from 口罩检测.generate_data import custom_reader
from 口罩检测.util import train_parameters
import paddle as paddle
import paddle.fluid as fluid
from 口罩检测.VGGNet import VGGNet
import numpy as np
eval_reader = paddle.batch(custom_reader(train_parameters['eval_list_path']),
                            batch_size=train_parameters['train_batch_size'],
                            drop_last=True)
with fluid.dygraph.guard():
    model,_ =fluid.load_dygraph('vgg')
    vgg =VGGNet()
    vgg.eval()
    accs=[]
    for batch_id,data in enumerate(eval_reader()):
        x_data = np.array([x[0] for x in data]).astype('float32')
        y_data = np.array([x[1] for x in data]).astype('int64')
        y_data = y_data[:,np.newaxis]

        img = fluid.dygraph.to_variable(x_data)
        label =fluid.dygraph.to_variable(y_data)

        out,acc= vgg(img,label)

        label = np.argmax(out.numpy())
        accs.append(acc.numpy()[0])
        print(np.mean(accs))