Inference Result is different between DIGITS(WEB) and Python Code

[killeress]

1.Digit Result

2.Python Result From This Tutorial

Here is my code

import numpy as np
import sys
import os

caffe_root = '/opt/caffe/'
sys.path.insert(0, os.path.join(caffe_root, 'python'))

import caffe
from caffe.proto import caffe_pb2

caffe.set_mode_gpu()
model_dir = 'model'
deploy_file = os.path.join(model_dir, 'deploy.prototxt')
weights_file = os.path.join(model_dir, 'snapshot_iter_64980.caffemodel')
net = caffe.Net(deploy_file, caffe.TEST, weights=weights_file)

transformer = caffe.io.Transformer({'data': net.blobs['data'].data.shape})
transformer.set_transpose('data', (2, 0, 1))
transformer.set_raw_scale('data', 255)
transformer.set_channel_swap('data', (2, 1, 0))

mean_file = os.path.join(model_dir, 'mean.binaryproto')
with open(mean_file, 'rb') as infile:
blob = caffe_pb2.BlobProto()
blob.MergeFromString(infile.read())
if blob.HasField('shape'):
blob_dims = blob.shape
assert len(blob_dims) == 4, 'Shape should have 4 dimensions - shape is %s' % blob.shape
elif blob.HasField('num') and blob.HasField('channels') and
blob.HasField('height') and blob.HasField('width'):
blob_dims = (blob.num, blob.channels, blob.height, blob.width)
else:
raise ValueError('blob does not provide shape or 4d dimensions')
pixel = np.reshape(blob.data, blob_dims[1:]).mean(1).mean(1)
transformer.set_mean('data', pixel)
labels_file = os.path.join(model_dir, 'labels.txt')
labels = np.loadtxt(labels_file, str, delimiter='\n')

image = caffe.io.load_image('test_img.jpg')

net.blobs['data'].data[...] = transformer.preprocess('data', image)

out = net.forward()

softmax_layer = out['softmax']

LLPM_prob = softmax_layer.item(0)
OK_prob = softmax_layer.item(1)
YSBD_prob = softmax_layer.item(2)
YSCQ_prob = softmax_layer.item(3)

print(LLPM_prob)
print(OK_prob)
print(YSBD_prob)
print(YSCQ_prob)
`

My Python Result:

4.98672634421e-05
0.00573868537322
0.993777871132
0.000433590757893