Merge branch '4.x' into '5.x'

modules/objdetect/include/opencv2/objdetect/barcode.hpp

@@ -57,6 +57,52 @@ public:
                                       CV_OUT std::vector<std::string> &decoded_info,
                                       CV_OUT std::vector<std::string> &decoded_type,
                                       OutputArray points = noArray()) const;
+
+    /** @brief Get detector downsampling threshold.
+     *
+     * @return detector downsampling threshold
+     */
+    CV_WRAP double getDownsamplingThreshold() const;
+
+    /** @brief Set detector downsampling threshold.
+     *
+     * By default, the detect method resizes the input image to this limit if the smallest image size is is greater than the threshold.
+     * Increasing this value can improve detection accuracy and the number of results at the expense of performance.
+     * Correlates with detector scales. Setting this to a large value will disable downsampling.
+     * @param thresh downsampling limit to apply (default 512)
+     * @see setDetectorScales
+     */
+    CV_WRAP BarcodeDetector& setDownsamplingThreshold(double thresh);
+
+    /** @brief Returns detector box filter sizes.
+     *
+     * @param sizes output parameter for returning the sizes.
+     */
+    CV_WRAP void getDetectorScales(CV_OUT std::vector<float>& sizes) const;
+
+    /** @brief Set detector box filter sizes.
+     *
+     * Adjusts the value and the number of box filters used in the detect step.
+     * The filter sizes directly correlate with the expected line widths for a barcode. Corresponds to expected barcode distance.
+     * If the downsampling limit is increased, filter sizes need to be adjusted in an inversely proportional way.
+     * @param sizes box filter sizes, relative to minimum dimension of the image (default [0.01, 0.03, 0.06, 0.08])
+     */
+    CV_WRAP BarcodeDetector& setDetectorScales(const std::vector<float>& sizes);
+
+    /** @brief Get detector gradient magnitude threshold.
+     *
+     * @return detector gradient magnitude threshold.
+     */
+    CV_WRAP double getGradientThreshold() const;
+
+    /** @brief Set detector gradient magnitude threshold.
+     *
+     * Sets the coherence threshold for detected bounding boxes.
+     * Increasing this value will generate a closer fitted bounding box width and can reduce false-positives.
+     * Values between 16 and 1024 generally work, while too high of a value will remove valid detections.
+     * @param thresh gradient magnitude threshold (default 64).
+     */
+    CV_WRAP BarcodeDetector& setGradientThreshold(double thresh);
 };
 //! @}
 

modules/objdetect/include/opencv2/objdetect/face.hpp

@@ -128,23 +128,23 @@ public:
      */
     enum DisType { FR_COSINE=0, FR_NORM_L2=1 };
 
-    /** @brief Aligning image to put face on the standard position
+    /** @brief Aligns detected face with the source input image and crops it
      *  @param src_img input image
-     *  @param face_box the detection result used for indicate face in input image
+     *  @param face_box the detected face result from the input image
      *  @param aligned_img output aligned image
      */
     CV_WRAP virtual void alignCrop(InputArray src_img, InputArray face_box, OutputArray aligned_img) const = 0;
 
-    /** @brief Extracting face feature from aligned image
+    /** @brief Extracts face feature from aligned image
      *  @param aligned_img input aligned image
      *  @param face_feature output face feature
      */
     CV_WRAP virtual void feature(InputArray aligned_img, OutputArray face_feature) = 0;
 
-    /** @brief Calculating the distance between two face features
+    /** @brief Calculates the distance between two face features
      *  @param face_feature1 the first input feature
      *  @param face_feature2 the second input feature of the same size and the same type as face_feature1
-     *  @param dis_type defining the similarity with optional values "FR_OSINE" or "FR_NORM_L2"
+     *  @param dis_type defines how to calculate the distance between two face features with optional values "FR_COSINE" or "FR_NORM_L2"
      */
     CV_WRAP virtual double match(InputArray face_feature1, InputArray face_feature2, int dis_type = FaceRecognizerSF::FR_COSINE) const = 0;