forked from p32761584/tensorlayer3
30 lines
725 B
Python
30 lines
725 B
Python
#! /usr/bin/python
|
|
# -*- coding: utf-8 -*-
|
|
"""VGG-16 for ImageNet using TL models."""
|
|
|
|
import time
|
|
|
|
import numpy as np
|
|
import tensorflow as tf
|
|
|
|
import tensorlayer as tl
|
|
from examples.model_zoo.imagenet_classes import class_names
|
|
from examples.model_zoo.vgg import vgg16
|
|
|
|
tl.logging.set_verbosity(tl.logging.DEBUG)
|
|
|
|
# get the whole model
|
|
vgg = vgg16(pretrained=True)
|
|
vgg.set_eval()
|
|
|
|
img = tl.vis.read_image('data/tiger.jpeg')
|
|
img = tl.prepro.imresize(img, (224, 224)).astype(np.float32) / 255
|
|
|
|
start_time = time.time()
|
|
output = vgg(img)
|
|
probs = tf.nn.softmax(output)[0].numpy()
|
|
print(" End time : %.5ss" % (time.time() - start_time))
|
|
preds = (np.argsort(probs)[::-1])[0:5]
|
|
for p in preds:
|
|
print(class_names[p], probs[p])
|