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