#include <Arduino.h>
#include <TensorFlowLite_ESP32.h>
#include <img_converters.h>

// Load the TFLite model
const unsigned char model_data[] = {your_model_data};

// TensorFlow Lite model and interpreter
TfLiteModel* model = NULL;
TfLiteInterpreter* interpreter = NULL;
TfLiteTensor* input = NULL;
TfLiteTensor* output = NULL;

void setup() {
  Serial.begin(9600);
  Serial.println("Program started");

  // Initialize TensorFlow Lite model
  model = tflite::GetModel(model_data);
  if (model == NULL) {
    Serial.println("Failed to load model");
    while (1);
  }

  // Create an interpreter to run the model
  static tflite::MicroErrorReporter micro_error_reporter;
  static tflite::ops::micro::AllOpsResolver resolver;
  static tflite::MicroInterpreter static_interpreter(model, resolver, tensor_arena, kTensorArenaSize, &micro_error_reporter);
  interpreter = &static_interpreter;

  // Allocate memory for the model
  if (interpreter->AllocateTensors() != kTfLiteOk) {
    Serial.println("Failed to allocate tensors");
    while (1);
  }

  // Get pointers to the input and output tensors
  input = interpreter->input(0);
  output = interpreter->output(0);

  Serial.println("TensorFlow Lite model loaded and interpreter created");
}

void loop() {
  // Assuming you have an image in the system files, load it here
  // Simulating the image capture
  uint8_t resized_img[224 * 224];
  // Simulating image conversion
  // For simplicity, let's assume the image is already in the correct format and size
  // You may need to adjust this part according to your actual image loading process
  
  // Run inference on the resized image
  run_inference(resized_img);

  // Delay for a while before next inference
  delay(1000);
}

void run_inference(uint8_t* input_data) {
  // Set input tensor data
  memcpy(input->data.uint8, input_data, input->bytes);

  // Run inference
  if (interpreter->Invoke() != kTfLiteOk) {
    Serial.println("Failed to invoke interpreter");
    return;
  }

  // Get output tensor data
  float* predictions = output->data.f;

  // Print the inference result
  Serial.println("Inference result:");
  for (int i = 0; i < 10; i++) {
    Serial.print(i);
    Serial.print(": ");
    Serial.println(predictions[i]);
  }
}