Tensorflow Lite c++ Build

I have already put a question about the access violation of the TensorFlow lite c++ API. No one answered it so far, I believe the error I made is with selecting the wrong header- and library files from the Bazel build.

The steps that I have done to get the Tensorflow Lite Header and Libraries are from Youtube Tutorial and from Tensorflow.

1. Get Required Python (for me Python 3.9.5)
2. Install required Packages locally
3. Install Bazel (for me 3.7.2) and MSYS2 (after installation run pacman -S git patch unzip) and add it to Path
4. Check VS Build Tools 2019 for C++ (I have VS 19 Community with MSVC v142 & Windows 10 SDK)
5. Download and Unzip Tensorflow Sources from Github (Release of 2.5.3)
6. Inside the Tensorflow Sources, use python .\configure.py to start configure the bazel build (I only used Yes for override eigen strong inline, the rest is kept on the default value)
7. The I opened GitBash cmd inside the tensorflow source bazel build -c opt //tensorflow/lite:tensorflowlite
8. After a successful build later I get the "bazel-bin", "bazel-out", "bazel-tensorflow-2.5.3" and "bazel-testlogs" folder.
9. I created the following folders tensorflow/include/tensorflow/lite & core and tensorflow/include/flatbuffers for the headers and finally the tensorflow/lib for the libraries.
10. I copied the tensorflowlite.dll & tensorflow.dll.if.lib from the build directory (tensorflow-2.5.3\bazel-bin\tensorflow\lite) into the tensorflow/lib directory together with the flatbuffers.lib (from tensorflow-2.5.3\bazel-bin\external\flatbuffers\src)
11. I copied the tensorflow-2.5.3\bazel-bin\external\flatbuffers\src_virtual_includes\flatbuffers\flatbuffers headers into the tensorflow/include/flatbuffers directory
12. I copied the tensorflow-2.5.3\tensorflow\lite and tensorflow-2.5.3\tensorflow\core from the original sources into the tensorflow/include/tensorflow/lite & core directory.

After those steps, I could create a new VS Project and add the created linker and include information. And created the following short example to read the input layer.

#include "tensorflow/lite/interpreter.h"
#include "tensorflow/lite/kernels/register.h"
#include "tensorflow/lite/model.h"
#include "tensorflow/lite/optional_debug_tools.h"

#define TFLITE_MINIMAL_CHECK(x)                                  \
    if (!(x))                                                    \
    {                                                            \
        fprintf(stderr, "Error at %s:%d\n", __FILE__, __LINE__); \
        exit(1);                                                 \
    }

int main()
{
    std::string filename = "C:/project/tflitetesting/models/classification/mobilenet_v1_1.0_224_quant.tflite";
    std::unique_ptr<tflite::FlatBufferModel> model =
        tflite::FlatBufferModel::BuildFromFile(filename.c_str());
    tflite::ops::builtin::BuiltinOpResolver resolver;
    tflite::InterpreterBuilder builder(*model, resolver);
    std::unique_ptr<tflite::Interpreter> interpreter;
    builder(&interpreter);

    TFLITE_MINIMAL_CHECK(interpreter->AllocateTensors() == kTfLiteOk);
    printf("=== Pre-invoke Interpreter State ===\n");
    tflite::PrintInterpreterState(interpreter.get());

    interpreter->SetAllowFp16PrecisionForFp32(true);
    interpreter->SetNumThreads(1);
    // Get Input Tensor Dimensions
    unsigned char* input = interpreter->typed_input_tensor<unsigned char>(0);
}

But I am still receiving the access violation exception inside interpreter.h at

  const Subgraph& primary_subgraph() const {
    return *subgraphs_.front();  // Safe as subgraphs_ always has 1 entry.
  }

What am I doing wrong? I dont want to build the shared library since the target (Coral Edge) has direct access to those functions (ex. interpreter->typed_input_tensor<unsigned char>(0); too.