我将官方的yolo11n.py转换成onnx再转成kmodel，再使用官方示例的mircopython代码进行运行代码如下：摄像头可以调用，但是框框没有显示出来；
我是一位初学者，想请教一下各位大佬：
1.我这个流程如何检测kmodel是否转换成功？
2.如果成功我应该如何看kmodel的输出是什么格式的？（因为onnx有netron可视化，kmodel有没有可以看他结构的代码？）
3.我应该如何修改后处理部分，以及显示部分让他能成功显示框框，我需要修改哪里？
4.有没有相关官方文档教学以及相关帮助文档？（因为我看官方的文档很多，但是很杂，有些用mircopython，有些用命令行，有些用Linux，有些是sdk，又有些是canmv，有些提了一点ai的部分，有些用yolo新的库，又有些没用，搞得我现在很乱）
from libs.PipeLine import PipeLine, ScopedTiming
from libs.YOLO import YOLO11
import os,sys,gc
import ulab.numpy as np
import image
if __name__=="__main__":
# 显示模式，默认"hdmi",可以选择"hdmi"和"lcd"
display_mode="hdmi"
rgb888p_size=[320,320]
if display_mode=="hdmi":
display_size=[1920,1080]
else:
display_size=[800,480]
kmodel_path="/data/test.kmodel"
labels = ["person","bicycle","car","motorcycle","airplane","bus","train","truck","boat","traffic", "light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie","suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch", "potted plant", "bed", "dining table", "toilet", "tv", "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"]
confidence_threshold = 0.5
nms_threshold=0.45
mask_threshold=0.5
model_input_size=[640,640]
# 初始化PipeLine
pl=PipeLine(rgb888p_size=rgb888p_size,display_size=display_size,display_mode=display_mode)
pl.create()
# 初始化YOLO11实例
yolo=YOLO11(task_type="detect",mode="video",kmodel_path=kmodel_path,labels=labels,rgb888p_size=rgb888p_size,model_input_size=model_input_size,display_size=display_size,conf_thresh=confidence_threshold,nms_thresh=nms_threshold,mask_thresh=mask_threshold,max_boxes_num=50,debug_mode=0)
yolo.config_preprocess()
try:
while True:
os.exitpoint()
with ScopedTiming("total",1):
# 逐帧推理
img=pl.get_frame()
res=yolo.run(img)
yolo.draw_result(res,pl.osd_img)
pl.show_image()
gc.collect()
except Exception as e:
sys.print_exception(e)
finally:
yolo.deinit()
pl.destroy()
