Francesco Gatti
33 lines
714 B
Python
33 lines
714 B
Python
#!/usr/bin/env python
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# mail: admin@9crk.com
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# author: 9crk.from China.ShenZhen
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# time: 2017-03-22
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import caffe
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import numpy as np
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import cv2
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import sys
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import Image
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import matplotlib.pyplot as plt
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model = 'lenet.prototxt';
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weights = 'lenet.caffemodel';
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net = caffe.Net(model,weights,caffe.TEST);
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caffe.set_mode_gpu()
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img = np.array(np.random.rand(28,28), dtype=np.float32)
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#revert the image,and normalize it to 0-1 range
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print "INPUT: ", img
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img.tofile("input.bin", format="f")
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print "SHAPE: ", np.shape(img)
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out = net.forward_all(data=np.asarray([img]))
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out = out[out.keys()[0]]
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print out
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print np.shape(out)
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out.tofile("output.bin", format="f")
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#print out['prob'][0]
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#print out['prob'][0].argmax()
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