# -*- coding: utf-8 -*-
"""
Created on Fri Jan 19 14:01:46 2024

@author: ym
"""

import torch
import os
# import torchvision.transforms as T
class Config:
    # network settings
    backbone = 'resnet18' # [resnet18, mobilevit_s, mobilenet_v2, mobilenetv3]
    batch_size = 8
    embedding_size = 256
    img_size = 224
    
    current_path = os.path.dirname(os.path.abspath(__file__))
    model_path = os.path.join(current_path, r"ckpts\resnet18_1220\best.pth")
    
    # model_path = "./trackers/reid/ckpts/resnet18_1220/best.pth"
    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
    
# =============================================================================
#     metric = 'arcface'  # [cosface, arcface]
#     drop_ratio = 0.5
#    
#     # training settings
#     checkpoints = "checkpoints/Mobilev3Large_1225"  # [resnet18, mobilevit_s, mobilenet_v2, mobilenetv3]
#     restore = False
#     
#     test_model = "./checkpoints/resnet18_1220/best.pth"
#
# 
#     device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
#     pin_memory = True  # if memory is large, set it True to speed up a bit
#     num_workers = 4  # dataloader
# =============================================================================

config = Config()