I think you're onto something. A "pip install" for models. Perhaps "pip install"...

antpls · on May 25, 2019

Back in the days, when I started Python, I didn't use external libraries. It was all the included batteries and docs, and it was great to start.

I was thinking about a new high-level module in the standard, you would just (pseudo python code) :

  import ai.vision
  guesses = ai.vision.guess(open('myimage.png'))
  print(guesses)
  # ["cat","person","boat"]

Three lines, everything else is abstracted. You would have ai.vision and ai.text for a start, with some accessors to other state-of-the-art models (like ai.vision.imagenet if you know better what your are doing)

The underlying models would be shipped and updated with newer versions of Python.

cheez · on May 26, 2019

Not exactly. The problem is that different models are tuned for different use cases. So I'd expect something like this:

   $ pip install pymodel-ResNet-1337

   #! /usr/bin/env python3
   import ai
   model = ai.loadModel("ResNet-1337",input=ai.input.Image,output=ai.output.Category)
   model.guess(open('myimage.png'))

Problems abound, for example, how would you resample/rescale the image.

I'd want, to start, a standard model format that can be serialized/deserialized into any language that can be (for example) pip installed and loaded. People seem to use HD5 but I don't think there is any sort of "standard".

So I'd expect the first incarnations of this idea to look like this:

   $ pip install tfmodel-ResNet-1377

or

   $ pip install kerasmodel-ResNet-1337

With some hooks for loading models:

   #!/usr/bin/env python3

   # whereas before you'd build a network, train it, and then use it, here you get the whole shebang in one go
   model = keras.loadInstalledModel("ResNet-1337")

Rest of it is up to the user, as usual