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#include <iostream>
#include <vector>
#include <cstdint>
#include <cstring>

bool isStartCode3(const uint8_t* p)
{
    return p[0] == 0x00 && p[1] == 0x00 && p[2] == 0x01;
}

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include(FetchContent)
FetchContent_Declare(
        googletest
        GIT_REPOSITORY https://github.com/google/googletest.git
        GIT_TAG v1.14.0
)

FetchContent_MakeAvailable(googletest)

add_executable(mytests

zhuker

#include <lame/lame.h>

struct Mp3Encoder {
  lame_global_flags *lame = nullptr;
  ~Mp3Encoder() {
    if (lame) {
      lame_close(lame);
      lame = nullptr;
    }
  }

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#include <iostream>

#ifdef __ARM_NEON

#include <arm_neon.h>

#endif

#include <fstream>

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void string_split(const std::string &s, const std::string &delim, std::deque<std::string> &out, int maxElements) {
  auto start = 0U;
  auto end = s.find(delim);
  while (end != std::string::npos && out.size() < maxElements - 1) {
    out.push_back(s.substr(start, end - start));
    start = end + delim.length();
    end = s.find(delim, start);
  }

  out.push_back(s.substr(start, s.length() - start));

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static std::vector<char> readAllBytes(char const* filename)
{
    std::ifstream ifs(filename, std::ios::binary | std::ios::ate);
    std::ifstream::pos_type pos = ifs.tellg();

    if (pos == 0)
    {
        return std::vector<char>{};
    }

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    @Test
    fun sleepParkNanos() {
        val nsec = 960 * 1000_000_000L / 48000

        val looping = AtomicBoolean(true)
        val histo = IntArray(10)
        val t = Thread() {
            val startTime = System.nanoTime()
            var i = 0
            while (looping.get()) {

zhuker

import numpy as np
import cv2 as cv
import glob

path_to_images = './dji-mini2/*.JPG'
draw_ui = False


def calibrate():
    # termination criteria

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import kotlin.math.*

interface ILatLng {
    val lat: Double
    val lon: Double
}

enum class Unit(s: String) {
    KILOMETERS("km"),
    METERS("m"),

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@Test
fun onnxRuntime() {
    val env = OrtEnvironment.getEnvironment()
    OrtSession.SessionOptions().use { opts ->
        opts.setOptimizationLevel(OrtSession.SessionOptions.OptLevel.BASIC_OPT)
        env.createSession("mymodel.onnx", opts).use { session ->
            for (i in session.inputInfo.values) {
                println(i)
            }
            for (o in session.outputInfo.values) {