===================================================================
--- git.orig/samples/cpp/logistic_regression.cpp
+++ git/samples/cpp/logistic_regression.cpp
-@@ -83,7 +83,7 @@ static float calculateAccuracyPercent(co
+@@ -28,7 +28,7 @@ static float calculateAccuracyPercent(co
int main()
{
--- git.orig/samples/dnn/classification.cpp
+++ git/samples/dnn/classification.cpp
@@ -11,6 +11,7 @@ std::string keys =
- "{ help h | | Print help message. }"
- "{ @alias | | An alias name of model to extract preprocessing parameters from models.yml file. }"
- "{ zoo | models.yml | An optional path to file with preprocessing parameters }"
-+ "{ device | 0 | camera device number. }"
- "{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera.}"
- "{ framework f | | Optional name of an origin framework of the model. Detect it automatically if it does not set. }"
- "{ classes | | Optional path to a text file with names of classes. }"
-@@ -94,7 +95,7 @@ int main(int argc, char** argv)
+ "{ help h | | Print help message. }"
+ "{ @alias | | An alias name of model to extract preprocessing parameters from models.yml file. }"
+ "{ zoo | models.yml | An optional path to file with preprocessing parameters }"
++ "{ device | 0 | camera device number. }"
+ "{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera.}"
+ "{ initial_width | 0 | Preprocess input image by initial resizing to a specific width.}"
+ "{ initial_height | 0 | Preprocess input image by initial resizing to a specific height.}"
+@@ -102,7 +103,7 @@ int main(int argc, char** argv)
if (parser.has("input"))
cap.open(parser.get<String>("input"));
else
//! [Open a video file or an image file or a camera stream]
// Process frames.
-@@ -131,13 +132,13 @@ int main(int argc, char** argv)
+@@ -151,13 +152,13 @@ int main(int argc, char** argv)
double freq = getTickFrequency() / 1000;
double t = net.getPerfProfile(layersTimes) / freq;
std::string label = format("Inference time: %.2f ms", t);
===================================================================
--- git.orig/samples/dnn/text_detection.cpp
+++ git/samples/dnn/text_detection.cpp
-@@ -25,6 +25,7 @@ using namespace cv::dnn;
+@@ -30,6 +30,7 @@ using namespace cv::dnn;
const char* keys =
- "{ help h | | Print help message. }"
- "{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera.}"
-+ "{ device | 0 | camera device number. }"
- "{ model m | | Path to a binary .pb file contains trained detector network.}"
- "{ ocr | | Path to a binary .pb or .onnx file contains trained recognition network.}"
- "{ width | 320 | Preprocess input image by resizing to a specific width. It should be multiple by 32. }"
-@@ -75,7 +76,7 @@ int main(int argc, char** argv)
+ "{ help h | | Print help message. }"
+ "{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera.}"
++ "{ device | 0 | camera device number. }"
+ "{ detModel dmp | | Path to a binary .pb file contains trained detector network.}"
+ "{ width | 320 | Preprocess input image by resizing to a specific width. It should be multiple by 32. }"
+ "{ height | 320 | Preprocess input image by resizing to a specific height. It should be multiple by 32. }"
+@@ -106,7 +107,7 @@ int main(int argc, char** argv)
// Open a video file or an image file or a camera stream.
VideoCapture cap;
CV_Assert(openSuccess);
static const std::string kWinName = "EAST: An Efficient and Accurate Scene Text Detector";
-@@ -156,7 +157,7 @@ int main(int argc, char** argv)
-
- // Put efficiency information.
- std::string label = format("Inference time: %.2f ms", tickMeter.getTimeMilli());
-- putText(frame, label, Point(0, 15), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 255, 0));
-+ putText(frame, label, Point(0, 20), FONT_HERSHEY_SIMPLEX, 0.8, Scalar(0, 0, 255), 2, 8, false);
-
- imshow(kWinName, frame);
-
