|
|
@ -1683,31 +1683,6 @@ TEST(Imgproc_ColorLuv, accuracy) { CV_ColorLuvTest test; test.safe_run(); } |
|
|
|
TEST(Imgproc_ColorRGB, accuracy) { CV_ColorRGBTest test; test.safe_run(); } |
|
|
|
TEST(Imgproc_ColorRGB, accuracy) { CV_ColorRGBTest test; test.safe_run(); } |
|
|
|
TEST(Imgproc_ColorBayer, accuracy) { CV_ColorBayerTest test; test.safe_run(); } |
|
|
|
TEST(Imgproc_ColorBayer, accuracy) { CV_ColorBayerTest test; test.safe_run(); } |
|
|
|
|
|
|
|
|
|
|
|
TEST(Imgproc_ImreadVSCvtColor, regression) |
|
|
|
|
|
|
|
{ |
|
|
|
|
|
|
|
cvtest::TS& ts = *cvtest::TS::ptr(); |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
const int MAX_MEAN_DIFF = 3; |
|
|
|
|
|
|
|
const int MAX_ABS_DIFF = 10; |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
string imgName = string(ts.get_data_path()) + "/shared/lena.jpg"; |
|
|
|
|
|
|
|
Mat original_image = imread(imgName); |
|
|
|
|
|
|
|
Mat gray_by_codec = imread(imgName, 0); |
|
|
|
|
|
|
|
Mat gray_by_cvt; |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
cvtColor(original_image, gray_by_cvt, CV_BGR2GRAY); |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Mat diff; |
|
|
|
|
|
|
|
absdiff(gray_by_codec, gray_by_cvt, diff); |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
double actual_avg_diff = (double)sum(diff)[0] / countNonZero(diff); |
|
|
|
|
|
|
|
double actual_maxval, actual_minval; |
|
|
|
|
|
|
|
minMaxLoc(diff, &actual_minval, &actual_maxval); |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
EXPECT_LT(actual_avg_diff, MAX_MEAN_DIFF); |
|
|
|
|
|
|
|
EXPECT_LT(actual_maxval, MAX_ABS_DIFF); |
|
|
|
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
TEST(Imgproc_ColorBayer, regression) |
|
|
|
TEST(Imgproc_ColorBayer, regression) |
|
|
|
{ |
|
|
|
{ |
|
|
|
cvtest::TS& ts = *cvtest::TS::ptr(); |
|
|
|
cvtest::TS& ts = *cvtest::TS::ptr(); |
|
|
|