# 当前为语义分割的脚本，从现场minio读取图片，进而做语义分割，最终将结果存储到本地minio
import datetime
import json
import os

from cropland_module.change_detection_module import ChangeDetectionModule
from middleware.minio_util import downFile, upload_file, upload_file_from_buffer
from io import BytesIO

from mqtt_pub import MQTTClient

mqtt_client=None
# MQTT 代理地址和端口
# broker = "112.44.103.230"  # 公共 MQTT 代理（免费）
broker = "8.137.54.85"  # 公共 MQTT 代理（免费）
port = 1883  # MQTT 默认端口
# 主题
topic = "thing/product/ai/events"


def detection_func(task_id, s3_id, early_pic_url, later_pic_url, func_id):
    print("\n=== 变化检测系统 ===")
    # args = parse_args()
    gpu_id = "0"
    img_size = 256
    lr = 0.0001
    model_path = r'cropland_module/netCD_epoch_34.pth'

    # # image1_path = r'D:\project\dlfg\LEVIR-CD\test\A1\00201.png'
    # # image1_path = r'C:\Users\14867\Desktop\0613-building\Axz\xz\270\00201.jpg'
    #
    # # # 平移 5%-10%
    # # image1_path = r'C:\Users\14867\Desktop\0613-building\Axz\pingyi\00201.png'
    # # image2_path = r'D:\project\dlfg\LEVIR-CD\test\B1\00201.png'
    # image1_path = r'C:\Users\14867\Desktop\0613-building\Axz\pingyi\00205.png'
    # image2_path = r'C:\Users\14867\Desktop\0613-building\B\00205.png'
    # # image1_path=r'C:\Users\14867\Desktop\0613-building\B\00201.png'
    # # image2_path=r'C:\Users\14867\Desktop\0613-building\A\00201.png'

    cd = ChangeDetectionModule(gpu_id, img_size, lr)
    cd.load_model(model_path)

    early_pic = downFile(early_pic_url)
    later_pic = downFile(later_pic_url)

    from PIL import Image

    # image1 = Image.open(image1_path).convert('RGB')
    # image2 = Image.open(image2_path).convert('RGB')
    image1 = Image.open(early_pic).convert('RGB')
    image2 = Image.open(later_pic).convert('RGB')

    output, binary_result = cd.predict_without_label(image1, image2)

    pic_name = os.path.basename(later_pic)

    # # # 保存结果（可选）
    # result = Image.fromarray(binary_result)
    # result.save("output.png")
    #

    result = Image.fromarray(binary_result)
    # 将图像保存到 BytesIO 对象中
    buffer = BytesIO()
    result.save(buffer, format="PNG")  # 保存为 PNG 格式
    buffer.seek(0)  #
    # 现在 image_data 是图片的二进制数据
    # 你可以将其写入文件、发送到网络等
    # with open("output.png", "wb") as f:
    #     f.write(image_data)


    date_str = datetime.datetime.now().strftime("%Y%m%d")
    time_s = datetime.datetime.now().timestamp()
    mqtt_client = MQTTClient(broker, port, topic)

    pic_name_1=f"{date_str}/{time_s}-1-{pic_name}"
    pic_name_2=f"{date_str}/{time_s}-2-{pic_name}"
    pic_name=f"{date_str}/{time_s}-result-{pic_name}"


    minio_path_1, file_type_1 = upload_file(early_pic, None)
    minio_path_2, file_type_2 = upload_file(later_pic, None)
    minio_path_result, file_type_result = upload_file_from_buffer(buffer,pic_name)

    message = {
        "flight_task_id": task_id,
        "minio": {
            "minio_path_1": minio_path_1,
            "minio_path_2": minio_path_2,
            "minio_path_result": minio_path_result,
            "file_type": file_type_result
        }
    }
    json_message = json.dumps(message, indent=4, ensure_ascii=False)
    mqtt_client.publish_message(json_message)