From 674c618471f2f7c57d6ca51a6638667864b6ebc8 Mon Sep 17 00:00:00 2001
From: CSBVision <bjoern.boeken@csb.com>
Date: Tue, 8 Aug 2023 13:31:32 +0200
Subject: [PATCH] Update dnn_utils.cpp
---
modules/dnn/src/dnn_utils.cpp | 65 ++++++++++++++++++++--------------
modules/dnn/test/test_misc.cpp | 22 ++++++++++++
2 files changed, 60 insertions(+), 27 deletions(-)
diff --git a/modules/dnn/src/dnn_utils.cpp b/modules/dnn/src/dnn_utils.cpp
index 18c7e975eb..d4d7dda008 100644
--- a/modules/dnn/src/dnn_utils.cpp
+++ b/modules/dnn/src/dnn_utils.cpp
@@ -5,6 +5,7 @@
#include "precomp.hpp"
#include <opencv2/imgproc.hpp>
+#include <opencv2/core/utils/logger.hpp>
namespace cv {
@@ -100,13 +101,27 @@ void blobFromImagesWithParams(InputArrayOfArrays images_, OutputArray blob_, con
images_.getMatVector(images);
CV_Assert(!images.empty());
+ if (param.ddepth == CV_8U)
+ {
+ CV_Assert(param.scalefactor == Scalar::all(1.0) && "Scaling is not supported for CV_8U blob depth");
+ CV_Assert(param.mean == Scalar() && "Mean subtraction is not supported for CV_8U blob depth");
+ }
+
int nch = images[0].channels();
Scalar scalefactor = param.scalefactor;
+ Scalar mean = param.mean;
- if (param.ddepth == CV_8U)
+ if (param.swapRB)
{
- CV_Assert(scalefactor == Scalar::all(1.0) && "Scaling is not supported for CV_8U blob depth");
- CV_Assert(param.mean == Scalar() && "Mean subtraction is not supported for CV_8U blob depth");
+ if (nch > 2)
+ {
+ std::swap(mean[0], mean[2]);
+ std::swap(scalefactor[0], scalefactor[2]);
+ }
+ else
+ {
+ CV_LOG_WARNING(NULL, "Red/blue color swapping requires at least three image channels.");
+ }
}
for (size_t i = 0; i < images.size(); i++)
@@ -126,34 +141,26 @@ void blobFromImagesWithParams(InputArrayOfArrays images_, OutputArray blob_, con
size);
images[i] = images[i](crop);
}
+ else if (param.paddingmode == DNN_PMODE_LETTERBOX)
+ {
+ float resizeFactor = std::min(size.width / (float)imgSize.width,
+ size.height / (float)imgSize.height);
+ int rh = int(imgSize.height * resizeFactor);
+ int rw = int(imgSize.width * resizeFactor);
+ resize(images[i], images[i], Size(rw, rh), INTER_LINEAR);
+
+ int top = (size.height - rh)/2;
+ 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);
+ }
else
{
- if (param.paddingmode == DNN_PMODE_LETTERBOX)
- {
- float resizeFactor = std::min(size.width / (float)imgSize.width,
- size.height / (float)imgSize.height);
- int rh = int(imgSize.height * resizeFactor);
- int rw = int(imgSize.width * resizeFactor);
- resize(images[i], images[i], Size(rw, rh), INTER_LINEAR);
-
- int top = (size.height - rh)/2;
- 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);
- }
- else
- resize(images[i], images[i], size, 0, 0, INTER_LINEAR);
+ resize(images[i], images[i], size, 0, 0, INTER_LINEAR);
}
}
- Scalar mean = param.mean;
- if (param.swapRB)
- {
- std::swap(mean[0], mean[2]);
- std::swap(scalefactor[0], scalefactor[2]);
- }
-
if (images[i].depth() == CV_8U && param.ddepth == CV_32F)
images[i].convertTo(images[i], CV_32F);
@@ -220,18 +227,22 @@ void blobFromImagesWithParams(InputArrayOfArrays images_, OutputArray blob_, con
CV_Assert(image.depth() == blob_.depth());
CV_Assert(image.channels() == image0.channels());
CV_Assert(image.size() == image0.size());
- if (param.swapRB)
+ if (nch > 2 && param.swapRB)
{
Mat tmpRB;
cvtColor(image, tmpRB, COLOR_BGR2RGB);
tmpRB.copyTo(Mat(tmpRB.rows, tmpRB.cols, subMatType, blob.ptr((int)i, 0)));
}
else
+ {
image.copyTo(Mat(image.rows, image.cols, subMatType, blob.ptr((int)i, 0)));
+ }
}
}
else
+ {
CV_Error(Error::StsUnsupportedFormat, "Unsupported data layout in blobFromImagesWithParams function.");
+ }
}
void imagesFromBlob(const cv::Mat& blob_, OutputArrayOfArrays images_)
diff --git a/modules/dnn/test/test_misc.cpp b/modules/dnn/test/test_misc.cpp
index 4ee3e013cb..0c5fb28c5d 100644
--- a/modules/dnn/test/test_misc.cpp
+++ b/modules/dnn/test/test_misc.cpp
@@ -120,6 +120,28 @@ TEST(blobFromImageWithParams_4ch, letter_box)
EXPECT_EQ(0, cvtest::norm(targetBlob, blob, NORM_INF));
}
+TEST(blobFromImagesWithParams_4ch, multi_image)
+{
+ Mat img(10, 10, CV_8UC4, cv::Scalar(0, 1, 2, 3));
+ Scalar scalefactor(0.1, 0.2, 0.3, 0.4);
+
+ Image2BlobParams param;
+ param.scalefactor = scalefactor;
+ param.datalayout = DNN_LAYOUT_NHWC;
+
+ Mat blobs = blobFromImagesWithParams(std::vector<Mat> { img, 2*img }, param);
+ vector<Range> ranges;
+ ranges.push_back(Range(0, 1));
+ ranges.push_back(Range(0, blobs.size[1]));
+ ranges.push_back(Range(0, blobs.size[2]));
+ ranges.push_back(Range(0, blobs.size[3]));
+ Mat blob0 = blobs(ranges);
+ ranges[0] = Range(1, 2);
+ Mat blob1 = blobs(ranges);
+
+ EXPECT_EQ(0, cvtest::norm(2*blob0, blob1, NORM_INF));
+}
+
TEST(readNet, Regression)
{
Net net = readNet(findDataFile("dnn/squeezenet_v1.1.prototxt"),