dnn(tflite): add 3rdparty flatbuffers with pre-generated schema

modules/dnn/CMakeLists.txt

@@ -127,23 +127,27 @@ else()
   set(fw_inc "${CMAKE_CURRENT_LIST_DIR}/misc/caffe" "${CMAKE_CURRENT_LIST_DIR}/misc/tensorflow" "${CMAKE_CURRENT_LIST_DIR}/misc/onnx")
 endif()
 
+ocv_option(OPENCV_DNN_TFLITE "Build with TFLite support" (TARGET ocv.3rdparty.flatbuffers))
+if(TARGET ocv.3rdparty.flatbuffers AND OPENCV_DNN_TFLITE)
+  if(NOT HAVE_FLATBUFFERS)
+    message(FATAL_ERROR "DNN: TFLite is not supported without enabled 'flatbuffers'. Check build configuration.")
+  endif()
+  list(APPEND libs ocv.3rdparty.flatbuffers)
+  list(APPEND fw_hdrs "${CMAKE_CURRENT_LIST_DIR}/misc/tflite/schema_generated.h")
+  list(APPEND fw_inc "${CMAKE_CURRENT_LIST_DIR}/misc/tflite")
+
+  # Schema is generated by this command:
+  #add_custom_command(
+  #      OUTPUT "${CMAKE_CURRENT_BINARY_DIR}/schema_generated.h"
+  #      COMMAND flatbuffers::flatc --cpp -o "${CMAKE_CURRENT_BINARY_DIR}" "${CMAKE_CURRENT_LIST_DIR}/src/tflite/schema.fbs")
+endif()
+
 list(APPEND include_dirs ${fw_inc})
 list(APPEND libs ${Protobuf_LIBRARIES})
 if(NOT BUILD_PROTOBUF)
   list(APPEND include_dirs ${Protobuf_INCLUDE_DIRS})
 endif()
 
-if(HAVE_FLATBUFFERS)
-  list(APPEND libs flatbuffers::flatbuffers)
-  list(APPEND fw_srcs "${CMAKE_CURRENT_BINARY_DIR}/schema_generated.h")
-
-  add_custom_command(
-        OUTPUT "${CMAKE_CURRENT_BINARY_DIR}/schema_generated.h"
-        COMMAND flatbuffers::flatc --cpp -o "${CMAKE_CURRENT_BINARY_DIR}" "${CMAKE_CURRENT_LIST_DIR}/src/tflite/schema.fbs")
-
-  ocv_target_compile_definitions(${the_module} PRIVATE "HAVE_FLATBUFFERS=1")
-endif()
-
 set(sources_options "")
 
 list(APPEND libs ${LAPACK_LIBRARIES})
@@ -232,6 +236,9 @@ if(TARGET ocv.3rdparty.openvino AND OPENCV_DNN_OPENVINO)
   endif()
 endif()
 
+
+ocv_install_used_external_targets(${libs} ${dnn_runtime_libs})
+
 ocv_glob_module_sources(${sources_options} SOURCES ${fw_srcs} ${webnn_srcs})
 ocv_create_module(${libs} ${dnn_runtime_libs})
 ocv_add_samples()
@@ -292,8 +299,12 @@ if(TARGET ocv.3rdparty.cann AND OPENCV_TEST_DNN_CANN)
   endif()
 endif()
 
-if(HAVE_FLATBUFFERS)
+ocv_option(OPENCV_TEST_DNN_TFLITE "Build test with TFLite" (OPENCV_DNN_TFLITE))
+if(OPENCV_TEST_DNN_TFLITE)
   if(TARGET opencv_test_dnn)
-    ocv_target_compile_definitions(opencv_test_dnn PRIVATE "HAVE_FLATBUFFERS=1")
+    ocv_target_compile_definitions(opencv_test_dnn PRIVATE "OPENCV_TEST_DNN_TFLITE=1")
+  endif()
+  if(TARGET opencv_perf_dnn)
+    ocv_target_compile_definitions(opencv_perf_dnn PRIVATE "OPENCV_TEST_DNN_TFLITE=1")
   endif()
 endif()

modules/dnn/src/tflite/tflite_importer.cpp

@@ -119,7 +119,7 @@ TFLiteImporter::TFLiteImporter(Net& dstNet, const char* modelBuffer, size_t bufS
     CV_Assert(model);
     CV_Assert(model->subgraphs());
     CV_Assert(model->buffers());
-    CV_CheckEQ(model->subgraphs()->size(), 1, "");
+    CV_CheckEQ((size_t)model->subgraphs()->size(), 1u, "");
 
     modelTensors = model->subgraphs()->Get(0)->tensors();
     CV_Assert(modelTensors);

modules/dnn/test/test_tflite_importer.cpp

@@ -12,17 +12,15 @@ Test for TFLite models loading
 #include <opencv2/dnn/layer.details.hpp>  // CV_DNN_REGISTER_LAYER_CLASS
 #include <opencv2/dnn/utils/debug_utils.hpp>
 
-namespace opencv_test
-{
+#ifdef OPENCV_TEST_DNN_TFLITE
+
+namespace opencv_test { namespace {
 
 using namespace cv;
 using namespace cv::dnn;
 
-void testModel(const std::string& modelName, const Mat& input, double norm = 1e-5) {
-#ifndef HAVE_FLATBUFFERS
-    throw SkipTestException("FlatBuffers required for TFLite importer");
-#endif
-
+void testModel(const std::string& modelName, const Mat& input, double l1 = 1e-5, double lInf = 1e-4)
+{
     Net net = readNet(findDataFile("dnn/tflite/" + modelName + ".tflite", false));
     net.setInput(input);
 
@@ -34,20 +32,21 @@ void testModel(const std::string& modelName, const Mat& input, double norm = 1e-
     ASSERT_EQ(outs.size(), outNames.size());
     for (int i = 0; i < outNames.size(); ++i) {
         Mat ref = blobFromNPY(findDataFile(format("dnn/tflite/%s_out_%s.npy", modelName.c_str(), outNames[i].c_str())));
-        normAssert(ref.reshape(1, 1), outs[i].reshape(1, 1), outNames[i].c_str(), norm);
+        normAssert(ref.reshape(1, 1), outs[i].reshape(1, 1), outNames[i].c_str(), l1, lInf);
     }
 }
 
-void testModel(const std::string& modelName, const Size& inpSize, double norm = 1e-5) {
+void testModel(const std::string& modelName, const Size& inpSize, double l1 = 1e-5, double lInf = 1e-4)
+{
     Mat input = imread(findDataFile("cv/shared/lena.png"));
     input = blobFromImage(input, 1.0 / 255, inpSize, 0, true);
-    testModel(modelName, input, norm);
+    testModel(modelName, input, l1, lInf);
 }
 
 // https://google.github.io/mediapipe/solutions/face_mesh
 TEST(Test_TFLite, face_landmark)
 {
-    testModel("face_landmark", Size(192, 192), 2e-5);
+    testModel("face_landmark", Size(192, 192), 2e-5, 2e-4);
 }
 
 // https://google.github.io/mediapipe/solutions/face_detection
@@ -64,9 +63,6 @@ TEST(Test_TFLite, selfie_segmentation)
 
 TEST(Test_TFLite, max_unpooling)
 {
-#ifndef HAVE_FLATBUFFERS
-    throw SkipTestException("FlatBuffers required for TFLite importer");
-#endif
     // Due Max Unpoling is a numerically unstable operation and small difference between frameworks
     // might lead to positional difference of maximal elements in the tensor, this test checks
     // behavior of Max Unpooling layer only.
@@ -120,4 +116,6 @@ TEST(Test_TFLite, max_unpooling)
     }
 }
 
-}
+}}  // namespace
+
+#endif  // OPENCV_TEST_DNN_TFLITE