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# ===================== 1. 统一导入区域（顺序合理，无冗余） =====================
# 第三方库/工具类导入
from libs.PipeLine import PipeLine
from libs.AIBase import AIBase
from libs.AI2D import Ai2d

from libs.Utils import *
from libs.YOLO import YOLOv8  # 保留必要导入，无冗余
# 系统/硬件库导入
import os
import sys
import ujson
import gc
#import math
import utime  # 嵌入式专用计时/延时，无需同时导入time（若ScopedTiming仍报错，再添加time）
# 媒体/AI相关导入
from media.media import *
from media.sensor import *
from media.display import *
import nncase_runtime as nn
import ulab.numpy as np
import image
import aicube
import aidemo
import random

# ===================== 2. 核心外设配置（仅保留需要的，整洁清晰） =====================
DISPLAY_WIDTH = 960  # LCD物理宽度（原生）
DISPLAY_HEIGHT = 540 # LCD物理高度（原生）

# 对齐函数（按需保留，适配Camera要求）
def align_to_8(x):
    return (x // 8) * 8
def align_to_16(x):
    return (x // 16) * 16

# Sensor输出尺寸（对齐后，替换原1280x720）
SENSOR_WIDTH = DISPLAY_WIDTH
SENSOR_HEIGHT = 536

# ===================== 3. 自定义检测类（模型逻辑完全保留，仅适配外设参数） =====================
class DetectionApp(AIBase):
    def __init__(self,kmodel_path,labels,model_input_size=[640,640],
                 anchors=[10.13,16,30,33,23,30,61,62,45,59,119,116,90,156,198,373,326],
                 model_type="AnchorBaseDet",confidence_threshold=0.5,nms_threshold=0.25,
                 nms_option=False,strides=[8,16,32],
                 rgb888p_size=[SENSOR_WIDTH, SENSOR_HEIGHT],
                 display_size=[DISPLAY_WIDTH, DISPLAY_HEIGHT],debug_mode=0):
        super().__init__(kmodel_path,model_input_size,rgb888p_size,debug_mode)
        # 模型核心参数（完全未修改，仅外设参数适配）
        self.kmodel_path=kmodel_path
        self.labels=labels
        self.model_input_size=model_input_size
        self.anchors=anchors
        self.model_type=model_type
        self.confidence_threshold=confidence_threshold
        self.nms_threshold=nms_threshold
        self.nms_option=nms_option
        self.strides=strides
        # 外设尺寸（适配新配置，宽16对齐）
        self.rgb888p_size=[ALIGN_UP(rgb888p_size[0],16),rgb888p_size[1]]
        self.display_size=[ALIGN_UP(display_size[0],16),display_size[1]]
        # 其他参数（完全保留原逻辑）
        self.debug_mode=debug_mode
        self.color_four=get_colors(len(self.labels))
        self.ai2d=Ai2d(debug_mode)
        self.ai2d.set_ai2d_dtype(nn.ai2d_format.NCHW_FMT,nn.ai2d_format.NCHW_FMT,np.uint8, np.uint8)

    # 预处理配置（模型核心逻辑完全未修改）
    def config_preprocess(self,input_image_size=None):
        with ScopedTiming("set preprocess config",self.debug_mode > 0):
            ai2d_input_size=input_image_size if input_image_size else self.rgb888p_size
            top,bottom,left,right,_=center_pad_param(self.rgb888p_size,self.model_input_size)
            self.ai2d.pad([0,0,0,0,top,bottom,left,right], 0, [114,114,114])
            self.ai2d.resize(nn.interp_method.tf_bilinear, nn.interp_mode.half_pixel)
            self.ai2d.build([1,3,ai2d_input_size[1],ai2d_input_size[0]],
                            [1,3,self.model_input_size[1],self.model_input_size[0]])

    # 后处理（模型核心逻辑完全未修改，无任何多余改动）
    def postprocess(self,results):
        with ScopedTiming("postprocess",self.debug_mode > 0):
            if self.model_type == "AnchorBaseDet":
                det_boxes = aicube.anchorbasedet_post_process( results[0], results[1], results[2],
                                                               self.model_input_size, self.rgb888p_size,
                                                               self.strides, len(self.labels),
                                                               self.confidence_threshold, self.nms_threshold,
                                                               self.anchors, self.nms_option)
            elif self.model_type == "GFLDet":
                det_boxes = aicube.gfldet_post_process( results[0], results[1], results[2],
                                                        self.model_input_size, self.rgb888p_size,
                                                        self.strides, len(self.labels),
                                                        self.confidence_threshold, self.nms_threshold,
                                                        self.nms_option)
            elif self.model_type=="AnchorFreeDet":
                det_boxes = aicube.anchorfreedet_post_process( results[0], results[1], results[2],
                                                               self.model_input_size, self.rgb888p_size,
                                                               self.strides, len(self.labels),
                                                               self.confidence_threshold, self.nms_threshold,
                                                               self.nms_option)
            else:
                det_boxes=None
            return det_boxes

    # 绘制结果（仅适配新外设尺寸，绘制逻辑完全未修改）
    def draw_result(self,pl,det_boxes):
        with ScopedTiming("draw osd",self.debug_mode > 0):
            if det_boxes:
                pl.osd_img.clear()
                for det_boxe in det_boxes:
                    x1, y1, x2, y2 = det_boxe[2],det_boxe[3],det_boxe[4],det_boxe[5]
                    # 坐标映射适配新尺寸（仅此处适配，无其他改动）
                    sx=int(x1 * self.display_size[0] // self.rgb888p_size[0])
                    sy=int(y1 * self.display_size[1] // self.rgb888p_size[1])
                    w = int(float(x2 - x1) * self.display_size[0] // self.rgb888p_size[0])
                    h = int(float(y2 - y1) * self.display_size[1] // self.rgb888p_size[1])
                    pl.osd_img.draw_rectangle(sx , sy , w , h , color=self.get_color(det_boxe[0]))
                    label = self.labels[det_boxe[0]]
                    score = str(round(det_boxe[1],2))
                    pl.osd_img.draw_string_advanced(sx, sy-50,32, label + " " + score , color=self.color_four[det_boxe[0]])
            else:
                pl.osd_img.clear()
                pl.osd_img.draw_rectangle(0, 0, 128, 128, color=(0,0,0,0))

    # 获取颜色（完全保留原逻辑）
    def get_color(self, x):
        idx=x%len(self.color_four)
        return self.color_four[idx]

# ===================== 4. 主程序（整洁无冗余，外设参数适配，模型逻辑不变） =====================
# 优化后主程序（添加退出捕获）
if __name__=="__main__":
    # 基础配置（不变）
    display_mode="lcd"
    kmodel_path="/sdcard/examples/ai_test_kmodel/insect_det.kmodel"
    labels=["leconte","boerner","armandi","linnaeus","coleoptera","acuminatus"]
    confidence_threshold=0.5
    nms_threshold = 0.5
    anchors=[30,23,21,33,29,43,44,29,41,39,41,68,71,43,59,61,71,72]

    # 初始化变量（提前定义，方便异常释放）
    pl = None
    det = None
    try:

        rgb888p_size = [SENSOR_WIDTH, SENSOR_HEIGHT]
        display_size = [DISPLAY_WIDTH, DISPLAY_HEIGHT]


        # 初始化PipeLine
        pl=PipeLine(rgb888p_size=rgb888p_size,display_mode=display_mode, display_size=display_size)
        #pl=PipeLine(rgb888p_size=rgb888p_size,display_mode=display_mode)
        pl.create()
        actual_display_size=pl.get_display_size()
        # 校验实际显示尺寸与配置尺寸是否一致
        if actual_display_size[0] != DISPLAY_WIDTH or actual_display_size[1] != DISPLAY_HEIGHT:
            print(f"警告：显示尺寸不匹配，配置[{DISPLAY_WIDTH},{DISPLAY_HEIGHT}]，实际[{actual_display_size[0]},{actual_display_size[1]}]")
        # 初始化检测类
        det=DetectionApp(
            kmodel_path=kmodel_path,
            labels=labels,
            model_input_size=[640,640],
            anchors=anchors,
            rgb888p_size=rgb888p_size,
            display_size=actual_display_size,
            debug_mode=0
        )
        det.config_preprocess()


        # 推理循环
        while True:
            with ScopedTiming("total",1):
                img=pl.get_frame()

                det_boxes=det.run(img)

                det.draw_result(pl,det_boxes)
                print(f"剩余内存g：{gc.mem_free()} 字节")
                pl.show_image()                         #g打印h没打印，在这一行卡住且因为get display buffer failed

                #Display.show_image(det_boxes, 0, 0, Display.LAYER_OSD0)
                print(f"剩余内存h：{gc.mem_free()} 字节")
                gc.collect()
                print(f"剩余内存i：{gc.mem_free()} 字节")
                utime.sleep_ms(1)
    except KeyboardInterrupt:
        print("用户退出程序")
    except Exception as e:
        print(f"程序异常：{str(e)}")
    finally:
        # 确保资源释放
        if det is not None:
            det.deinit()
        if pl is not None:
            pl.destroy()
        print("资源已释放")