mirror/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2025-06-07 17:44:04 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Fix false positives of face detection network for large faces

Browse Source
This commit is contained in:
Dmitry Kurtaev 2019-07-22 12:18:57 +03:00 committed by Alexander Alekhin
parent ad092bf1ce
commit a2125594ea
4 changed files with 1817 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

25
modules/dnn/test/test_caffe_importer.cpp
View File

@ -561,7 +561,7 @@ TEST(Test_Caffe, shared_weights)
typedef testing::TestWithParam<tuple<std::string, Target> > opencv_face_detector; typedef testing::TestWithParam<tuple<std::string, Target> > opencv_face_detector;
TEST_P(opencv_face_detector, Accuracy) TEST_P(opencv_face_detector, Accuracy)
{ {
std::string proto = findDataFile("dnn/opencv_face_detector.prototxt", false); std::string proto = findDataFile("dnn/opencv_face_detector.prototxt");
std::string model = findDataFile(get<0>(GetParam()), false); std::string model = findDataFile(get<0>(GetParam()), false);
dnn::Target targetId = (dnn::Target)(int)get<1>(GetParam()); dnn::Target targetId = (dnn::Target)(int)get<1>(GetParam());
@ -584,6 +584,29 @@ TEST_P(opencv_face_detector, Accuracy)
0, 1, 0.95097077, 0.51901293, 0.45863652, 0.5777427, 0.5347801); 0, 1, 0.95097077, 0.51901293, 0.45863652, 0.5777427, 0.5347801);
normAssertDetections(ref, out, "", 0.5, 1e-5, 2e-4); normAssertDetections(ref, out, "", 0.5, 1e-5, 2e-4);
} }
// False positives bug for large faces: https://github.com/opencv/opencv/issues/15106
TEST_P(opencv_face_detector, issue_15106)
{
std::string proto = findDataFile("dnn/opencv_face_detector.prototxt");
std::string model = findDataFile(get<0>(GetParam()), false);
dnn::Target targetId = (dnn::Target)(int)get<1>(GetParam());
Net net = readNetFromCaffe(proto, model);
Mat img = imread(findDataFile("cv/shared/lena.png"));
img = img.rowRange(img.rows / 4, 3 * img.rows / 4).colRange(img.cols / 4, 3 * img.cols / 4);
Mat blob = blobFromImage(img, 1.0, Size(300, 300), Scalar(104.0, 177.0, 123.0), false, false);
net.setPreferableBackend(DNN_BACKEND_OPENCV);
net.setPreferableTarget(targetId);
net.setInput(blob);
// Output has shape 1x1xNx7 where N - number of detections.
// An every detection is a vector of values [id, classId, confidence, left, top, right, bottom]
Mat out = net.forward();
Mat ref = (Mat_<float>(1, 7) << 0, 1, 0.9149431, 0.30424616, 0.26964942, 0.88733053, 0.99815309);
normAssertDetections(ref, out, "", 0.2, 6e-5, 1e-4);
}
INSTANTIATE_TEST_CASE_P(Test_Caffe, opencv_face_detector, INSTANTIATE_TEST_CASE_P(Test_Caffe, opencv_face_detector,
Combine( Combine(
Values("dnn/opencv_face_detector.caffemodel", Values("dnn/opencv_face_detector.caffemodel",

4
samples/dnn/face_detector/deploy.prototxt
View File

@ -892,7 +892,7 @@ layer {
} }
convolution_param { convolution_param {
num_output: 128 num_output: 128
pad: 1 pad: 0
kernel_size: 3 kernel_size: 3
stride: 1 stride: 1
weight_filler { weight_filler {
@ -958,7 +958,7 @@ layer {
} }
convolution_param { convolution_param {
num_output: 128 num_output: 128
pad: 1 pad: 0
kernel_size: 3 kernel_size: 3
stride: 1 stride: 1
weight_filler { weight_filler {

1790
samples/dnn/face_detector/deploy_lowres.prototxt Normal file
View File

File diff suppressed because it is too large Load Diff

2
samples/dnn/js_face_recognition.html
View File

@ -69,7 +69,7 @@ function recognize(face) {
function loadModels(callback) { function loadModels(callback) {
var utils = new Utils(''); var utils = new Utils('');
var proto = 'https://raw.githubusercontent.com/opencv/opencv/3.4/samples/dnn/face_detector/deploy.prototxt'; var proto = 'https://raw.githubusercontent.com/opencv/opencv/3.4/samples/dnn/face_detector/deploy_lowres.prototxt';
var weights = 'https://raw.githubusercontent.com/opencv/opencv_3rdparty/dnn_samples_face_detector_20180205_fp16/res10_300x300_ssd_iter_140000_fp16.caffemodel'; var weights = 'https://raw.githubusercontent.com/opencv/opencv_3rdparty/dnn_samples_face_detector_20180205_fp16/res10_300x300_ssd_iter_140000_fp16.caffemodel';
var recognModel = 'https://raw.githubusercontent.com/pyannote/pyannote-data/master/openface.nn4.small2.v1.t7'; var recognModel = 'https://raw.githubusercontent.com/pyannote/pyannote-data/master/openface.nn4.small2.v1.t7';
utils.createFileFromUrl('face_detector.prototxt', proto, () => { utils.createFileFromUrl('face_detector.prototxt', proto, () => {