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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
by antpls 7y ago
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 7y agoNot 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