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Merge branch 4.x

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This commit is contained in:
Alexander Smorkalov
2024-01-23 17:06:52 +03:00
parent d6424233f0 69772b0260
commit decf6538a2
148 changed files with 3263 additions and 1564 deletions
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modules/dnn/include/opencv2/dnn/all_layers.hpp
+5
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@@ -1183,6 +1183,11 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<AttentionLayer> create(const LayerParams &params);
};
class CV_EXPORTS GroupNormLayer : public Layer {
public:
static Ptr<GroupNormLayer> create(const LayerParams &params);
};
//! @}
//! @}
CV__DNN_INLINE_NS_END
modules/dnn/include/opencv2/dnn/dnn.hpp
+20 -20
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@@ -444,7 +444,7 @@ CV__DNN_INLINE_NS_BEGIN
* Networks imported from Intel's Model Optimizer are launched in Intel's Inference Engine
* backend.
*/
CV_WRAP static Net readFromModelOptimizer(const String& xml, const String& bin);
CV_WRAP static Net readFromModelOptimizer(CV_WRAP_FILE_PATH const String& xml, CV_WRAP_FILE_PATH const String& bin);
/** @brief Create a network from Intel's Model Optimizer in-memory buffers with intermediate representation (IR).
* @param[in] bufferModelConfig buffer with model's configuration.
@@ -477,7 +477,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param path path to output file with .dot extension
* @see dump()
*/
CV_WRAP void dumpToFile(const String& path);
CV_WRAP void dumpToFile(CV_WRAP_FILE_PATH const String& path);
/** @brief Adds new layer to the net.
* @param name unique name of the adding layer.
* @param type typename of the adding layer (type must be registered in LayerRegister).
@@ -839,7 +839,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param darknetModel path to the .weights file with learned network.
* @returns Network object that ready to do forward, throw an exception in failure cases.
*/
CV_EXPORTS_W Net readNetFromDarknet(const String &cfgFile, const String &darknetModel = String());
CV_EXPORTS_W Net readNetFromDarknet(CV_WRAP_FILE_PATH const String &cfgFile, CV_WRAP_FILE_PATH const String &darknetModel = String());
/** @brief Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.
* @param bufferCfg A buffer contains a content of .cfg file with text description of the network architecture.
@@ -864,7 +864,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param caffeModel path to the .caffemodel file with learned network.
* @returns Net object.
*/
CV_EXPORTS_W Net readNetFromCaffe(const String &prototxt, const String &caffeModel = String());
CV_EXPORTS_W Net readNetFromCaffe(CV_WRAP_FILE_PATH const String &prototxt, CV_WRAP_FILE_PATH const String &caffeModel = String());
/** @brief Reads a network model stored in Caffe model in memory.
* @param bufferProto buffer containing the content of the .prototxt file
@@ -893,7 +893,7 @@ CV__DNN_INLINE_NS_BEGIN
* let us make it more flexible.
* @returns Net object.
*/
CV_EXPORTS_W Net readNetFromTensorflow(const String &model, const String &config = String());
CV_EXPORTS_W Net readNetFromTensorflow(CV_WRAP_FILE_PATH const String &model, CV_WRAP_FILE_PATH const String &config = String());
/** @brief Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.
* @param bufferModel buffer containing the content of the pb file
@@ -918,7 +918,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param model path to the .tflite file with binary flatbuffers description of the network architecture
* @returns Net object.
*/
CV_EXPORTS_W Net readNetFromTFLite(const String &model);
CV_EXPORTS_W Net readNetFromTFLite(CV_WRAP_FILE_PATH const String &model);
/** @brief Reads a network model stored in <a href="https://www.tensorflow.org/lite">TFLite</a> framework's format.
* @param bufferModel buffer containing the content of the tflite file
@@ -957,7 +957,7 @@ CV__DNN_INLINE_NS_BEGIN
* or @ref readNetFromDarknet. An order of @p model and @p config
* arguments does not matter.
*/
CV_EXPORTS_W Net readNet(const String& model, const String& config = "", const String& framework = "");
CV_EXPORTS_W Net readNet(CV_WRAP_FILE_PATH const String& model, CV_WRAP_FILE_PATH const String& config = "", const String& framework = "");
/**
* @brief Read deep learning network represented in one of the supported formats.
@@ -979,7 +979,7 @@ CV__DNN_INLINE_NS_BEGIN
* backend.
*/
CV_EXPORTS_W
Net readNetFromModelOptimizer(const String &xml, const String &bin = "");
Net readNetFromModelOptimizer(CV_WRAP_FILE_PATH const String &xml, CV_WRAP_FILE_PATH const String &bin = "");
/** @brief Load a network from Intel's Model Optimizer intermediate representation.
* @param[in] bufferModelConfig Buffer contains XML configuration with network's topology.
@@ -1008,7 +1008,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param onnxFile path to the .onnx file with text description of the network architecture.
* @returns Network object that ready to do forward, throw an exception in failure cases.
*/
CV_EXPORTS_W Net readNetFromONNX(const String &onnxFile);
CV_EXPORTS_W Net readNetFromONNX(CV_WRAP_FILE_PATH const String &onnxFile);
/** @brief Reads a network model from <a href="https://onnx.ai/">ONNX</a>
* in-memory buffer.
@@ -1031,7 +1031,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param path to the .pb file with input tensor.
* @returns Mat.
*/
CV_EXPORTS_W Mat readTensorFromONNX(const String& path);
CV_EXPORTS_W Mat readTensorFromONNX(CV_WRAP_FILE_PATH const String& path);
/** @brief Creates 4-dimensional blob from image. Optionally resizes and crops @p image from center,
* subtract @p mean values, scales values by @p scalefactor, swap Blue and Red channels.
@@ -1204,7 +1204,7 @@ CV__DNN_INLINE_NS_BEGIN
* is taken from NVidia's Caffe fork: https://github.com/NVIDIA/caffe.
* So the resulting model may be used there.
*/
CV_EXPORTS_W void shrinkCaffeModel(const String& src, const String& dst,
CV_EXPORTS_W void shrinkCaffeModel(CV_WRAP_FILE_PATH const String& src, CV_WRAP_FILE_PATH const String& dst,
const std::vector<String>& layersTypes = std::vector<String>());
/** @brief Create a text representation for a binary network stored in protocol buffer format.
@@ -1213,7 +1213,7 @@ CV__DNN_INLINE_NS_BEGIN
*
* @note To reduce output file size, trained weights are not included.
*/
CV_EXPORTS_W void writeTextGraph(const String& model, const String& output);
CV_EXPORTS_W void writeTextGraph(CV_WRAP_FILE_PATH const String& model, CV_WRAP_FILE_PATH const String& output);
/** @brief Performs non maximum suppression given boxes and corresponding scores.
@@ -1318,7 +1318,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param[in] model Binary file contains trained weights.
* @param[in] config Text file contains network configuration.
*/
CV_WRAP Model(const String& model, const String& config = "");
CV_WRAP Model(CV_WRAP_FILE_PATH const String& model, CV_WRAP_FILE_PATH const String& config = "");
/**
* @brief Create model from deep learning network.
@@ -1423,7 +1423,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param[in] model Binary file contains trained weights.
* @param[in] config Text file contains network configuration.
*/
CV_WRAP ClassificationModel(const String& model, const String& config = "");
CV_WRAP ClassificationModel(CV_WRAP_FILE_PATH const String& model, CV_WRAP_FILE_PATH const String& config = "");
/**
* @brief Create model from deep learning network.
@@ -1473,7 +1473,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param[in] model Binary file contains trained weights.
* @param[in] config Text file contains network configuration.
*/
CV_WRAP KeypointsModel(const String& model, const String& config = "");
CV_WRAP KeypointsModel(CV_WRAP_FILE_PATH const String& model, CV_WRAP_FILE_PATH const String& config = "");
/**
* @brief Create model from deep learning network.
@@ -1505,7 +1505,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param[in] model Binary file contains trained weights.
* @param[in] config Text file contains network configuration.
*/
CV_WRAP SegmentationModel(const String& model, const String& config = "");
CV_WRAP SegmentationModel(CV_WRAP_FILE_PATH const String& model, CV_WRAP_FILE_PATH const String& config = "");
/**
* @brief Create model from deep learning network.
@@ -1536,7 +1536,7 @@ CV__DNN_INLINE_NS_BEGIN
* @param[in] model Binary file contains trained weights.
* @param[in] config Text file contains network configuration.
*/
CV_WRAP DetectionModel(const String& model, const String& config = "");
CV_WRAP DetectionModel(CV_WRAP_FILE_PATH const String& model, CV_WRAP_FILE_PATH const String& config = "");
/**
* @brief Create model from deep learning network.
@@ -1602,7 +1602,7 @@ public:
* @param[in] config Text file contains network configuration
*/
CV_WRAP inline
TextRecognitionModel(const std::string& model, const std::string& config = "")
TextRecognitionModel(CV_WRAP_FILE_PATH const std::string& model, CV_WRAP_FILE_PATH const std::string& config = "")
: TextRecognitionModel(readNet(model, config)) { /* nothing */ }
/**
@@ -1757,7 +1757,7 @@ public:
* @param[in] config Text file contains network configuration.
*/
CV_WRAP inline
TextDetectionModel_EAST(const std::string& model, const std::string& config = "")
TextDetectionModel_EAST(CV_WRAP_FILE_PATH const std::string& model, CV_WRAP_FILE_PATH const std::string& config = "")
: TextDetectionModel_EAST(readNet(model, config)) { /* nothing */ }
/**
@@ -1818,7 +1818,7 @@ public:
* @param[in] config Text file contains network configuration.
*/
CV_WRAP inline
TextDetectionModel_DB(const std::string& model, const std::string& config = "")
TextDetectionModel_DB(CV_WRAP_FILE_PATH const std::string& model, CV_WRAP_FILE_PATH const std::string& config = "")
: TextDetectionModel_DB(readNet(model, config)) { /* nothing */ }
CV_WRAP TextDetectionModel_DB& setBinaryThreshold(float binaryThreshold);