forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
optical_flow.cc
85 lines (76 loc) · 2.39 KB
/
optical_flow.cc
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
#include <caffe2/video/optical_flow.h>
namespace caffe2 {
void OpticalFlowExtractor(
const cv::Mat& prev_gray,
const cv::Mat& curr_gray,
const int flow_alg_type,
cv::Mat& flow) {
#if CV_MAJOR_VERSION >= 4
cv::Ptr<cv::DISOpticalFlow> tvl1 = cv::DISOpticalFlow::create();
#else
cv::Ptr<cv::DualTVL1OpticalFlow> tvl1 = cv::DualTVL1OpticalFlow::create();
#endif
switch (flow_alg_type) {
case FLowAlgType::FarnebackOpticalFlow:
cv::calcOpticalFlowFarneback(
prev_gray,
curr_gray,
flow,
std::sqrt(2) / 2.0,
5,
10,
2,
7,
1.5,
cv::OPTFLOW_FARNEBACK_GAUSSIAN);
break;
case FLowAlgType::DensePyrLKOpticalFlow:
LOG(ERROR) << "DensePyrLKOpticalFlow only has sparse version on CPU";
break;
case FLowAlgType::BroxOpticalFlow:
LOG(ERROR) << "BroxOpticalFlow on CPU is not available";
break;
case FLowAlgType::OpticalFlowDual_TVL1:
tvl1->calc(prev_gray, curr_gray, flow);
break;
default:
LOG(ERROR) << "Unsupported optical flow type " << flow_alg_type;
break;
}
}
void MergeOpticalFlow(cv::Mat& prev_flow, const cv::Mat& curr_flow) {
const int rows = prev_flow.rows;
const int cols = prev_flow.cols;
// merge two optical flows into one
for (int y = 0; y < rows; y++) {
for (int x = 0; x < cols; x++) {
cv::Point2f u = prev_flow.at<cv::Point2f>(y, x);
// get the new location
int x_new = std::min(cols - 1, std::max(0, cvRound(u.x + x)));
int y_new = std::min(rows - 1, std::max(0, cvRound(u.y + y)));
cv::Point2f u_new = curr_flow.at<cv::Point2f>(y_new, x_new);
// update the flow
prev_flow.at<cv::Point2f>(y, x) += u_new;
}
}
}
void MultiFrameOpticalFlowExtractor(
const std::vector<cv::Mat>& grays,
const int optical_flow_alg_type,
cv::Mat& flow) {
int num_frames = grays.size();
CAFFE_ENFORCE_GE(num_frames, 2, "need at least 2 frames!");
// compute optical flow for every two frames
std::vector<cv::Mat> flows;
for (int i = 0; i < num_frames - 1; i++) {
cv::Mat tmp;
OpticalFlowExtractor(grays[i], grays[i + 1], optical_flow_alg_type, tmp);
flows.push_back(tmp);
}
flows[0].copyTo(flow);
// aggregate optical flow across multiple frame
for (int i = 1; i < num_frames - 1; i++) {
MergeOpticalFlow(flow, flows[i]);
}
}
} // namespace caffe2