772 static int filter_get_image( mlt_frame frame, uint8_t **image, mlt_image_format *format, int *width, int *height, int writable )
773 {
774 // Get the filter
775 mlt_filter filter = mlt_frame_pop_service( frame );
776
777 // Get the motion_est context object
778 struct motion_est_context_s *c = mlt_properties_get_data( MLT_FILTER_PROPERTIES( filter ), "context", NULL);
779
780
781 // Get the new image and frame number
782 int error = mlt_frame_get_image( frame, image, format, width, height, 1 );
783
784 #ifdef BENCHMARK
785 struct timeval start; gettimeofday(&start, NULL );
786 #endif
787
788
789 if( error != 0 )
790 mlt_properties_debug( MLT_FRAME_PROPERTIES(frame), "error after mlt_frame_get_image() in motion_est", stderr );
791
792 c->current_frame_position = mlt_frame_get_position( frame );
793
794 /* Context Initialization */
795 if ( c->initialized == 0 ) {
796
797 // Get the filter properties object
798 mlt_properties properties = mlt_filter_properties( filter );
799
800 c->width = *width;
801 c->height = *height;
802
803 /* Get parameters that may have been overridden */
804 if( mlt_properties_get( properties, "macroblock_width") != NULL )
805 c->mb_w = mlt_properties_get_int( properties, "macroblock_width");
806
807 if( mlt_properties_get( properties, "macroblock_height") != NULL )
808 c->mb_h = mlt_properties_get_int( properties, "macroblock_height");
809
810 if( mlt_properties_get( properties, "prediction_thresh") != NULL )
811 c->initial_thresh = mlt_properties_get_int( properties, "prediction_thresh" );
812 else
813 c->initial_thresh = c->mb_w * c->mb_h;
814
815 if( mlt_properties_get( properties, "search_method") != NULL )
816 c->search_method = mlt_properties_get_int( properties, "search_method");
817
818 if( mlt_properties_get( properties, "skip_prediction") != NULL )
819 c->skip_prediction = mlt_properties_get_int( properties, "skip_prediction");
820
821 if( mlt_properties_get( properties, "limit_x") != NULL )
822 c->limit_x = mlt_properties_get_int( properties, "limit_x");
823
824 if( mlt_properties_get( properties, "limit_y") != NULL )
825 c->limit_y = mlt_properties_get_int( properties, "limit_y");
826
827 if( mlt_properties_get( properties, "check_chroma" ) != NULL )
828 c->check_chroma = mlt_properties_get_int( properties, "check_chroma" );
829
830 if( mlt_properties_get( properties, "denoise" ) != NULL )
831 c->denoise = mlt_properties_get_int( properties, "denoise" );
832
833 if( mlt_properties_get( properties, "show_reconstruction" ) != NULL )
834 c->show_reconstruction = mlt_properties_get_int( properties, "show_reconstruction" );
835
836 if( mlt_properties_get( properties, "show_residual" ) != NULL )
837 c->show_residual = mlt_properties_get_int( properties, "show_residual" );
838
839 if( mlt_properties_get( properties, "toggle_when_paused" ) != NULL )
840 c->toggle_when_paused = mlt_properties_get_int( properties, "toggle_when_paused" );
841
842 init_optimizations( c );
843
844 // Calculate the dimensions in macroblock units
845 c->mv_buffer_width = (*width / c->mb_w);
846 c->mv_buffer_height = (*height / c->mb_h);
847
848 // Size of the motion vector buffer
849 c->mv_size = c->mv_buffer_width * c->mv_buffer_height * sizeof(struct motion_vector_s);
850
851 // Allocate the motion vector buffers
852 c->former_vectors = mlt_pool_alloc( c->mv_size );
853 c->current_vectors = mlt_pool_alloc( c->mv_size );
854 c->denoise_vectors = mlt_pool_alloc( c->mv_size );
855
856 // Register motion buffers for destruction
857 mlt_properties_set_data( properties, "current_motion_vectors", (void *)c->current_vectors, 0, mlt_pool_release, NULL );
858 mlt_properties_set_data( properties, "former_motion_vectors", (void *)c->former_vectors, 0, mlt_pool_release, NULL );
859 mlt_properties_set_data( properties, "denoise_motion_vectors", (void *)c->denoise_vectors, 0, mlt_pool_release, NULL );
860
861 c->former_vectors_valid = 0;
862 memset( c->former_vectors, 0, c->mv_size );
863
864 // Calculate the size of our steps (the number of bytes that seperate adjacent pixels in X and Y direction)
865 switch( *format ) {
866 case mlt_image_yuv422:
867 c->xstride = 2;
868 c->ystride = c->xstride * *width;
869 break;
870 default:
871 // I don't know
872 fprintf(stderr, "\"I am unfamiliar with your new fangled pixel format!\" -filter_motion_est\n");
873 return -1;
874 }
875
876 // Allocate a cache for the previous frame's image
877 c->former_image = mlt_pool_alloc( *width * *height * 2 );
878 c->cache_image = mlt_pool_alloc( *width * *height * 2 );
879
880 // Register for destruction
881 mlt_properties_set_data( properties, "cache_image", (void *)c->cache_image, 0, mlt_pool_release, NULL );
882 mlt_properties_set_data( properties, "former_image", (void *)c->former_image, 0, mlt_pool_release, NULL );
883
884 c->former_frame_position = c->current_frame_position;
885 c->previous_msad = 0;
886
887 c->initialized = 1;
888 }
889
890 /* Check to see if somebody else has given us bounds */
891 struct mlt_geometry_item_s *bounds = mlt_properties_get_data( MLT_FRAME_PROPERTIES( frame ), "bounds", NULL );
892
893 if( bounds != NULL ) {
894 // translate pixel units (from bounds) to macroblock units
895 // make sure whole macroblock stays within bounds
896 c->left_mb = ( bounds->x + c->mb_w - 1 ) / c->mb_w;
897 c->top_mb = ( bounds->y + c->mb_h - 1 ) / c->mb_h;
898 c->right_mb = ( bounds->x + bounds->w ) / c->mb_w - 1;
899 c->bottom_mb = ( bounds->y + bounds->h ) / c->mb_h - 1;
900 c->bounds.x = bounds->x;
901 c->bounds.y = bounds->y;
902 c->bounds.w = bounds->w;
903 c->bounds.h = bounds->h;
904 } else {
905 c->left_mb = c->prev_left_mb = 0;
906 c->top_mb = c->prev_top_mb = 0;
907 c->right_mb = c->prev_right_mb = c->mv_buffer_width - 1; // Zero indexed
908 c->bottom_mb = c->prev_bottom_mb = c->mv_buffer_height - 1;
909 c->bounds.x = 0;
910 c->bounds.y = 0;
911 c->bounds.w = *width;
912 c->bounds.h = *height;
913 }
914
915 // If video is advancing, run motion vector algorithm and etc...
916 if( c->former_frame_position + 1 == c->current_frame_position )
917 {
918
919 // Swap the motion vector buffers and reuse allocated memory
920 struct motion_vector_s *temp = c->current_vectors;
921 c->current_vectors = c->former_vectors;
922 c->former_vectors = temp;
923
924 // This is done because filter_vismv doesn't pay attention to frame boundry
925 memset( c->current_vectors, 0, c->mv_size );
926
927 // Perform the motion search
928 motion_search( c->cache_image, *image, c );
929
930 collect_post_statistics( c );
931
932
933 // Detect shot changes
934 if( c->comparison_average > 10 * c->mb_w * c->mb_h &&
935 c->comparison_average > c->previous_msad * 2 )
936 {
937 fprintf(stderr, " - SAD: %d <<Shot change>>\n", c->comparison_average);
938 mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "shot_change", 1);
939 // c->former_vectors_valid = 0; // Invalidate the previous frame's predictors
940 c->shot_change = 1;
941 }
942 else {
943 c->former_vectors_valid = 1;
944 c->shot_change = 0;
945 //fprintf(stderr, " - SAD: %d\n", c->comparison_average);
946 }
947
948 c->previous_msad = c->comparison_average;
949
950 if( c->comparison_average != 0 ) { // If the frame is not a duplicate of the previous frame
951
952 // denoise the vector buffer
953 if( c->denoise )
954 median_denoise( c->current_vectors, c );
955
956 // Pass the new vector data into the frame
957 mlt_properties_set_data( MLT_FRAME_PROPERTIES( frame ), "motion_est.vectors",
958 (void*)c->current_vectors, c->mv_size, NULL, NULL );
959
960 // Cache the frame's image. Save the old cache. Reuse memory.
961 // After this block, exactly two unique frames will be cached
962 uint8_t *timg = c->cache_image;
963 c->cache_image = c->former_image;
964 c->former_image = timg;
965 memcpy( c->cache_image, *image, *width * *height * c->xstride );
966
967
968 }
969 else {
970 // Undo the Swap, This fixes the ugliness caused by a duplicate frame
971 temp = c->current_vectors;
972 c->current_vectors = c->former_vectors;
973 c->former_vectors = temp;
974 mlt_properties_set_data( MLT_FRAME_PROPERTIES( frame ), "motion_est.vectors",
975 (void*)c->former_vectors, c->mv_size, NULL, NULL );
976 }
977
978
979 if( c->shot_change == 1)
980 ;
981 else if( c->show_reconstruction )
982 show_reconstruction( *image, c );
983 else if( c->show_residual )
984 show_residual( *image, c );
985
986 }
987 // paused
988 else if( c->former_frame_position == c->current_frame_position )
989 {
990 // Pass the old vector data into the frame if it's valid
991 if( c->former_vectors_valid == 1 ) {
992 mlt_properties_set_data( MLT_FRAME_PROPERTIES( frame ), "motion_est.vectors",
993 (void*)c->current_vectors, c->mv_size, NULL, NULL );
994
995 if( c->shot_change == 1)
996 ;
997 else if( c->toggle_when_paused == 1 ) {
998 if( c->show_reconstruction )
999 show_reconstruction( *image, c );
1000 else if( c->show_residual )
1001 show_residual( *image, c );
1002 c->toggle_when_paused = 2;
1003 }
1004 else if( c->toggle_when_paused == 2 )
1005 c->toggle_when_paused = 1;
1006 else {
1007 if( c->show_reconstruction )
1008 show_reconstruction( *image, c );
1009 else if( c->show_residual )
1010 show_residual( *image, c );
1011 }
1012
1013 }
1014
1015 mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "shot_change", c->shot_change);
1016 }
1017 // there was jump in frame number
1018 else {
1019 // fprintf(stderr, "Warning: there was a frame number jumped from %d to %d.\n", c->former_frame_position, c->current_frame_position);
1020 c->former_vectors_valid = 0;
1021 }
1022
1023
1024 // Cache our bounding geometry for the next frame's processing
1025 c->prev_left_mb = c->left_mb;
1026 c->prev_top_mb = c->top_mb;
1027 c->prev_right_mb = c->right_mb;
1028 c->prev_bottom_mb = c->bottom_mb;
1029
1030 // Remember which frame this is
1031 c->former_frame_position = c->current_frame_position;
1032
1033
1034 mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "motion_est.macroblock_width", c->mb_w );
1035 mlt_properties_set_int( MLT_FRAME_PROPERTIES( frame ), "motion_est.macroblock_height", c->mb_h );
1036
1037 #ifdef BENCHMARK
1038 struct timeval finish; gettimeofday(&finish, NULL ); int difference = (finish.tv_sec - start.tv_sec) * 1000000 + (finish.tv_usec - start.tv_usec);
1039 fprintf(stderr, " in frame %d:%d usec\n", c->current_frame_position, difference);
1040 #endif
1041
1042
1043 return error;
1044 }
1045
1046
1047
1048 /** filter processing.
1049 */
1050
1051 static mlt_frame filter_process( mlt_filter this, mlt_frame frame )
1052 {
1053
1054 // Keeps tabs on the filter object
1055 mlt_frame_push_service( frame, this);
1056
1057 // Push the frame filter
1058 mlt_frame_push_get_image( frame, filter_get_image );
1059
1060 return frame;
1061 }
1062
1063 /** Constructor for the filter.
1064 */
1065 mlt_filter filter_motion_est_init( char *arg )
1066 {
1067 mlt_filter this = mlt_filter_new( );
1068 if ( this != NULL )
1069 {
1070 // Get the properties object
1071 mlt_properties properties = MLT_FILTER_PROPERTIES( this );
1072
1073 // Initialize the motion estimation context
1074 struct motion_est_context_s *context;
1075 context = mlt_pool_alloc( sizeof(struct motion_est_context_s) );
1076 mlt_properties_set_data( properties, "context", (void *)context, sizeof( struct motion_est_context_s ),
1077 mlt_pool_release, NULL );
1078
1079
1080 // Register the filter
1081 this->process = filter_process;
1082
1083 /* defaults that may be overridden */
1084 context->mb_w = 16;
1085 context->mb_h = 16;
1086 context->skip_prediction = 0;
1087 context->limit_x = 64;
1088 context->limit_y = 64;
1089 context->search_method = DIAMOND_SEARCH; // FIXME: not used
1090 context->check_chroma = 0;
1091 context->denoise = 1;
1092 context->show_reconstruction = 0;
1093 context->show_residual = 0;
1094 context->toggle_when_paused = 0;
1095
1096 /* reference functions that may have optimized versions */
1097 context->compare_reference = sad_reference;
1098
1099 // The rest of the buffers will be initialized when the filter is first processed
1100 context->initialized = 0;
1101 }
1102 return this;
1103 }