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model_val.py

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+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))