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eval_model.py

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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)