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from 手势识别.generate_data import data_reader
from 手势识别.build_model import FullNet_Model
import paddle.fluid as fluid
import paddle as paddle
import numpy as np
test_reader = paddle.batch(reader=data_reader('./test_data.list'), batch_size=32)
with fluid.dygraph.guard():
accs=[]
model_dict,_=fluid.load_dygraph('FullNet_Model')
model = FullNet_Model()
model.load_dict(model_dict) #加载模型
model.eval() #开启评估模式
for batch_id,data in enumerate(test_reader()):
images = np.array([x[0].reshape(3,100,100) for x in data],np.float32)
labels = np.array([x[1] for x in data]).astype("int64")
labels = labels[:,np.newaxis]
image = fluid.dygraph.to_variable(images)
label = fluid.dygraph.to_variable(labels)
predict = model(image)
acc=fluid.layers.accuracy(predict,label)
accs.append(acc.numpy()[0])
avg_acc=np.mean(accs)
print('平均准确率为',avg_acc)