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from PIL import Image
import paddle.fluid as fluid
import numpy as np
from 手势识别.build_model import FullNet_Model
def load_image(path):
img =Image.open(path)
img = img.resize((100,100),Image.ANTIALIAS)
img = np.array(img).astype('float32')
img = img.transpose(2,0,1)
img = img/255.0
print(img.shape)
return img
with fluid.dygraph.guard():
infer_path ='test.jpg'
model = FullNet_Model()
model_dict,_ =fluid.load_dygraph('./FullNet_Model')
model.load_dict(model_dict)
model.eval() #开启评估模式
infer_image = load_image(infer_path)
infer_image = infer_image[np.newaxis,:,:,:]
infer_image =fluid.dygraph.to_variable(infer_image)
result = model(infer_image)
print(np.argmax(result.numpy()))