import matplotlib.pyplot as plt
train_parameters={
    "input_size":[3,244,244],
    "class_dim":-1,
    'target_path':"./data_set",
    "train_list_path":'./train.txt',
    'eval_list_path':'./eval.txt',
    "readme_path": "./readme.json",
    'label_dict':{'0': 'maskimages', '1': 'nomaskimages'},
    "train_batch_size": 8,
    'num_epochs':1,
    "learning_stategry":{
        'lr':0.001
    }
}

def draw_train_process(title,iters,cost,accs,label_cost,label_acc):
    plt.title(title,fontsize=24)
    plt.xlabel('iter',fontsize=20)
    plt.ylabel('cost/acc',fontsize=20)
    plt.plot(iters,cost,color='red',label=label_cost)
    plt.plot(iters,accs,color='green',label=label_acc)
    plt.legend()
    plt.grid()
    plt.show()

def draw_process(title,color,iters,data,label):
    plt.title(title, fontsize=24)
    plt.xlabel("iter", fontsize=20)
    plt.ylabel(label, fontsize=20)
    plt.plot(iters, data,color=color,label=label)
    plt.legend()
    plt.grid()
    plt.show()