Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

fix model diagnostic tool

Browse Source
pull/21357/head
rogday 3 years ago
parent a55950865e
commit 0fe7420638
6 changed files with 113 additions and 69 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 3
      modules/dnn/include/opencv2/dnn/layer.hpp
  2. 11
      modules/dnn/src/debug_utils.cpp
  3. 7
      modules/dnn/src/dnn.cpp
  4. 4
      modules/dnn/src/dnn_common.hpp
  5. 151
      modules/dnn/src/onnx/onnx_importer.cpp
  6. 6
      modules/dnn/src/tensorflow/tf_importer.cpp

3
modules/dnn/include/opencv2/dnn/layer.hpp
Unescape View File

@ -66,6 +66,9 @@ public:
//! Unregisters registered layer with specified type name. Thread-safe.
static void unregisterLayer(const String &type);
//! Check if layer is registered.
static bool isLayerRegistered(const std::string& type);
/** @brief Creates instance of registered layer.
* @param type type name of creating layer.
* @param params parameters which will be used for layer initialization.

11
modules/dnn/src/debug_utils.cpp
Unescape View File

@ -37,11 +37,8 @@ void skipModelImport(bool skip)
void detail::LayerHandler::addMissing(const std::string& name, const std::string& type)
{
cv::AutoLock lock(getLayerFactoryMutex());
auto& registeredLayers = getLayerFactoryImpl();
// If we didn't add it, but can create it, it's custom and not missing.
if (layers.find(type) == layers.end() && registeredLayers.find(type) != registeredLayers.end())
if (!contains(type) && LayerFactory::isLayerRegistered(type))
{
return;
}
@ -51,17 +48,17 @@ void detail::LayerHandler::addMissing(const std::string& name, const std::string
bool detail::LayerHandler::contains(const std::string& type) const
{
return layers.find(type) != layers.end();
return layers.count(type) != 0;
}
void detail::LayerHandler::printMissing()
void detail::LayerHandler::printMissing() const
{
if (layers.empty())
{
return;
}
std::stringstream ss;
std::ostringstream ss;
ss << "DNN: Not supported types:\n";
for (const auto& type_names : layers)
{

7
modules/dnn/src/dnn.cpp
Unescape View File

@ -6092,6 +6092,13 @@ void LayerFactory::unregisterLayer(const String &type)
}
}
bool LayerFactory::isLayerRegistered(const std::string& type)
{
cv::AutoLock lock(getLayerFactoryMutex());
auto& registeredLayers = getLayerFactoryImpl();
return registeredLayers.find(type) != registeredLayers.end();
}
Ptr<Layer> LayerFactory::createLayerInstance(const String &type, LayerParams& params)
{
CV_TRACE_FUNCTION();

4
modules/dnn/src/dnn_common.hpp
Unescape View File

@ -5,8 +5,8 @@
#ifndef __OPENCV_DNN_COMMON_HPP__
#define __OPENCV_DNN_COMMON_HPP__
#include <unordered_set>
#include <unordered_map>
#include <unordered_set>
#include <opencv2/dnn.hpp>
@ -59,7 +59,7 @@ class LayerHandler
public:
void addMissing(const std::string& name, const std::string& type);
bool contains(const std::string& type) const;
void printMissing();
void printMissing() const;
protected:
LayerParams getNotImplementedParams(const std::string& name, const std::string& op);

151
modules/dnn/src/onnx/onnx_importer.cpp
Unescape View File

@ -48,6 +48,8 @@ CV__DNN_INLINE_NS_BEGIN
extern bool DNN_DIAGNOSTICS_RUN;
class ONNXLayerHandler;
class ONNXImporter
{
opencv_onnx::ModelProto model_proto;
@ -80,7 +82,7 @@ public:
void populateNet();
protected:
std::unique_ptr<detail::LayerHandler> missingLayerHandler;
std::unique_ptr<ONNXLayerHandler> layerHandler;
Net& dstNet;
opencv_onnx::GraphProto graph_proto;
@ -98,11 +100,14 @@ protected:
void handleNode(const opencv_onnx::NodeProto& node_proto);
private:
friend class ONNXLayerHandler;
typedef void (ONNXImporter::*ONNXImporterNodeParser)(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
typedef std::map<std::string, ONNXImporterNodeParser> DispatchMap;
typedef std::map<std::string, DispatchMap> DomainDispatchMap;
DomainDispatchMap domain_dispatch_map;
std::string getLayerTypeDomain(const opencv_onnx::NodeProto& node_proto);
const DispatchMap& getDispatchMap(const opencv_onnx::NodeProto& node_proto);
void buildDispatchMap_ONNX_AI(int opset_version);
void buildDispatchMap_COM_MICROSOFT(int opset_version);
@ -156,6 +161,7 @@ private:
void parseSoftMax (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseDetectionOutput (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseCumSum (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseSimpleLayers (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
// Domain: com.microsoft
// URL: https://github.com/microsoft/onnxruntime/blob/master/docs/ContribOperators.md
@ -178,9 +184,38 @@ private:
const std::string str_domain_ai_onnx = "ai.onnx";
};
class ONNXLayerHandler : public detail::LayerHandler
{
public:
explicit ONNXLayerHandler(ONNXImporter* importer_);
void fillRegistry(const opencv_onnx::GraphProto& net);
protected:
ONNXImporter* importer;
};
ONNXLayerHandler::ONNXLayerHandler(ONNXImporter* importer_) : importer(importer_){}
void ONNXLayerHandler::fillRegistry(const opencv_onnx::GraphProto &net)
{
int layersSize = net.node_size();
for (int li = 0; li < layersSize; li++) {
const opencv_onnx::NodeProto &node_proto = net.node(li);
const std::string& name = node_proto.output(0);
const std::string& type = node_proto.op_type();
const std::string& layer_type_domain = importer->getLayerTypeDomain(node_proto);
const auto& dispatch = importer->getDispatchMap(node_proto);
if (dispatch.find(type) == dispatch.end())
{
addMissing(name, cv::format("%s.%s", layer_type_domain.c_str(), type.c_str()));
}
}
printMissing();
}
ONNXImporter::ONNXImporter(Net& net, const char *onnxFile)
: missingLayerHandler(DNN_DIAGNOSTICS_RUN ? new detail::LayerHandler() : nullptr)
: layerHandler(DNN_DIAGNOSTICS_RUN ? new ONNXLayerHandler(this) : nullptr)
, dstNet(net)
, onnx_opset(0)
{
@ -203,7 +238,7 @@ ONNXImporter::ONNXImporter(Net& net, const char *onnxFile)
}
ONNXImporter::ONNXImporter(Net& net, const char* buffer, size_t sizeBuffer)
: missingLayerHandler(DNN_DIAGNOSTICS_RUN ? new detail::LayerHandler() : nullptr)
: layerHandler(DNN_DIAGNOSTICS_RUN ? new ONNXLayerHandler(this) : nullptr)
, dstNet(net)
, onnx_opset(0)
{
@ -795,6 +830,7 @@ void ONNXImporter::populateNet()
if (DNN_DIAGNOSTICS_RUN) {
CV_LOG_INFO(NULL, "DNN/ONNX: start diagnostic run!");
layerHandler->fillRegistry(graph_proto);
}
for(int li = 0; li < layersSize; li++)
@ -806,54 +842,48 @@ void ONNXImporter::populateNet()
CV_LOG_DEBUG(NULL, (DNN_DIAGNOSTICS_RUN ? "DNN/ONNX: diagnostic run completed!" : "DNN/ONNX: import completed!"));
}
std::string ONNXImporter::getLayerTypeDomain(const opencv_onnx::NodeProto& node_proto)
{
if (!node_proto.has_domain())
return str_domain_ai_onnx;
const std::string& domain = node_proto.domain();
if (domain.empty())
return str_domain_ai_onnx;
return domain;
}
const ONNXImporter::DispatchMap& ONNXImporter::getDispatchMap(const opencv_onnx::NodeProto& node_proto)
{
static DispatchMap empty_map;
const std::string& layer_type_domain = getLayerTypeDomain(node_proto);
auto it = domain_dispatch_map.find(layer_type_domain);
if (it == domain_dispatch_map.end())
{
return empty_map;
}
return it->second;
}
void ONNXImporter::handleNode(const opencv_onnx::NodeProto& node_proto)
{
CV_Assert(node_proto.output_size() >= 1);
const std::string& name = node_proto.output(0);
const std::string& layer_type = node_proto.op_type();
const std::string& layer_type_domain = [&]()
{
if (!node_proto.has_domain())
return str_domain_ai_onnx;
const std::string& domain = node_proto.domain();
if (domain.empty())
return str_domain_ai_onnx;
return domain;
}();
const auto& dispatch = [&]()
const std::string& layer_type_domain = getLayerTypeDomain(node_proto);
const auto& dispatch = getDispatchMap(node_proto);
CV_LOG_DEBUG(NULL, "DNN/ONNX: processing node with " << node_proto.input_size() << " inputs and "
<< node_proto.output_size() << " outputs: "
<< cv::format("[%s]:(%s)", layer_type.c_str(), name.c_str())
<< cv::format(" from %sdomain='", onnx_opset_map.count(layer_type_domain) == 1 ? "" : "undeclared ")
<< layer_type_domain << "'"
);
if (dispatch.empty())
{
if (layer_type_domain != str_domain_ai_onnx)
{
if (onnx_opset_map.find(layer_type_domain) == onnx_opset_map.end())
{
CV_LOG_WARNING(NULL, "DNN/ONNX: processing node with " << node_proto.input_size() << " inputs and " << node_proto.output_size() << " outputs: "
<< cv::format("[%s]:(%s)", layer_type.c_str(), name.c_str())
<< " from undeclared domain='" << layer_type_domain << "'"
);
}
else
{
CV_LOG_DEBUG(NULL, "DNN/ONNX: processing node with " << node_proto.input_size() << " inputs and " << node_proto.output_size() << " outputs: "
<< cv::format("[%s]:(%s)", layer_type.c_str(), name.c_str())
<< " from domain='" << layer_type_domain << "'"
);
}
auto it = domain_dispatch_map.find(layer_type_domain);
if (it == domain_dispatch_map.end())
{
CV_LOG_WARNING(NULL, "DNN/ONNX: missing dispatch map for domain='" << layer_type_domain << "'");
return DispatchMap();
}
return it->second;
}
else
{
CV_LOG_DEBUG(NULL, "DNN/ONNX: processing node with " << node_proto.input_size() << " inputs and " << node_proto.output_size() << " outputs: "
<< cv::format("[%s]:(%s)", layer_type.c_str(), name.c_str())
);
return domain_dispatch_map[str_domain_ai_onnx];
}
}();
CV_LOG_WARNING(NULL, "DNN/ONNX: missing dispatch map for domain='" << layer_type_domain << "'");
}
LayerParams layerParams;
try
@ -2871,6 +2901,15 @@ void ONNXImporter::parseCumSum(LayerParams& layerParams, const opencv_onnx::Node
addLayer(layerParams, node_proto);
}
void ONNXImporter::parseSimpleLayers(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto)
{
for (int j = 0; j < node_proto.input_size(); j++) {
if (layer_id.find(node_proto.input(j)) == layer_id.end())
layerParams.blobs.push_back(getBlob(node_proto, j));
}
addLayer(layerParams, node_proto);
}
void ONNXImporter::parseCustomLayer(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto)
{
const std::string& name = layerParams.name;
@ -2886,20 +2925,11 @@ void ONNXImporter::parseCustomLayer(LayerParams& layerParams, const opencv_onnx:
}
}
CV_LOG_INFO(NULL, "DNN/ONNX: unknown node type, try using custom handler for node with " << node_proto.input_size() << " inputs and " << node_proto.output_size() << " outputs: "
CV_LOG_IF_INFO(NULL, !LayerFactory::isLayerRegistered(layer_type), "DNN/ONNX: unknown node type, try using custom handler for node with " << node_proto.input_size() << " inputs and " << node_proto.output_size() << " outputs: "
<< cv::format("[%s]:(%s)", layer_type.c_str(), name.c_str())
);
if (missingLayerHandler)
{
missingLayerHandler->addMissing(layerParams.name, layerParams.type);
}
for (int j = 0; j < node_proto.input_size(); j++) {
if (layer_id.find(node_proto.input(j)) == layer_id.end())
layerParams.blobs.push_back(getBlob(node_proto, j));
}
addLayer(layerParams, node_proto);
parseSimpleLayers(layerParams, node_proto);
}
void ONNXImporter::parseQuantDequant(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto)
@ -3349,6 +3379,15 @@ void ONNXImporter::buildDispatchMap_ONNX_AI(int opset_version)
dispatch["DetectionOutput"] = &ONNXImporter::parseDetectionOutput;
dispatch["CumSum"] = &ONNXImporter::parseCumSum;
std::vector<std::string> simpleLayers{"Acos", "Acosh", "Asin", "Asinh", "Atan", "Atanh", "Ceil", "Celu", "Cos",
"Cosh", "Dropout", "Erf", "Exp", "Floor", "HardSigmoid", "HardSwish",
"Identity", "Log", "Round", "Selu", "Sigmoid", "Sin", "Sinh", "Softmax",
"Softplus", "Softsign", "Sqrt", "Tan", "ThresholdedRelu"};
for (const auto& name : simpleLayers)
{
dispatch[name] = &ONNXImporter::parseSimpleLayers;
}
// ai.onnx: opset 10+
dispatch["QuantizeLinear"] = dispatch["DequantizeLinear"] = &ONNXImporter::parseQuantDequant;
dispatch["QLinearConv"] = &ONNXImporter::parseQConv;

6
modules/dnn/src/tensorflow/tf_importer.cpp
Unescape View File

@ -3090,10 +3090,8 @@ void TFImporter::populateNet()
{
const tensorflow::NodeDef& layer = net.node(li);
const std::string name = layer.name();
const std::string type = layer.op();
const int ninputs = layer.input_size();
CV_LOG_DEBUG(NULL, "DNN/TF: (" << li << "/" << layersSize << ") Parse layer " << name << " @ " << type << " with " << ninputs << " inputs");
CV_LOG_DEBUG(NULL, "DNN/TF: processing node (" << li << "/" << layersSize << ") with " << layer.input_size() << " inputs: "
<< cv::format("[%s]:(%s)", layer.op().c_str(), layer.name().c_str()));
parseNode(layer);
}

Write Preview
Loading…
Cancel
Save