from libs.PipeLine import PipeLine
from libs.YOLO import YOLO26
from libs.Utils import *
import os,sys,gc
import ulab.numpy as np
import image

if __name__=="__main__":
    # 这里仅为示例，自定义场景请修改为您自己的模型路径、标签名称、模型输入大小
    kmodel_path="/sdcard/examples/kmodel/fruit_det_yolo26n_320.kmodel"
    labels = ["apple","banana","orange"]
    model_input_size=[320,320]

    # 添加显示模式，默认hdmi，可选hdmi/lcd/lt9611/st7701/hx8399,其中hdmi默认置为lt9611，分辨率1920*1080；lcd默认置为st7701，分辨率800*480
    display_mode="lcd"
    rgb888p_size=[640,360]
    confidence_threshold = 0.5
    # 初始化PipeLine
    pl=PipeLine(rgb888p_size=rgb888p_size,display_mode=display_mode)
    pl.create()
    display_size=pl.get_display_size()
    # 初始化 YOLO26 模型
    yolo=YOLO26(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,max_boxes_num=50,debug_mode=0)
    yolo.config_preprocess()
    while True:
        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()
    yolo.deinit()
    pl.destroy()
