| {0: 'tench, Tinca tinca', | |
| 1: 'goldfish, Carassius auratus', | |
| 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', | |
| 3: 'tiger shark, Galeocerdo cuvieri', | |
| 4: 'hammerhead, hammerhead shark', | |
| 5: 'electric ray, crampfish, numbfish, torpedo', | |
| 6: 'stingray', | |
| 7: 'cock', | |
| 8: 'hen', | |
| 9: 'ostrich, Struthio camelus', |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
| {n01440764: 'tench, Tinca tinca', | |
| n01443537: 'goldfish, Carassius auratus', | |
| n01484850: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', | |
| n01491361: 'tiger shark, Galeocerdo cuvieri', | |
| n01494475: 'hammerhead, hammerhead shark', | |
| n01496331: 'electric ray, crampfish, numbfish, torpedo', | |
| n01498041: 'stingray', | |
| n01514668: 'cock', | |
| n01514859: 'hen', | |
| n01518878: 'ostrich, Struthio camelus', |
| # python3 -m unittest_example | |
| # python3 -m unittest -v unittest_example | |
| # python3 -m unittest -v unittest_example.Numbers.test_odd | |
| import unittest | |
| class Numbers(unittest.TestCase): | |
| def test_20(self): | |
| x = 13 |
