You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
34 lines
995 B
34 lines
995 B
6 months ago
|
from PIL import Image
|
||
|
|
import numpy as np
|
||
|
|
import paddle.fluid as fluid
|
||
|
|
from 口罩检测.util import train_parameters
|
||
|
|
from 口罩检测.VGGNet import VGGNet
|
||
|
|
def load_image(img_path):
|
||
|
|
img =Image.open(img_path)
|
||
|
|
if img.mode !='RGB':
|
||
|
|
img = img.covert('RGB')
|
||
|
|
img = img.resize((244,244),Image.BILINEAR)
|
||
|
|
img = np.array(img).astype('float32')
|
||
|
|
img = img.transpose((2,0,1))
|
||
|
|
img = img/255.0
|
||
|
|
return img
|
||
|
|
|
||
|
|
label_dict = train_parameters['label_dict']
|
||
|
|
|
||
|
|
#模型预测
|
||
|
|
with fluid.dygraph.guard():
|
||
|
|
model,_ = fluid.dygraph.load_dygraph('vgg')
|
||
|
|
vgg = VGGNet()
|
||
|
|
vgg.eval()
|
||
|
|
infer_path='./unmask.jpg'
|
||
|
|
img = Image.open(infer_path)
|
||
|
|
|
||
|
|
x_data = load_image(infer_path)
|
||
|
|
x_data = np.array(x_data)
|
||
|
|
x_data = x_data[np.newaxis,:,:,:]
|
||
|
|
x_data= fluid.dygraph.to_variable(x_data)
|
||
|
|
out = vgg(x_data)
|
||
|
|
result = np.argmax(out.numpy())
|
||
|
|
print(label_dict)
|
||
|
|
print("被预测的图片为：{}".format(label_dict[str(result)]))
|