Merge pull request #9835 from sovrasov:blob_from_img_crop_opt

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

@@ -695,12 +695,14 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
      *  @param scalefactor multiplier for @p image values.
      *  @param swapRB flag which indicates that swap first and last channels
      *  in 3-channel image is necessary.
-     *  @details input image is resized so one side after resize is equal to corresponing
+     *  @param crop flag which indicates whether image will be cropped after resize or not
+     *  @details if @p crop is true, input image is resized so one side after resize is equal to corresponing
      *  dimension in @p size and another one is equal or larger. Then, crop from the center is performed.
+     *  If @p crop is false, direct resize without cropping and preserving aspect ratio is performed.
      *  @returns 4-dimansional Mat with NCHW dimensions order.
      */
     CV_EXPORTS_W Mat blobFromImage(const Mat& image, double scalefactor=1.0, const Size& size = Size(),
-                                   const Scalar& mean = Scalar(), bool swapRB=true);
+                                   const Scalar& mean = Scalar(), bool swapRB=true, bool crop=true);
     /** @brief Creates 4-dimensional blob from series of images. Optionally resizes and
      *  crops @p images from center, subtract @p mean values, scales values by @p scalefactor,
      *  swap Blue and Red channels.
@@ -711,12 +713,14 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
      *  @param scalefactor multiplier for @p images values.
      *  @param swapRB flag which indicates that swap first and last channels
      *  in 3-channel image is necessary.
-     *  @details input image is resized so one side after resize is equal to corresponing
+     *  @param crop flag which indicates whether image will be cropped after resize or not
+     *  @details if @p crop is true, input image is resized so one side after resize is equal to corresponing
      *  dimension in @p size and another one is equal or larger. Then, crop from the center is performed.
+     *  If @p crop is false, direct resize without cropping and preserving aspect ratio is performed.
      *  @returns 4-dimansional Mat with NCHW dimensions order.
      */
     CV_EXPORTS_W Mat blobFromImages(const std::vector<Mat>& images, double scalefactor=1.0,
-                                    Size size = Size(), const Scalar& mean = Scalar(), bool swapRB=true);
+                                    Size size = Size(), const Scalar& mean = Scalar(), bool swapRB=true, bool crop=true);
 
     /** @brief Convert all weights of Caffe network to half precision floating point.
      * @param src Path to origin model from Caffe framework contains single

modules/dnn/src/dnn.cpp

@@ -85,15 +85,15 @@ static String toString(const T &v)
 }
 
 Mat blobFromImage(const Mat& image, double scalefactor, const Size& size,
-                  const Scalar& mean, bool swapRB)
+                  const Scalar& mean, bool swapRB, bool crop)
 {
     CV_TRACE_FUNCTION();
     std::vector<Mat> images(1, image);
-    return blobFromImages(images, scalefactor, size, mean, swapRB);
+    return blobFromImages(images, scalefactor, size, mean, swapRB, crop);
 }
 
 Mat blobFromImages(const std::vector<Mat>& images_, double scalefactor, Size size,
-                   const Scalar& mean_, bool swapRB)
+                   const Scalar& mean_, bool swapRB, bool crop)
 {
     CV_TRACE_FUNCTION();
     std::vector<Mat> images = images_;
@@ -103,6 +103,8 @@ Mat blobFromImages(const std::vector<Mat>& images_, double scalefactor, Size siz
         if (size == Size())
             size = imgSize;
         if (size != imgSize)
+        {
+            if(crop)
             {
               float resizeFactor = std::max(size.width / (float)imgSize.width,
                                             size.height / (float)imgSize.height);
@@ -112,6 +114,9 @@ Mat blobFromImages(const std::vector<Mat>& images_, double scalefactor, Size siz
                         size);
               images[i] = images[i](crop);
             }
+            else
+              resize(images[i], images[i], size);
+        }
         if(images[i].depth() == CV_8U)
             images[i].convertTo(images[i], CV_32F);
         Scalar mean = mean_;