Merge pull request #9994 from r2d3:dnn_memory_load

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

@@ -644,11 +644,33 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
       */
     CV_EXPORTS_W Net readNetFromCaffe(const String &prototxt, const String &caffeModel = String());
 
+    /** @brief Reads a network model stored in Caffe model in memory.
+      * @details This is an overloaded member function, provided for convenience.
+      * It differs from the above function only in what argument(s) it accepts.
+      * @param bufferProto buffer containing the content of the .prototxt file
+      * @param lenProto length of bufferProto
+      * @param bufferModel buffer containing the content of the .caffemodel file
+      * @param lenModel length of bufferModel
+      */
+    CV_EXPORTS Net readNetFromCaffe(const char *bufferProto, size_t lenProto,
+                                    const char *bufferModel = NULL, size_t lenModel = 0);
+
     /** @brief Reads a network model stored in Tensorflow model file.
       * @details This is shortcut consisting from createTensorflowImporter and Net::populateNet calls.
       */
     CV_EXPORTS_W Net readNetFromTensorflow(const String &model, const String &config = String());
 
+    /** @brief Reads a network model stored in Tensorflow model in memory.
+      * @details This is an overloaded member function, provided for convenience.
+      * It differs from the above function only in what argument(s) it accepts.
+      * @param bufferModel buffer containing the content of the pb file
+      * @param lenModel length of bufferModel
+      * @param bufferConfig buffer containing the content of the pbtxt file
+      * @param lenConfig length of bufferConfig
+      */
+    CV_EXPORTS Net readNetFromTensorflow(const char *bufferModel, size_t lenModel,
+                                         const char *bufferConfig = NULL, size_t lenConfig = 0);
+
     /** @brief Reads a network model stored in Torch model file.
       * @details This is shortcut consisting from createTorchImporter and Net::populateNet calls.
       */

modules/dnn/src/caffe/caffe_importer.cpp

@@ -92,6 +92,17 @@ public:
             ReadNetParamsFromBinaryFileOrDie(caffeModel, &netBinary);
     }
 
+    CaffeImporter(const char *dataProto, size_t lenProto,
+                  const char *dataModel, size_t lenModel)
+    {
+        CV_TRACE_FUNCTION();
+
+        ReadNetParamsFromTextBufferOrDie(dataProto, lenProto, &net);
+
+        if (dataModel != NULL && lenModel > 0)
+            ReadNetParamsFromBinaryBufferOrDie(dataModel, lenModel, &netBinary);
+    }
+
     void addParam(const Message &msg, const FieldDescriptor *field, cv::dnn::LayerParams &params)
     {
         const Reflection *refl = msg.GetReflection();
@@ -398,6 +409,15 @@ Net readNetFromCaffe(const String &prototxt, const String &caffeModel /*= String
     return net;
 }
 
+Net readNetFromCaffe(const char *bufferProto, size_t lenProto,
+                     const char *bufferModel, size_t lenModel)
+{
+    CaffeImporter caffeImporter(bufferProto, lenProto, bufferModel, lenModel);
+    Net net;
+    caffeImporter.populateNet(net);
+    return net;
+}
+
 #endif //HAVE_PROTOBUF
 
 CV__DNN_EXPERIMENTAL_NS_END

modules/dnn/src/caffe/caffe_io.cpp

@@ -1107,28 +1107,37 @@ const char* UpgradeV1LayerType(const V1LayerParameter_LayerType type) {
 
 const int kProtoReadBytesLimit = INT_MAX;  // Max size of 2 GB minus 1 byte.
 
+bool ReadProtoFromBinary(ZeroCopyInputStream* input, Message *proto) {
+    CodedInputStream coded_input(input);
+    coded_input.SetTotalBytesLimit(kProtoReadBytesLimit, 536870912);
+
+    return proto->ParseFromCodedStream(&coded_input);
+}
+
 bool ReadProtoFromTextFile(const char* filename, Message* proto) {
     std::ifstream fs(filename, std::ifstream::in);
     CHECK(fs.is_open()) << "Can't open \"" << filename << "\"";
     IstreamInputStream input(&fs);
-    bool success = google::protobuf::TextFormat::Parse(&input, proto);
+    return google::protobuf::TextFormat::Parse(&input, proto);
-    fs.close();
-    return success;
 }
 
 bool ReadProtoFromBinaryFile(const char* filename, Message* proto) {
     std::ifstream fs(filename, std::ifstream::in | std::ifstream::binary);
     CHECK(fs.is_open()) << "Can't open \"" << filename << "\"";
-    ZeroCopyInputStream* raw_input = new IstreamInputStream(&fs);
+    IstreamInputStream raw_input(&fs);
-    CodedInputStream* coded_input = new CodedInputStream(raw_input);
-    coded_input->SetTotalBytesLimit(kProtoReadBytesLimit, 536870912);
 
-    bool success = proto->ParseFromCodedStream(coded_input);
+    return ReadProtoFromBinary(&raw_input, proto);
+}
 
-    delete coded_input;
+bool ReadProtoFromTextBuffer(const char* data, size_t len, Message* proto) {
-    delete raw_input;
+    ArrayInputStream input(data, len);
-    fs.close();
+    return google::protobuf::TextFormat::Parse(&input, proto);
-    return success;
+}
+
+
+bool ReadProtoFromBinaryBuffer(const char* data, size_t len, Message* proto) {
+    ArrayInputStream raw_input(data, len);
+    return ReadProtoFromBinary(&raw_input, proto);
 }
 
 void ReadNetParamsFromTextFileOrDie(const char* param_file,
@@ -1138,6 +1147,13 @@ void ReadNetParamsFromTextFileOrDie(const char* param_file,
   UpgradeNetAsNeeded(param_file, param);
 }
 
+void ReadNetParamsFromTextBufferOrDie(const char* data, size_t len,
+                                      NetParameter* param) {
+  CHECK(ReadProtoFromTextBuffer(data, len, param))
+      << "Failed to parse NetParameter buffer";
+  UpgradeNetAsNeeded("memory buffer", param);
+}
+
 void ReadNetParamsFromBinaryFileOrDie(const char* param_file,
                                       NetParameter* param) {
   CHECK(ReadProtoFromBinaryFile(param_file, param))
@@ -1145,6 +1161,13 @@ void ReadNetParamsFromBinaryFileOrDie(const char* param_file,
   UpgradeNetAsNeeded(param_file, param);
 }
 
+void ReadNetParamsFromBinaryBufferOrDie(const char* data, size_t len,
+                                        NetParameter* param) {
+  CHECK(ReadProtoFromBinaryBuffer(data, len, param))
+      << "Failed to parse NetParameter buffer";
+  UpgradeNetAsNeeded("memory buffer", param);
+}
+
 }
 }
 #endif

modules/dnn/src/caffe/caffe_io.hpp

@@ -102,6 +102,18 @@ void ReadNetParamsFromTextFileOrDie(const char* param_file,
 void ReadNetParamsFromBinaryFileOrDie(const char* param_file,
                                       caffe::NetParameter* param);
 
+// Read parameters from a memory buffer into a NetParammeter proto message.
+void ReadNetParamsFromBinaryBufferOrDie(const char* data, size_t len,
+                                        caffe::NetParameter* param);
+void ReadNetParamsFromTextBufferOrDie(const char* data, size_t len,
+                                      caffe::NetParameter* param);
+
+// Utility functions used internally by Caffe and TensorFlow loaders
+bool ReadProtoFromTextFile(const char* filename, ::google::protobuf::Message* proto);
+bool ReadProtoFromBinaryFile(const char* filename, ::google::protobuf::Message* proto);
+bool ReadProtoFromTextBuffer(const char* data, size_t len, ::google::protobuf::Message* proto);
+bool ReadProtoFromBinaryBuffer(const char* data, size_t len, ::google::protobuf::Message* proto);
+
 }
 }
 #endif

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -449,6 +449,9 @@ void ExcludeLayer(tensorflow::GraphDef& net, const int layer_index, const int in
 class TFImporter : public Importer {
 public:
     TFImporter(const char *model, const char *config = NULL);
+    TFImporter(const char *dataModel, size_t lenModel,
+               const char *dataConfig = NULL, size_t lenConfig = 0);
+
     void populateNet(Net dstNet);
     ~TFImporter() {}
 
@@ -479,6 +482,15 @@ TFImporter::TFImporter(const char *model, const char *config)
         ReadTFNetParamsFromTextFileOrDie(config, &netTxt);
 }
 
+TFImporter::TFImporter(const char *dataModel, size_t lenModel,
+                       const char *dataConfig, size_t lenConfig)
+{
+    if (dataModel != NULL && lenModel > 0)
+        ReadTFNetParamsFromBinaryBufferOrDie(dataModel, lenModel, &netBin);
+    if (dataConfig != NULL && lenConfig > 0)
+        ReadTFNetParamsFromTextBufferOrDie(dataConfig, lenConfig, &netTxt);
+}
+
 void TFImporter::kernelFromTensor(const tensorflow::TensorProto &tensor, Mat &dstBlob)
 {
     MatShape shape;
@@ -1326,5 +1338,14 @@ Net readNetFromTensorflow(const String &model, const String &config)
     return net;
 }
 
+Net readNetFromTensorflow(const char* bufferModel, size_t lenModel,
+                          const char* bufferConfig, size_t lenConfig)
+{
+    TFImporter importer(bufferModel, lenModel, bufferConfig, lenConfig);
+    Net net;
+    importer.populateNet(net);
+    return net;
+}
+
 CV__DNN_EXPERIMENTAL_NS_END
 }} // namespace

modules/dnn/src/tensorflow/tf_io.cpp

@@ -23,6 +23,7 @@ Implementation of various functions which are related to Tensorflow models readi
 
 #include "graph.pb.h"
 #include "tf_io.hpp"
+#include "../caffe/caffe_io.hpp"
 #include "../caffe/glog_emulator.hpp"
 
 namespace cv {
@@ -36,41 +37,28 @@ using namespace ::google::protobuf::io;
 
 const int kProtoReadBytesLimit = INT_MAX;  // Max size of 2 GB minus 1 byte.
 
-// TODO: remove Caffe duplicate
-bool ReadProtoFromBinaryFileTF(const char* filename, Message* proto) {
-    std::ifstream fs(filename, std::ifstream::in | std::ifstream::binary);
-    CHECK(fs.is_open()) << "Can't open \"" << filename << "\"";
-    ZeroCopyInputStream* raw_input = new IstreamInputStream(&fs);
-    CodedInputStream* coded_input = new CodedInputStream(raw_input);
-    coded_input->SetTotalBytesLimit(kProtoReadBytesLimit, 536870912);
-
-    bool success = proto->ParseFromCodedStream(coded_input);
-
-    delete coded_input;
-    delete raw_input;
-    fs.close();
-    return success;
-}
-
-bool ReadProtoFromTextFileTF(const char* filename, Message* proto) {
-    std::ifstream fs(filename, std::ifstream::in);
-    CHECK(fs.is_open()) << "Can't open \"" << filename << "\"";
-    IstreamInputStream input(&fs);
-    bool success = google::protobuf::TextFormat::Parse(&input, proto);
-    fs.close();
-    return success;
-}
-
 void ReadTFNetParamsFromBinaryFileOrDie(const char* param_file,
-                                      tensorflow::GraphDef* param) {
+                                        tensorflow::GraphDef* param) {
-  CHECK(ReadProtoFromBinaryFileTF(param_file, param))
+    CHECK(ReadProtoFromBinaryFile(param_file, param))
-      << "Failed to parse GraphDef file: " << param_file;
+        << "Failed to parse GraphDef file: " << param_file;
+}
+
+void ReadTFNetParamsFromBinaryBufferOrDie(const char* data, size_t len,
+                                          tensorflow::GraphDef* param) {
+    CHECK(ReadProtoFromBinaryBuffer(data, len, param))
+        << "Failed to parse GraphDef buffer";
 }
 
 void ReadTFNetParamsFromTextFileOrDie(const char* param_file,
                                       tensorflow::GraphDef* param) {
-  CHECK(ReadProtoFromTextFileTF(param_file, param))
+    CHECK(ReadProtoFromTextFile(param_file, param))
-      << "Failed to parse GraphDef file: " << param_file;
+        << "Failed to parse GraphDef file: " << param_file;
+}
+
+void ReadTFNetParamsFromTextBufferOrDie(const char* data, size_t len,
+                                        tensorflow::GraphDef* param) {
+    CHECK(ReadProtoFromTextBuffer(data, len, param))
+        << "Failed to parse GraphDef buffer";
 }
 
 }

modules/dnn/src/tensorflow/tf_io.hpp

@@ -25,6 +25,13 @@ void ReadTFNetParamsFromBinaryFileOrDie(const char* param_file,
 void ReadTFNetParamsFromTextFileOrDie(const char* param_file,
                                       tensorflow::GraphDef* param);
 
+// Read parameters from a memory buffer into a GraphDef proto message.
+void ReadTFNetParamsFromBinaryBufferOrDie(const char* data, size_t len,
+                                          tensorflow::GraphDef* param);
+
+void ReadTFNetParamsFromTextBufferOrDie(const char* data, size_t len,
+                                        tensorflow::GraphDef* param);
+
 }
 }
 

modules/dnn/test/test_caffe_importer.cpp

@@ -55,6 +55,24 @@ static std::string _tf(TString filename)
     return (getOpenCVExtraDir() + "/dnn/") + filename;
 }
 
+TEST(Test_Caffe, memory_read)
+{
+    const string proto = findDataFile("dnn/bvlc_googlenet.prototxt", false);
+    const string model = findDataFile("dnn/bvlc_googlenet.caffemodel", false);
+
+    string dataProto;
+    ASSERT_TRUE(readFileInMemory(proto, dataProto));
+    string dataModel;
+    ASSERT_TRUE(readFileInMemory(model, dataModel));
+
+    Net net = readNetFromCaffe(dataProto.c_str(), dataProto.size());
+    ASSERT_FALSE(net.empty());
+
+    Net net2 = readNetFromCaffe(dataProto.c_str(), dataProto.size(),
+                                dataModel.c_str(), dataModel.size());
+    ASSERT_FALSE(net2.empty());
+}
+
 TEST(Test_Caffe, read_gtsrb)
 {
     Net net = readNetFromCaffe(_tf("gtsrb.prototxt"));
@@ -67,13 +85,26 @@ TEST(Test_Caffe, read_googlenet)
     ASSERT_FALSE(net.empty());
 }
 
-TEST(Reproducibility_AlexNet, Accuracy)
+typedef testing::TestWithParam<tuple<bool> > Reproducibility_AlexNet;
+TEST_P(Reproducibility_AlexNet, Accuracy)
 {
+    bool readFromMemory = get<0>(GetParam());
     Net net;
     {
         const string proto = findDataFile("dnn/bvlc_alexnet.prototxt", false);
         const string model = findDataFile("dnn/bvlc_alexnet.caffemodel", false);
-        net = readNetFromCaffe(proto, model);
+        if (readFromMemory)
+        {
+            string dataProto;
+            ASSERT_TRUE(readFileInMemory(proto, dataProto));
+            string dataModel;
+            ASSERT_TRUE(readFileInMemory(model, dataModel));
+
+            net = readNetFromCaffe(dataProto.c_str(), dataProto.size(),
+                                   dataModel.c_str(), dataModel.size());
+        }
+        else
+            net = readNetFromCaffe(proto, model);
         ASSERT_FALSE(net.empty());
     }
 
@@ -86,6 +117,8 @@ TEST(Reproducibility_AlexNet, Accuracy)
     normAssert(ref, out);
 }
 
+INSTANTIATE_TEST_CASE_P(Test_Caffe, Reproducibility_AlexNet, testing::Values(true, false));
+
 #if !defined(_WIN32) || defined(_WIN64)
 TEST(Reproducibility_FCN, Accuracy)
 {

modules/dnn/test/test_common.hpp

@@ -57,4 +57,23 @@ inline void normAssert(cv::InputArray ref, cv::InputArray test, const char *comm
     EXPECT_LE(normInf, lInf) << comment;
 }
 
+inline bool readFileInMemory(const std::string& filename, std::string& content)
+{
+    std::ios::openmode mode = std::ios::in | std::ios::binary;
+    std::ifstream ifs(filename.c_str(), mode);
+    if (!ifs.is_open())
+        return false;
+
+    content.clear();
+
+    ifs.seekg(0, std::ios::end);
+    content.reserve(ifs.tellg());
+    ifs.seekg(0, std::ios::beg);
+
+    content.assign((std::istreambuf_iterator<char>(ifs)),
+                   std::istreambuf_iterator<char>());
+
+    return true;
+}
+
 #endif

modules/dnn/test/test_tf_importer.cpp

@@ -75,14 +75,32 @@ static std::string path(const std::string& file)
 }
 
 static void runTensorFlowNet(const std::string& prefix, bool hasText = false,
-                             double l1 = 1e-5, double lInf = 1e-4)
+                             double l1 = 1e-5, double lInf = 1e-4,
+                             bool memoryLoad = false)
 {
     std::string netPath = path(prefix + "_net.pb");
     std::string netConfig = (hasText ? path(prefix + "_net.pbtxt") : "");
     std::string inpPath = path(prefix + "_in.npy");
     std::string outPath = path(prefix + "_out.npy");
 
-    Net net = readNetFromTensorflow(netPath, netConfig);
+    Net net;
+    if (memoryLoad)
+    {
+        // Load files into a memory buffers
+        string dataModel;
+        ASSERT_TRUE(readFileInMemory(netPath, dataModel));
+
+        string dataConfig;
+        if (hasText)
+            ASSERT_TRUE(readFileInMemory(netConfig, dataConfig));
+
+        net = readNetFromTensorflow(dataModel.c_str(), dataModel.size(),
+                                    dataConfig.c_str(), dataConfig.size());
+    }
+    else
+        net = readNetFromTensorflow(netPath, netConfig);
+
+    ASSERT_FALSE(net.empty());
 
     cv::Mat input = blobFromNPY(inpPath);
     cv::Mat target = blobFromNPY(outPath);
@@ -216,4 +234,15 @@ TEST(Test_TensorFlow, resize_nearest_neighbor)
     runTensorFlowNet("resize_nearest_neighbor");
 }
 
+TEST(Test_TensorFlow, memory_read)
+{
+    double l1 = 1e-5;
+    double lInf = 1e-4;
+    runTensorFlowNet("lstm", true, l1, lInf, true);
+
+    runTensorFlowNet("batch_norm", false, l1, lInf, true);
+    runTensorFlowNet("fused_batch_norm", false, l1, lInf, true);
+    runTensorFlowNet("batch_norm_text", true, l1, lInf, true);
+}
+
 }