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Definitely. Last weekend, I had a simple project of locking my computer screen when I am away with the help of the webcam. I know this is trivial with current s

by antpls 7y ago

Definitely. Last weekend, I had a simple project of locking my computer screen when I am away with the help of the webcam. I know this is trivial with current state-of-the-art pretrained neural net models, but I did give up. I couldnt find an easy way to fetch pretrained models (from where? which one?), feed the webcam stream, and then do inference "is there a face in the image?". It would probably be trivial for someone who knows CV libraries or tensorflow, but we really miss the good old time when 5 obvious lines of Python did the job. Maybe a new Python standard library with an API for AI would be useful here.

_visgean 7y ago
try yolo.
milquetoastaf 7y ago
No need for ML https://docs.opencv.org/3.4/db/d5c/tutorial_py_bg_subtraction.html https://docs.opencv.org/3.4/db/d5c/tutorial_py_bg_subtractio... https://realpython.com/face-recognition-with-python/#opencv https://realpython.com/face-recognition-with-python/#opencv
cheez 7y ago
I think you're onto something. A "pip install" for models. Perhaps "pip install" is sufficient and we just need to start using it.
- 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 ago
    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
winrid 7y ago
Could just use opencv and check for your face.

by antpls 7y ago

_visgean 7y ago

try yolo.

milquetoastaf 7y ago

No need for ML https://docs.opencv.org/3.4/db/d5c/tutorial_py_bg_subtraction.html https://docs.opencv.org/3.4/db/d5c/tutorial_py_bg_subtractio... https://realpython.com/face-recognition-with-python/#opencv https://realpython.com/face-recognition-with-python/#opencv

cheez 7y ago

I think you're onto something. A "pip install" for models. Perhaps "pip install" is sufficient and we just need to start using it.

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 ago
  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

winrid 7y ago

Could just use opencv and check for your face.