使用環境
Arduino IDE 2.3.3

使用機器
M5stack cores3
M5stack llmモジュール

使用したプログラム
https://docs.m5stack.com/ja/stackflow/applications/cv/yolo11n_detection

/*

• SPDX-FileCopyrightText: 2024 M5Stack Technology CO LTD
• SPDX-License-Identifier: MIT
  */
  #include <Arduino.h>
  #include <M5Unified.h>
  #include <M5ModuleLLM.h>
  #include <M5GFX.h>

#include "M5CoreS3.h"

M5ModuleLLM module_llm;
String yolo_work_id;

struct DetectionResult {
String class_name;
float confidence;
int x1;
int y1;
int x2;
int y2;
};

M5Canvas canvas(&M5.Display);

void setup()
{
M5.begin();
M5.Display.setTextSize(2);
M5.Display.setTextScroll(true);

canvas.createSprite(M5.Display.width(), M5.Display.height());

/* Init M5CoreS3 Camera */
CoreS3.Camera.begin();
CoreS3.Camera.sensor->set_framesize(CoreS3.Camera.sensor, FRAMESIZE_QVGA);

/* Init module serial port */
int rxd = M5.getPin(m5::pin_name_t::port_c_rxd);
int txd = M5.getPin(m5::pin_name_t::port_c_txd);
Serial2.begin(115200, SERIAL_8N1, rxd, txd);
/* Init module */
module_llm.begin(&Serial2);

/* Make sure module is connected */
M5.Display.printf(">> Check ModuleLLM connection..\n");
while (1) {
    if (module_llm.checkConnection()) {
        break;
    }
}

/* Reset ModuleLLM */
M5.Display.printf(">> Reset ModuleLLM..\n");
module_llm.sys.reset();

/* Set ModuleLLM baud rate */
M5.Display.printf(">> ModuleLLM connected, set baud rate to 1500000\n");
module_llm.setBaudRate(1500000); //この辺りにエラー

Serial2.begin(1500000, SERIAL_8N1, rxd, txd);
module_llm.begin(&Serial2);

/* Setup YOLO module and save returned work id */
M5.Display.printf(">> Setup yolo..\n");
yolo_work_id = module_llm.yolo.setup();
canvas.setFont(&fonts::FreeSerifBold12pt7b);

}

DetectionResult parseDetection(String& jsonStr)
{
DetectionResult detection;
JsonDocument doc;
deserializeJson(doc, jsonStr);
JsonObject obj = doc.as<JsonObject>();
if (obj["bbox"].is<JsonArray>() && obj["class"].is<const char*>() && obj["confidence"].is<const char*>()) {
detection.class_name = obj["class"].as<const char*>();
detection.confidence = atof(obj["confidence"].as<const char*>());
JsonArray bbox = obj["bbox"].as<JsonArray>();
if (bbox.size() == 4) {
detection.x1 = (int)atof(bbox[0].as<const char*>());
detection.y1 = (int)atof(bbox[1].as<const char*>());
detection.x2 = (int)atof(bbox[2].as<const char*>());
detection.y2 = (int)atof(bbox[3].as<const char*>());
}
}
return detection;
}

void loop()
{
if (CoreS3.Camera.get()) {
uint8_t* out_jpg = NULL;
size_t out_jpg_len = 0;
frame2jpg(CoreS3.Camera.fb, 50, &out_jpg, &out_jpg_len);
canvas.pushImage(0, 0, CoreS3.Display.width(), CoreS3.Display.height(), (uint16_t*)CoreS3.Camera.fb->buf);
module_llm.yolo.inferenceAndWaitResult(
yolo_work_id, out_jpg, out_jpg_len,
[](String& result) {
DetectionResult detection = parseDetection(result);
int y1_pos = detection.y1 - 40;
if (y1_pos < 24) y1_pos = 24;
String combinedResult = detection.class_name + " " + String(detection.confidence, 2);
canvas.drawString(combinedResult, detection.x1, y1_pos);
canvas.drawRect(detection.x1, detection.y1 - 40, detection.x2, detection.y2 - 40, ORANGE);
},
10);
canvas.pushSprite(0, 0);
free(out_jpg);
}
CoreS3.Camera.free();
}

(Cores3のカメラで動かすプログラム)