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from PIL import Image
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import paddle.fluid as fluid
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import numpy as np
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from 手势识别.build_model import FullNet_Model
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def load_image(path):
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img =Image.open(path)
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img = img.resize((100,100),Image.ANTIALIAS)
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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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print(img.shape)
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return img
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with fluid.dygraph.guard():
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infer_path ='test.jpg'
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model = FullNet_Model()
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model_dict,_ =fluid.load_dygraph('./FullNet_Model')
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model.load_dict(model_dict)
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model.eval() #开启评估模式
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infer_image = load_image(infer_path)
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infer_image = infer_image[np.newaxis,:,:,:]
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infer_image =fluid.dygraph.to_variable(infer_image)
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result = model(infer_image)
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print(np.argmax(result.numpy()))
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