mirror of
https://github.com/wassname/IndicoIo-python.git
synced 2026-06-27 16:10:34 +08:00
Chris Lee
117 lines
3.8 KiB
Python
117 lines
3.8 KiB
Python
from indicoio.config import TEXT_APIS, IMAGE_APIS, API_NAMES
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from indicoio.utils.api import api_handler
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from indicoio.utils.image import image_preprocess
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from indicoio.utils.errors import IndicoError
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CLIENT_SERVER_MAP = dict((api, api.strip().replace("_", "").lower()) for api in API_NAMES)
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SERVER_CLIENT_MAP = dict((v, k) for k, v in CLIENT_SERVER_MAP.iteritems())
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def multi(data, type, apis, available, batch=False, **kwargs):
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"""
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Helper to make multi requests of different types.
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:param data: data to be sent in JSON.
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:param type: String type of API request
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:param apis: List of apis to use.
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:param apis: List of apis available for use.
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:type data: str or image
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:type type: str or unicode
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:type apis: list of str
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:type available: list of str
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:rtype: Dictionary of api responses
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"""
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# Client side api name checking - strictly only accept func name api
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invalid_apis = [api for api in apis if api not in available]
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if invalid_apis:
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raise IndicoError("%s are not valid %s APIs. Please reference the available APIs below:\n%s"
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% (", ".join(invalid_apis), type, ", ".join(available))
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)
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# Convert client api names to server names before sending request
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apis = map(CLIENT_SERVER_MAP.get, apis)
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result = api_handler(data, url_params = {"apis":apis, "batch":batch}, **kwargs)
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return handle_response(result)
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def handle_response(result):
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# Parse out the results to a dicionary of api: result
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return dict((SERVER_CLIENT_MAP[api], parsed_response(api, res))
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for api, res in result.iteritems())
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def predict_text(input_text, apis=TEXT_APIS, cloud=None, batch=False, api_key=None, **kwargs):
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"""
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Given input text, returns the results of specified text apis. Possible apis
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include: [ 'text_tags', 'political', 'sentiment', 'language' ]
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Example usage:
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.. code-block:: python
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>>> import indicoio
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>>> text = 'Monday: Delightful with mostly sunny skies. Highs in the low 70s.'
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>>> results = indicoio.text(data = text, apis = ["language", "sentiment"])
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>>> language_results = results["langauge"]
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>>> sentiment_results = results["sentiment"]
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:param text: The text to be analyzed.
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:param apis: List of apis to use.
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:type text: str or unicode
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:type apis: list of str
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:rtype: Dictionary of api responses
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"""
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return multi(
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api="apis",
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data=input_text,
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type="text",
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available = TEXT_APIS,
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cloud=cloud,
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batch=batch,
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api_key=api_key,
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apis=apis,
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**kwargs)
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def predict_image(image, apis=IMAGE_APIS, cloud=None, batch=False, api_key=None, **kwargs):
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"""
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Given input image, returns the results of specified image apis. Possible apis
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include: ['fer', 'facial_features', 'image_features']
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Example usage:
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.. code-block:: python
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>>> import indicoio
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>>> import numpy as np
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>>> face = np.zeros((48,48)).tolist()
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>>> results = indicoio.image(image = face, apis = ["fer", "facial_features"])
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>>> fer = results["fer"]
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>>> facial_features = results["facial_features"]
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:param text: The text to be analyzed.
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:param apis: List of apis to use.
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:type text: str or unicode
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:type apis: list of str
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:rtype: Dictionary of api responses
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"""
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return multi(
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api="apis",
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data=image_preprocess(image, batch=batch),
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type="image",
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available=IMAGE_APIS,
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cloud=cloud,
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batch=batch,
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api_key=api_key,
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apis=apis,
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**kwargs)
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def parsed_response(api, response):
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result = response.get('results', False)
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if result:
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return result
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raise IndicoError(
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"Sorry, the %s API returned an unexpected response.\n\t%s"
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% (api, response.get('error', ""))
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)
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