python - 如何在谷歌机器学习中预测图像

Question

我正在使用谷歌云机器学习。我想识别不同的图像。现在我已经用不同类型的图像训练了我的模型（使用 tensorflow 的初始模型），并且我在 Google 机器学习中创建了一个带有结果的版本。

如何预测新图像？你有什么想法可以帮助我吗？

非常感谢！

Answer 1

I'm not quite clear on what you're asking. Without more information, I will just point you to the Google blog post and code sample that detail how to train on images.

But back to what I think you're asking...for a model to be deployed to Google Cloud ML a few things have to happen:

• It needs to have its inputs and output collections declared in the Tensorflow model before saving the checkpoint.
• The model checkpoint needs to be copied to GCS
• You must use gcloud to create a new "model" (as far as gcloud is concerned, a model is a namespace for many different tensorflow checkpoints) and then deploy your checkpoint to that gcloud model.

The prediction quickstart has a very similar example here.