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34 lines
995 B
34 lines
995 B
from PIL import Image
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import numpy as np
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import paddle.fluid as fluid
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from 口罩检测.util import train_parameters
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from 口罩检测.VGGNet import VGGNet
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def load_image(img_path):
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img =Image.open(img_path)
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if img.mode !='RGB':
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img = img.covert('RGB')
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img = img.resize((244,244),Image.BILINEAR)
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img = np.array(img).astype('float32')
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img = img.transpose((2,0,1))
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img = img/255.0
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return img
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label_dict = train_parameters['label_dict']
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#模型预测
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with fluid.dygraph.guard():
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model,_ = fluid.dygraph.load_dygraph('vgg')
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vgg = VGGNet()
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vgg.eval()
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infer_path='./unmask.jpg'
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img = Image.open(infer_path)
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x_data = load_image(infer_path)
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x_data = np.array(x_data)
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x_data = x_data[np.newaxis,:,:,:]
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x_data= fluid.dygraph.to_variable(x_data)
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out = vgg(x_data)
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result = np.argmax(out.numpy())
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print(label_dict)
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print("被预测的图片为：{}".format(label_dict[str(result)]))
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