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27 lines
1002 B
27 lines
1002 B
6 months ago
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from 口罩检测.generate_data import custom_reader
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from 口罩检测.util import train_parameters
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import paddle as paddle
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import paddle.fluid as fluid
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from 口罩检测.VGGNet import VGGNet
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import numpy as np
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eval_reader = paddle.batch(custom_reader(train_parameters['eval_list_path']),
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batch_size=train_parameters['train_batch_size'],
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drop_last=True)
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with fluid.dygraph.guard():
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model,_ =fluid.load_dygraph('vgg')
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vgg =VGGNet()
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vgg.eval()
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accs=[]
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for batch_id,data in enumerate(eval_reader()):
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x_data = np.array([x[0] for x in data]).astype('float32')
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y_data = np.array([x[1] for x in data]).astype('int64')
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y_data = y_data[:,np.newaxis]
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img = fluid.dygraph.to_variable(x_data)
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label =fluid.dygraph.to_variable(y_data)
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out,acc= vgg(img,label)
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label = np.argmax(out.numpy())
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accs.append(acc.numpy()[0])
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print(np.mean(accs))
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