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Merge pull request #29227 from omrope79:object_detect_changes

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Update BarcodeDetector super-resolution API to use single-file ONNX #29227

### Pull Request Readiness Checklist

This PR updates the `BarcodeDetector` super-resolution API to support and utilize a single-file ONNX model format. 

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
- [x] 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
This commit is contained in:
omrope79
2026-06-05 10:30:41 +05:30
committed by GitHub
parent 35ac66291f
commit ada32973b4
5 changed files with 48 additions and 22 deletions
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doc/tutorials/objdetect/barcode_detect_and_decode/barcode_detect_and_decode.markdown
+1 -1
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@@ -33,7 +33,7 @@ While coding, we firstly need to create a cv::barcode::BarcodeDetector object. I
#### Initialization
Optionally user can construct barcode detector with super resolution model which should be downloaded from https://github.com/WeChatCV/opencv_3rdparty/tree/wechat_qrcode (`sr.caffemodel`, `sr.prototxt`).
Optionally user can construct barcode detector with a super resolution model, passed as a single-file ONNX network (`sr.onnx`). A converted model can be downloaded from https://github.com/WeChatCV/opencv_3rdparty/tree/wechat_qrcode. Caffe models (`sr.prototxt` / `sr.caffemodel`) are no longer supported.
@snippet cpp/barcode.cpp initialize
modules/objdetect/include/opencv2/objdetect/barcode.hpp
+12 -6
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@@ -18,16 +18,22 @@ namespace barcode {
class CV_EXPORTS_W_SIMPLE BarcodeDetector : public cv::GraphicalCodeDetector
{
public:
/** @brief Initialize the BarcodeDetector.
/** @brief Initialize the BarcodeDetector. Super resolution is disabled.
*/
CV_WRAP BarcodeDetector();
/** @brief Initialize the BarcodeDetector.
/** @brief Initialize the BarcodeDetector with a Super Resolution model.
*
* Parameters allow to load _optional_ Super Resolution DNN model for better quality.
* @param prototxt_path prototxt file path for the super resolution model
* @param model_path model file path for the super resolution model
* Loads a Super Resolution DNN model in ONNX format, used to upscale small/low-quality
* barcode crops before decoding for better quality.
*
* @note Caffe models (`sr.prototxt` / `sr.caffemodel`) are no longer supported; convert
* the model to ONNX (a converted `sr.onnx` is available from
* https://github.com/WeChatCV/opencv_3rdparty/tree/wechat_qrcode).
*
* @param super_resolution_model_path path to a single-file ONNX Super Resolution model.
*/
CV_WRAP BarcodeDetector(CV_WRAP_FILE_PATH const std::string &prototxt_path, CV_WRAP_FILE_PATH const std::string &model_path);
CV_WRAP BarcodeDetector(CV_WRAP_FILE_PATH const std::string &super_resolution_model_path);
~BarcodeDetector();
/** @brief Decodes barcode in image once it's found by the detect() method.
modules/objdetect/src/barcode.cpp
+7 -8
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@@ -339,22 +339,21 @@ bool BarcodeImpl::detectAndDecodeMulti(InputArray img, vector<string> &decoded_i
// Public class implementation
BarcodeDetector::BarcodeDetector()
: BarcodeDetector(string(), string())
: BarcodeDetector(std::string())
{
}
BarcodeDetector::BarcodeDetector(const string &prototxt_path, const string &model_path)
BarcodeDetector::BarcodeDetector(const string &super_resolution_model_path)
{
Ptr<BarcodeImpl> p_ = new BarcodeImpl();
p = p_;
p_->sr = make_shared<SuperScale>();
// The Super Resolution model is now a single-file ONNX network; the legacy Caffe
// prototxt argument is retained for API compatibility but is no longer used.
CV_UNUSED(prototxt_path);
if (!model_path.empty())
// The optional Super Resolution model is a single-file ONNX network (Caffe support
// has been removed). An empty path simply disables super resolution.
if (!super_resolution_model_path.empty())
{
CV_Assert(utils::fs::exists(model_path));
int res = p_->sr->init(model_path);
CV_Assert(utils::fs::exists(super_resolution_model_path));
int res = p_->sr->init(super_resolution_model_path);
CV_Assert(res == 0);
p_->use_nn_sr = true;
}
modules/objdetect/test/test_barcode.cpp
+23
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@@ -227,4 +227,27 @@ TEST(BarcodeDetector_parameters, invalid)
EXPECT_ANY_THROW(bardet.setGradientThreshold(-0.1));
}
TEST(BarcodeDetector_super_resolution, accuracy)
{
// Reuse the existing WeChat Super Resolution ONNX model shipped in opencv_extra.
const string sr_path = findDataFile("dnn/wechat_2021-01/sr.onnx", false);
if (sr_path.empty())
throw SkipTestException("Missing super resolution model (dnn/wechat_2021-01/sr.onnx)");
const string fname = "single/book.jpg";
const string image_path = findDataFile("barcode/" + fname);
Mat img = imread(image_path);
ASSERT_FALSE(img.empty()) << "Can't read image: " << image_path;
// Construct with the ONNX super resolution model enabled.
barcode::BarcodeDetector det(sr_path);
vector<string> lines, types;
vector<Point2f> points;
bool res = det.detectAndDecodeWithType(img, lines, types, points);
ASSERT_TRUE(res);
EXPECT_EQ(toSet(testResults[fname].type), toSet(types));
EXPECT_EQ(toSet(testResults[fname].data), toSet(lines));
}
}} // opencv_test::<anonymous>::
samples/cpp/barcode.cpp
+5 -7
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@@ -175,8 +175,7 @@ int main(int argc, char **argv)
"{i in | | input image path (also switches to image detection mode) }"
"{detect | false | detect 1D barcode only (skip decoding) }"
"{o out | | path to result file (only for single image decode) }"
"{sr_prototxt| | super resolution prototxt path }"
"{sr_model | | super resolution model path }";
"{sr_model | | optional super resolution ONNX model path (e.g. sr.onnx) }";
CommandLineParser cmd_parser(argc, argv, keys);
cmd_parser.about("This program detects the 1D barcodes from camera or images using the OpenCV library.");
if (cmd_parser.has("help"))
@@ -186,7 +185,6 @@ int main(int argc, char **argv)
}
const string in_file = cmd_parser.get<string>("in");
const string out_file = cmd_parser.get<string>("out");
const string sr_prototxt = cmd_parser.get<string>("sr_prototxt");
const string sr_model = cmd_parser.get<string>("sr_model");
if (!cmd_parser.check())
{
@@ -199,17 +197,17 @@ int main(int argc, char **argv)
//! [initialize]
try
{
app.bardet = makePtr<barcode::BarcodeDetector>(sr_prototxt, sr_model);
app.bardet = makePtr<barcode::BarcodeDetector>(sr_model);
}
catch (const std::exception& e)
{
cout <<
"\n---------------------------------------------------------------\n"
"Failed to initialize super resolution.\n"
"Please, download 'sr.*' from\n"
"Please, download 'sr.onnx' from\n"
"https://github.com/WeChatCV/opencv_3rdparty/tree/wechat_qrcode\n"
"and put them into the current directory.\n"
"Or you can leave sr_prototxt and sr_model unspecified.\n"
"and put it into the current directory.\n"
"Or you can leave sr_model unspecified.\n"
"---------------------------------------------------------------\n";
cout << e.what() << endl;
return -1;