import os

import cv2
import torch

from net import *
from dataset import *

transform = transforms.Compose([
            transforms.ToTensor()
        ])

data=FaceMaskDataset('/data2/face_mask')
d = DataLoader(data, batch_size=1000, shuffle=True)
with torch.no_grad():
    for i,(image,label) in enumerate(d):
        net=FaceMaskNet().cuda()
        net.load_state_dict(torch.load('params/face_mobilenet_v2.pth'))
        net.eval()
        out=net(image.cuda())
        out=torch.argmax(out,dim=1)
        acc=torch.mean(torch.eq(label.cuda(), out).float()).item()
        print(acc)