参考
https://hackernoon.com/creating-insanely-fast-image-classifiers-with-mobilenet-in-tensorflow-f030ce0a2991
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/image_retraining/retrain.py
https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/#0
https://www.tensorflow.org/tutorials/image_retraining
准备图片
images/label1/1.jpg
/2.jpg
images/label2/1.jpg
/2.jpg
开始训练，默认Inception v3 model
python retrain.py \ --bottleneck_dir=bottlenecks \ --how_many_training_steps=500 \ --model_dir=inception \ --summaries_dir=training_summaries/basic \ --output_graph=retrained_graph.pb \ --output_labels=retrained_labels.txt \ --image_dir=flower_photos
也可以使用其他模型
详细参数查看
python retrain.py -h
使用训练结果进行预测
参考https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/#5
这样在训练好的inception-2015-12-05数据基础上
仅重新训练最后一层
用较短的时间达到分类效果