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https://github.com/wassname/IndicoIo-python.git
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Passing in a root_url variable and pulling config from environment variables
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committed by
Madison May
parent
a1621e8531
commit
6b9251f4f5
@@ -2,12 +2,14 @@ import json
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import requests
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import numpy as np
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from indicoio.utils import api_handler
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def fer(api_root, image, batch=False, auth=None, **kwargs):
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from indicoio.utils import api_handler
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import indicoio.config as config
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def fer(image, url_root=config.api_root, batch=False, auth=None, **kwargs):
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"""
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Given a grayscale input image of a face, returns a probability distribution over emotional state.
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Input should be in a list of list format, resizing will be attempted internally but for best
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Input should be in a list of list format, resizing will be attempted internally but for best
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performance, images should be already sized at 48x48 pixels..
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Example usage:
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@@ -19,13 +21,13 @@ def fer(api_root, image, batch=False, auth=None, **kwargs):
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>>> face = np.zeros((48,48)).tolist()
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>>> emotions = fer(face)
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>>> emotions
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{u'Angry': 0.6340586827229989, u'Sad': 0.1764309536057839,
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u'Neutral': 0.05582989039191157, u'Surprise': 0.0072685938275375344,
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{u'Angry': 0.6340586827229989, u'Sad': 0.1764309536057839,
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u'Neutral': 0.05582989039191157, u'Surprise': 0.0072685938275375344,
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u'Fear': 0.08523385724298838, u'Happy': 0.04117802220878012}
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:param image: The image to be analyzed.
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:type image: list of lists
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:rtype: Dictionary containing emotion probability pairs
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"""
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return api_handler(image, api_root + "fer", batch=batch, auth=auth, **kwargs)
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return api_handler(image, url_root + "fer", batch=batch, auth=auth, **kwargs)
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