Merge pull request #24569 from Abdurrahheem:ash/padding_value_fix

Add support for custom padding in DNN preprocessing #24569

This PR add functionality for specifying value in padding.
It is required in many preprocessing pipelines in DNNs such as Yolox object detection model

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake

modules/dnn/include/opencv2/dnn/dnn.hpp

@@ -1212,7 +1212,7 @@ CV__DNN_INLINE_NS_BEGIN
         CV_WRAP Image2BlobParams();
         CV_WRAP Image2BlobParams(const Scalar& scalefactor, const Size& size = Size(), const Scalar& mean = Scalar(),
                             bool swapRB = false, int ddepth = CV_32F, DataLayout datalayout = DNN_LAYOUT_NCHW,
-                            ImagePaddingMode mode = DNN_PMODE_NULL);
+                            ImagePaddingMode mode = DNN_PMODE_NULL, Scalar borderValue = 0.0);
 
         CV_PROP_RW Scalar scalefactor; //!< scalefactor multiplier for input image values.
         CV_PROP_RW Size size;    //!< Spatial size for output image.
@@ -1221,6 +1221,7 @@ CV__DNN_INLINE_NS_BEGIN
         CV_PROP_RW int ddepth;   //!< Depth of output blob. Choose CV_32F or CV_8U.
         CV_PROP_RW DataLayout datalayout; //!< Order of output dimensions. Choose DNN_LAYOUT_NCHW or DNN_LAYOUT_NHWC.
         CV_PROP_RW ImagePaddingMode paddingmode;   //!< Image padding mode. @see ImagePaddingMode.
+        CV_PROP_RW Scalar borderValue;   //!< Value used in padding mode for padding.
     };
 
     /** @brief Creates 4-dimensional blob from image with given params.

modules/dnn/src/dnn_utils.cpp

@@ -17,9 +17,9 @@ Image2BlobParams::Image2BlobParams():scalefactor(Scalar::all(1.0)), size(Size())
 {}
 
 Image2BlobParams::Image2BlobParams(const Scalar& scalefactor_, const Size& size_, const Scalar& mean_, bool swapRB_,
-                         int ddepth_, DataLayout datalayout_, ImagePaddingMode mode_):
+                         int ddepth_, DataLayout datalayout_, ImagePaddingMode mode_, Scalar borderValue_):
         scalefactor(scalefactor_), size(size_), mean(mean_), swapRB(swapRB_), ddepth(ddepth_),
-        datalayout(datalayout_), paddingmode(mode_)
+        datalayout(datalayout_), paddingmode(mode_), borderValue(borderValue_)
 {}
 
 void getVector(InputArrayOfArrays images_, std::vector<Mat>& images) {
@@ -196,7 +196,7 @@ void blobFromImagesWithParamsImpl(InputArrayOfArrays images_, Tmat& blob_, const
                 int bottom = size.height - top - rh;
                 int left = (size.width - rw)/2;
                 int right = size.width - left - rw;
-                copyMakeBorder(images[i], images[i], top, bottom, left, right, BORDER_CONSTANT);
+                copyMakeBorder(images[i], images[i], top, bottom, left, right, BORDER_CONSTANT, param.borderValue);
             }
             else
             {

modules/dnn/test/test_misc.cpp

@@ -93,6 +93,39 @@ TEST(blobFromImageWithParams_4ch, NHWC_scalar_scale)
     }
 }
 
+TEST(blobFromImageWithParams_CustomPadding, letter_box)
+{
+    Mat img(40, 20, CV_8UC4, Scalar(0, 1, 2, 3));
+
+    // Custom padding value that you have added
+    Scalar customPaddingValue(5, 6, 7, 8); // Example padding value
+
+    Size targetSize(20, 20);
+
+    Mat targetImg = img.clone();
+
+    cv::copyMakeBorder(
+        targetImg, targetImg, 0, 0,
+        targetSize.width / 2,
+        targetSize.width / 2,
+        BORDER_CONSTANT,
+        customPaddingValue);
+
+    // Set up Image2BlobParams with your new functionality
+    Image2BlobParams param;
+    param.size = targetSize;
+    param.paddingmode = DNN_PMODE_LETTERBOX;
+    param.borderValue = customPaddingValue; // Use your new feature here
+
+    // Create blob with custom padding
+    Mat blob = dnn::blobFromImageWithParams(img, param);
+
+    // Create target blob for comparison
+    Mat targetBlob = dnn::blobFromImage(targetImg, 1.0, targetSize);
+
+    EXPECT_EQ(0, cvtest::norm(targetBlob, blob, NORM_INF));
+}
+
 TEST(blobFromImageWithParams_4ch, letter_box)
 {
     Mat img(40, 20, CV_8UC4, cv::Scalar(0,1,2,3));