Metadata-Version: 1.0
Name: ml4k
Version: 0.8
Summary: UNKNOWN
Home-page: UNKNOWN
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
Description: # Python wrapper for the machinelearningforkids.co.uk API
        
        This library was designed for use with [machinelearningforkids.co.uk](https://machinelearningforkids.co.uk).
        
        ## Installation
        
        Use pip to install the `ml4k` package:
        
            sudo pip install ml4k
        
        ## Usage
        
        In order to use your machine learning model, create a `Model` object
        with your project's API key:
        
            import ml4k
        
            API_KEY = "PASTE-API-KEY-HERE"
            model = ml4k.Model(API_KEY)
        
        
        The following methods are available:
        
        ### `model.classify(data)`
        
        Classifies the given data and returns a dictionary with the result. The
        result dictionary contains the `"label"` and `"confidence"` values.
        
        
        ### `model.add_training_data(label, data)`
        
        Adds training data to the given label "bucket". You can pass text,
        images, or a list of numbers.
        
        
        ## Examples
        
        ### Recognizing Text
        
            # Get input from user and pass it to our model
            command = input("Type a command: ")
            result = model.classify("Turn on the lamp")
        
            if result["label"] == "lamp_on":
                print("Turning on the lamp")
            elif result["label"] == "lamp_off":
                print("Turning off the lamp")
        
        
        ### Recognizing Images
        
        Recognizing images is similar, but you need to pass binary image data.
        There are many was to get image data in python, such as opening and
        reading a file, or capturing from the webcam using a the
        [SimpleCV](http://simplecv.org/) library. 
        
        Images will be automatically downsized before sending to the API. 
        
            # Assuming you have image data stored as a binary string...
            result = model.classify(image)
            if result["label"] == "dog":
                print("That's a dog")
            elif result["label"] == "cat":
                print("That's a cat")
        
Platform: UNKNOWN
