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1 /* | |
2 * Copyright (c) 2012 The WebRTC project authors. All Rights Reserved. | |
3 * | |
4 * Use of this source code is governed by a BSD-style license | |
5 * that can be found in the LICENSE file in the root of the source | |
6 * tree. An additional intellectual property rights grant can be found | |
7 * in the file PATENTS. All contributing project authors may | |
8 * be found in the AUTHORS file in the root of the source tree. | |
9 */ | |
10 #include "webrtc/modules/video_processing/main/source/content_analysis.h" | |
11 | |
12 #include <math.h> | |
13 #include <stdlib.h> | |
14 | |
15 #include "webrtc/system_wrappers/include/cpu_features_wrapper.h" | |
16 #include "webrtc/system_wrappers/include/tick_util.h" | |
17 | |
18 namespace webrtc { | |
19 | |
20 VPMContentAnalysis::VPMContentAnalysis(bool runtime_cpu_detection) | |
21 : orig_frame_(NULL), | |
22 prev_frame_(NULL), | |
23 width_(0), | |
24 height_(0), | |
25 skip_num_(1), | |
26 border_(8), | |
27 motion_magnitude_(0.0f), | |
28 spatial_pred_err_(0.0f), | |
29 spatial_pred_err_h_(0.0f), | |
30 spatial_pred_err_v_(0.0f), | |
31 first_frame_(true), | |
32 ca_Init_(false), | |
33 content_metrics_(NULL) { | |
34 ComputeSpatialMetrics = &VPMContentAnalysis::ComputeSpatialMetrics_C; | |
35 TemporalDiffMetric = &VPMContentAnalysis::TemporalDiffMetric_C; | |
36 | |
37 if (runtime_cpu_detection) { | |
38 #if defined(WEBRTC_ARCH_X86_FAMILY) | |
39 if (WebRtc_GetCPUInfo(kSSE2)) { | |
40 ComputeSpatialMetrics = &VPMContentAnalysis::ComputeSpatialMetrics_SSE2; | |
41 TemporalDiffMetric = &VPMContentAnalysis::TemporalDiffMetric_SSE2; | |
42 } | |
43 #endif | |
44 } | |
45 Release(); | |
46 } | |
47 | |
48 VPMContentAnalysis::~VPMContentAnalysis() { | |
49 Release(); | |
50 } | |
51 | |
52 VideoContentMetrics* VPMContentAnalysis::ComputeContentMetrics( | |
53 const VideoFrame& inputFrame) { | |
54 if (inputFrame.IsZeroSize()) | |
55 return NULL; | |
56 | |
57 // Init if needed (native dimension change). | |
58 if (width_ != inputFrame.width() || height_ != inputFrame.height()) { | |
59 if (VPM_OK != Initialize(inputFrame.width(), inputFrame.height())) | |
60 return NULL; | |
61 } | |
62 // Only interested in the Y plane. | |
63 orig_frame_ = inputFrame.buffer(kYPlane); | |
64 | |
65 // Compute spatial metrics: 3 spatial prediction errors. | |
66 (this->*ComputeSpatialMetrics)(); | |
67 | |
68 // Compute motion metrics | |
69 if (first_frame_ == false) | |
70 ComputeMotionMetrics(); | |
71 | |
72 // Saving current frame as previous one: Y only. | |
73 memcpy(prev_frame_, orig_frame_, width_ * height_); | |
74 | |
75 first_frame_ = false; | |
76 ca_Init_ = true; | |
77 | |
78 return ContentMetrics(); | |
79 } | |
80 | |
81 int32_t VPMContentAnalysis::Release() { | |
82 if (content_metrics_ != NULL) { | |
83 delete content_metrics_; | |
84 content_metrics_ = NULL; | |
85 } | |
86 | |
87 if (prev_frame_ != NULL) { | |
88 delete [] prev_frame_; | |
89 prev_frame_ = NULL; | |
90 } | |
91 | |
92 width_ = 0; | |
93 height_ = 0; | |
94 first_frame_ = true; | |
95 | |
96 return VPM_OK; | |
97 } | |
98 | |
99 int32_t VPMContentAnalysis::Initialize(int width, int height) { | |
100 width_ = width; | |
101 height_ = height; | |
102 first_frame_ = true; | |
103 | |
104 // skip parameter: # of skipped rows: for complexity reduction | |
105 // temporal also currently uses it for column reduction. | |
106 skip_num_ = 1; | |
107 | |
108 // use skipNum = 2 for 4CIF, WHD | |
109 if ( (height_ >= 576) && (width_ >= 704) ) { | |
110 skip_num_ = 2; | |
111 } | |
112 // use skipNum = 4 for FULLL_HD images | |
113 if ( (height_ >= 1080) && (width_ >= 1920) ) { | |
114 skip_num_ = 4; | |
115 } | |
116 | |
117 if (content_metrics_ != NULL) { | |
118 delete content_metrics_; | |
119 } | |
120 | |
121 if (prev_frame_ != NULL) { | |
122 delete [] prev_frame_; | |
123 } | |
124 | |
125 // Spatial Metrics don't work on a border of 8. Minimum processing | |
126 // block size is 16 pixels. So make sure the width and height support this. | |
127 if (width_ <= 32 || height_ <= 32) { | |
128 ca_Init_ = false; | |
129 return VPM_PARAMETER_ERROR; | |
130 } | |
131 | |
132 content_metrics_ = new VideoContentMetrics(); | |
133 if (content_metrics_ == NULL) { | |
134 return VPM_MEMORY; | |
135 } | |
136 | |
137 prev_frame_ = new uint8_t[width_ * height_]; // Y only. | |
138 if (prev_frame_ == NULL) return VPM_MEMORY; | |
139 | |
140 return VPM_OK; | |
141 } | |
142 | |
143 | |
144 // Compute motion metrics: magnitude over non-zero motion vectors, | |
145 // and size of zero cluster | |
146 int32_t VPMContentAnalysis::ComputeMotionMetrics() { | |
147 // Motion metrics: only one is derived from normalized | |
148 // (MAD) temporal difference | |
149 (this->*TemporalDiffMetric)(); | |
150 return VPM_OK; | |
151 } | |
152 | |
153 // Normalized temporal difference (MAD): used as a motion level metric | |
154 // Normalize MAD by spatial contrast: images with more contrast | |
155 // (pixel variance) likely have larger temporal difference | |
156 // To reduce complexity, we compute the metric for a reduced set of points. | |
157 int32_t VPMContentAnalysis::TemporalDiffMetric_C() { | |
158 // size of original frame | |
159 int sizei = height_; | |
160 int sizej = width_; | |
161 uint32_t tempDiffSum = 0; | |
162 uint32_t pixelSum = 0; | |
163 uint64_t pixelSqSum = 0; | |
164 | |
165 uint32_t num_pixels = 0; // Counter for # of pixels. | |
166 const int width_end = ((width_ - 2*border_) & -16) + border_; | |
167 | |
168 for (int i = border_; i < sizei - border_; i += skip_num_) { | |
169 for (int j = border_; j < width_end; j++) { | |
170 num_pixels += 1; | |
171 int ssn = i * sizej + j; | |
172 | |
173 uint8_t currPixel = orig_frame_[ssn]; | |
174 uint8_t prevPixel = prev_frame_[ssn]; | |
175 | |
176 tempDiffSum += (uint32_t)abs((int16_t)(currPixel - prevPixel)); | |
177 pixelSum += (uint32_t) currPixel; | |
178 pixelSqSum += (uint64_t) (currPixel * currPixel); | |
179 } | |
180 } | |
181 | |
182 // Default. | |
183 motion_magnitude_ = 0.0f; | |
184 | |
185 if (tempDiffSum == 0) return VPM_OK; | |
186 | |
187 // Normalize over all pixels. | |
188 float const tempDiffAvg = (float)tempDiffSum / (float)(num_pixels); | |
189 float const pixelSumAvg = (float)pixelSum / (float)(num_pixels); | |
190 float const pixelSqSumAvg = (float)pixelSqSum / (float)(num_pixels); | |
191 float contrast = pixelSqSumAvg - (pixelSumAvg * pixelSumAvg); | |
192 | |
193 if (contrast > 0.0) { | |
194 contrast = sqrt(contrast); | |
195 motion_magnitude_ = tempDiffAvg/contrast; | |
196 } | |
197 return VPM_OK; | |
198 } | |
199 | |
200 // Compute spatial metrics: | |
201 // To reduce complexity, we compute the metric for a reduced set of points. | |
202 // The spatial metrics are rough estimates of the prediction error cost for | |
203 // each QM spatial mode: 2x2,1x2,2x1 | |
204 // The metrics are a simple estimate of the up-sampling prediction error, | |
205 // estimated assuming sub-sampling for decimation (no filtering), | |
206 // and up-sampling back up with simple bilinear interpolation. | |
207 int32_t VPMContentAnalysis::ComputeSpatialMetrics_C() { | |
208 const int sizei = height_; | |
209 const int sizej = width_; | |
210 | |
211 // Pixel mean square average: used to normalize the spatial metrics. | |
212 uint32_t pixelMSA = 0; | |
213 | |
214 uint32_t spatialErrSum = 0; | |
215 uint32_t spatialErrVSum = 0; | |
216 uint32_t spatialErrHSum = 0; | |
217 | |
218 // make sure work section is a multiple of 16 | |
219 const int width_end = ((sizej - 2*border_) & -16) + border_; | |
220 | |
221 for (int i = border_; i < sizei - border_; i += skip_num_) { | |
222 for (int j = border_; j < width_end; j++) { | |
223 int ssn1= i * sizej + j; | |
224 int ssn2 = (i + 1) * sizej + j; // bottom | |
225 int ssn3 = (i - 1) * sizej + j; // top | |
226 int ssn4 = i * sizej + j + 1; // right | |
227 int ssn5 = i * sizej + j - 1; // left | |
228 | |
229 uint16_t refPixel1 = orig_frame_[ssn1] << 1; | |
230 uint16_t refPixel2 = orig_frame_[ssn1] << 2; | |
231 | |
232 uint8_t bottPixel = orig_frame_[ssn2]; | |
233 uint8_t topPixel = orig_frame_[ssn3]; | |
234 uint8_t rightPixel = orig_frame_[ssn4]; | |
235 uint8_t leftPixel = orig_frame_[ssn5]; | |
236 | |
237 spatialErrSum += (uint32_t) abs((int16_t)(refPixel2 | |
238 - (uint16_t)(bottPixel + topPixel + leftPixel + rightPixel))); | |
239 spatialErrVSum += (uint32_t) abs((int16_t)(refPixel1 | |
240 - (uint16_t)(bottPixel + topPixel))); | |
241 spatialErrHSum += (uint32_t) abs((int16_t)(refPixel1 | |
242 - (uint16_t)(leftPixel + rightPixel))); | |
243 pixelMSA += orig_frame_[ssn1]; | |
244 } | |
245 } | |
246 | |
247 // Normalize over all pixels. | |
248 const float spatialErr = (float)(spatialErrSum >> 2); | |
249 const float spatialErrH = (float)(spatialErrHSum >> 1); | |
250 const float spatialErrV = (float)(spatialErrVSum >> 1); | |
251 const float norm = (float)pixelMSA; | |
252 | |
253 // 2X2: | |
254 spatial_pred_err_ = spatialErr / norm; | |
255 // 1X2: | |
256 spatial_pred_err_h_ = spatialErrH / norm; | |
257 // 2X1: | |
258 spatial_pred_err_v_ = spatialErrV / norm; | |
259 return VPM_OK; | |
260 } | |
261 | |
262 VideoContentMetrics* VPMContentAnalysis::ContentMetrics() { | |
263 if (ca_Init_ == false) return NULL; | |
264 | |
265 content_metrics_->spatial_pred_err = spatial_pred_err_; | |
266 content_metrics_->spatial_pred_err_h = spatial_pred_err_h_; | |
267 content_metrics_->spatial_pred_err_v = spatial_pred_err_v_; | |
268 // Motion metric: normalized temporal difference (MAD). | |
269 content_metrics_->motion_magnitude = motion_magnitude_; | |
270 | |
271 return content_metrics_; | |
272 } | |
273 | |
274 } // namespace webrtc | |
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