# from yacs.config import CfgNode as CfgNode
import torchvision.transforms as T
import torch
import os

class globalVal:
    tempLibList = []
    tempLibLists = {}
    track_y_lists = []
    mac_id = None
    back_return_similarity = []
    back_add_similarity = []
    front_return_similarity = []
    front_add_similarity = []
    comprehensive_similarity = []

class config:
    save_videos_dir = 'videos'

    #url 
    # push_url = 'http://api.test2.ieemoo.cn/emoo-api/intelligence/addVideoPathBySequenceId.do'
    push_url = 'https://api.test2.ieemoo.cn/emoo-api/intelligence/addVideoPathBySequenceId.do'  # 闲时上传
    get_config_url = 'https://api.test2.ieemoo.cn/emoo-api/intelligence/addVideoPathByStoreId.do'  # 闲时上传相应配置
    storidPth = 'tools/storeId.txt'

    #obs update
    obs_access_key_id = 'LHXJC7GIC2NNUUHHTNVI'
    obs_secret_access_key = 'sVWvEItrFKWPp5DxeMvX8jLFU69iXPpzkjuMX3iM'
    obs_server = 'https://obs.cn-east-3.myhuaweicloud.com'
    obs_bucketName = 'ieemoo-ai'

    keys = ['x', 'y', 'w', 'h', 'track_id', 'score', 'cls', 'frame_index']
    
    obs_root_dir = 'ieemoo_ai_data'

    #contrast config
    host = "192.168.1.28"
    port = "19530"
    embedding_size = 256
    img_size = 224
    test_transform = T.Compose([
        T.ToTensor(),
        T.Resize((224, 224)),
        T.ConvertImageDtype(torch.float32),
        T.Normalize(mean=[0.5], std=[0.5]),
    ])

    # test_model = "./tools/ckpts/MobilenetV3Large_noParallel_2624.pth"
    test_model = "./tools/ckpts/resnet18_0721_best.pth"
    tracking_model = "./tools/ckpts/best_158734_cls11_noaug10.pt"
    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

    httpHost = '0.0.0.0'
    httpPort = 8088

    #tracking config
    botsort = './ytracking/tracking/trackers/cfg/botsort.yaml'
    incart = './tools/Template_images/incart.png'
    outcart = './tools/Template_images/outcart.png'
    cartboarder = './tools/Template_images/cartboarder.png'
    edgeline = './tools/Template_images/edgeline.png'
    cartedge = './tools/Template_images/cartedge.png'
    incart_ftmp = './tools/Template_images/incart_ftmp.png'


    action_type = {
        "1": 'purchase',
        '2': 'jettison',
        '3': 'unswept_purchase',
        '4': 'unswept_jettison'
    }
    camera_id = {
        '0': 'back',
        '1': 'front',
    }
    recognize_result = {
        '01': 'uncatalogued',
        '02': 'fail',
        '03': 'exception',
        '04': 'pass',
    }

    # reid config
    backbone = 'resnet18'  # [resnet18, mobilevit_s, mobilenet_v2, mobilenetv3]
    batch_size = 8

    model_path = './tools/ckpts/best_resnet18_0515.pth'

    temp_video_name = None

cfg = config()
gvalue = globalVal()