1 /* a complicated operation for testing
2 *
3 * 6/10/06
4 * - hacked in
5 * 27/11/06
6 * - added im_benchmarkn()
7 * 1/2/11
8 * - gtk-doc
9 */
10
11 /*
12
13 This file is part of VIPS.
14
15 VIPS is free software; you can redistribute it and/or modify
16 it under the terms of the GNU Lesser General Public License as published by
17 the Free Software Foundation; either version 2 of the License, or
18 (at your option) any later version.
19
20 This program is distributed in the hope that it will be useful,
21 but WITHOUT ANY WARRANTY; without even the implied warranty of
22 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
23 GNU Lesser General Public License for more details.
24
25 You should have received a copy of the GNU Lesser General Public License
26 along with this program; if not, write to the Free Software
27 Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
28 02110-1301 USA
29
30 */
31
32 /*
33
34 These files are distributed with VIPS - http://www.vips.ecs.soton.ac.uk
35
36 */
37
38 #ifdef HAVE_CONFIG_H
39 #include <config.h>
40 #endif /*HAVE_CONFIG_H*/
41 #include <vips/intl.h>
42
43 #include <stdio.h>
44 #include <stdlib.h>
45 #include <math.h>
46
47 #include <vips/vips.h>
48 #include <vips/vips7compat.h>
49
50 /*
51
52 VIPS SMP benchmark
53 ------------------
54
55 This is adapted from the system used to generate images for POD:
56
57 http://cima.ng-london.org.uk/~john/POD
58
59 Images from a 10k by 10k studio digital camera are colour processed, resized,
60 cropped and sharpened.
61
62 The original POD script was written in nip (see below). This operation is a
63 reimplementation in vanilla C to make it easier to run (and less fragile!).
64
65 This thing was originally processing images off a remote server over a 100mbit
66 network. No attempt was made to make it quick (there was no point): you
67 could make it a lot faster very easily.
68
69 ------ benchmark in nip2 -----------
70 #!/home/john/vips/bin/nip2 -s
71
72 // get command-line arguments
73
74 image_path = argv?1;
75 crop_id = parse_pint argv?2;
76 crop_left = parse_pint argv?3;
77 crop_top = parse_pint argv?4;
78 crop_width = parse_pint argv?5;
79 crop_height = parse_pint argv?6;
80 width = parse_pint argv?7;
81 height = parse_pint argv?8;
82 sharp = parse_pint argv?9;
83
84 // scale down by this much to undo photographic's relativisation
85 darken = Vector [1.18, 1, 1];
86
87 // fudge factor in XYZ to get a match under NGC lights on uv-durable paper
88 white_point_adjust = Vector [1.06, 1, 1.01];
89
90 // brighten by this in XYZ to get relative colorimetry
91 brighten = 1.5;
92
93 // blacks down by this much in LAB
94 blacks_down = Vector [-2, 0, 0];
95
96 // sharpen params for 400, 300, 200 and 150 dpi
97 // just change the size of the area we search
98 sharpen_params_table = [
99 [ 11, 2.5, 40, 20, 0.5, 1.5 ],
100 [ 7, 2.5, 40, 20, 0.5, 1.5 ],
101 [ 5, 2.5, 40, 20, 0.5, 1.5 ],
102 [ 3, 2.5, 40, 20, 0.5, 1.5 ]
103 ];
104
105 // convert D65 XYZ to D50 XYZ
106 D652D50 = recomb D652D50_direct;
107
108 stage_crop in
109 = extract_area crop_left crop_top crop_width crop_height in,
110 crop_id != 0
111 = in;
112
113 // fit within a width / height
114 stage_shrink image
115 = image, factor > 1; // never upscale
116 = resize factor factor Interpolate.BILINEAR image
117 {
118 hfactor = width / get_width image;
119 vfactor = height / get_height image;
120 factor = min_pair hfactor vfactor;
121 }
122
123 // unphotoize, go to xyz, convert to D50, adjust white point, back to lab
124 stage_colour in
125 = if in?0 > 99 then Vector [100, 0, 0] else in'''
126 {
127 // back to absolute
128 in' = in / darken;
129
130 xyz = colour_transform_to Image_type.XYZ in';
131
132 xyz' = D652D50 xyz * white_point_adjust * brighten;
133
134 in'' = colour_transform_to Image_type.LAB xyz';
135
136 // shadows down
137 in''' = in'' + blacks_down;
138 }
139
140 stage_sharp in
141 = (sharpen params?0 params?1 params?2 params?3 params?4 params?5 @
142 colour_transform_to Image_type.LABQ) in
143 {
144 params = sharpen_params_table?sharp;
145 }
146
147 // This was:
148 //
149 // stage_srgb in
150 // = (icc_export 8 "$VIPSHOME/share/nip2/data/sRGB.icm" 1 @
151 // colour_transform_to Image_type.LABQ) in;
152 //
153 // but that uses lcms which is single-threaded. So for this benchmark, we use
154 // VIPS's own ->sRGB converter, which is less accurate but does thread.
155 stage_srgb in
156 = colour_transform_to Image_type.sRGB in;
157
158 main = (get_image @ stage_srgb @
159 stage_sharp @ stage_colour @ stage_shrink @ stage_crop @
160 colour_transform_to Image_type.LAB @ Image_file) image_path;
161 ------ benchmark in nip2 -----------
162
163 */
164
165 /* The main part of the benchmark ... transform labq to labq. Chain several of
166 * these together to get a CPU-bound operation.
167 */
168 static int
benchmark(IMAGE * in,IMAGE * out)169 benchmark( IMAGE *in, IMAGE *out )
170 {
171 IMAGE *t[18];
172 double one[3] = { 1.0, 1.0, 1.0 };
173 double zero[3] = { 0.0, 0.0, 0.0 };
174 double darken[3] = { 1.0 / 1.18, 1.0, 1.0 };
175 double whitepoint[3] = { 1.06, 1.0, 1.01 };
176 double shadow[3] = { -2, 0, 0 };
177 double white[3] = { 100, 0, 0 };
178 DOUBLEMASK *d652d50 = im_create_dmaskv( "d652d50", 3, 3,
179 1.13529, -0.0604663, -0.0606321,
180 0.0975399, 0.935024, -0.0256156,
181 -0.0336428, 0.0414702, 0.994135 );
182
183 im_add_close_callback( out,
184 (im_callback_fn) im_free_dmask, d652d50, NULL );
185
186 return(
187 /* Set of descriptors for this operation.
188 */
189 im_open_local_array( out, t, 18, "im_benchmark", "p" ) ||
190
191 /* Unpack to float.
192 */
193 im_LabQ2Lab( in, t[0] ) ||
194
195 /* Crop 100 pixels off all edges.
196 */
197 im_extract_area( t[0], t[1],
198 100, 100, t[0]->Xsize - 200, t[0]->Ysize - 200 ) ||
199
200 /* Shrink by 10%, bilinear interp.
201 */
202 im_affinei_all( t[1], t[2],
203 vips_interpolate_bilinear_static(),
204 0.9, 0, 0, 0.9,
205 0, 0 ) ||
206
207 /* Find L ~= 100 areas (white surround).
208 */
209 im_extract_band( t[2], t[3], 0 ) ||
210 im_moreconst( t[3], t[4], 99 ) ||
211
212 /* Adjust white point and shadows.
213 */
214 im_lintra_vec( 3, darken, t[2], zero, t[5] ) ||
215 im_Lab2XYZ( t[5], t[6] ) ||
216 im_recomb( t[6], t[7], d652d50 ) ||
217 im_lintra_vec( 3, whitepoint, t[7], zero, t[8] ) ||
218 im_lintra( 1.5, t[8], 0.0, t[9] ) ||
219 im_XYZ2Lab( t[9], t[10] ) ||
220 im_lintra_vec( 3, one, t[10], shadow, t[11] ) ||
221
222 /* Make a solid white image.
223 */
224 im_black( t[12], t[4]->Xsize, t[4]->Ysize, 3 ) ||
225 im_lintra_vec( 3, zero, t[12], white, t[13] ) ||
226
227 /* Reattach border.
228 */
229 im_ifthenelse( t[4], t[13], t[11], t[14] ) ||
230
231 /* Sharpen.
232 */
233 im_Lab2LabQ( t[14], t[15] ) ||
234 im_sharpen( t[15], out, 11, 2.5, 40, 20, 0.5, 1.5 )
235 );
236 }
237
238 /**
239 * im_benchmarkn:
240 * @in: input image
241 * @out: output image
242 * @n: iterations
243 *
244 * This operation runs a complicated set of other operations on image @in,
245 * producing image @out. Use @n to set the number of iterations to run: a
246 * larger number will make the operation more CPU-bound, a smaller number will
247 * make the operation more IO-bound.
248 *
249 * See http://www.vips.ecs.soton.ac.uk/index.php?title=Benchmarks for a
250 * detailed discussion of the benchmark and some sample results.
251 *
252 * See also: im_benchmark2().
253 *
254 * Returns: 0 on success, -1 on error
255 */
256 int
im_benchmarkn(IMAGE * in,IMAGE * out,int n)257 im_benchmarkn( IMAGE *in, IMAGE *out, int n )
258 {
259 IMAGE *t[2];
260
261 if( n == 0 )
262 /* To sRGB.
263 */
264 return( im_LabQ2disp( in, out, im_col_displays( 7 ) ) );
265 else
266 return( im_open_local_array( out, t, 2, "benchmarkn", "p" ) ||
267 benchmark( in, t[0] ) ||
268
269 /* Expand back to the original size again ...
270 * benchmark does a 200 pixel crop plus a 10% shrink,
271 * so if we chain many of them together the image gets
272 * too small.
273 */
274 im_affinei_all( t[0], t[1],
275 vips_interpolate_bilinear_static(),
276 (double) in->Xsize / t[0]->Xsize, 0, 0,
277 (double) in->Ysize / t[0]->Ysize,
278 0, 0 ) ||
279
280 im_benchmarkn( t[1], out, n - 1 ) );
281 }
282
283 /**
284 * im_benchmark2:
285 * @in: input image
286 * @out: average image value
287 *
288 * This operation runs a single im_benchmarkn() and calculates the average
289 * pixel value. It's useful if you just want to test image input.
290 *
291 * See also: im_benchmarkn().
292 *
293 * Returns: 0 on success, -1 on error
294 */
295 int
im_benchmark2(IMAGE * in,double * out)296 im_benchmark2( IMAGE *in, double *out )
297 {
298 IMAGE *t;
299
300 return(
301 !(t = im_open_local( in, "benchmarkn", "p" )) ||
302 im_benchmarkn( in, t, 1 ) ||
303 im_avg( t, out )
304 );
305 }
306
307