mirror of
https://github.com/wassname/IndicoIo-python.git
synced 2026-06-27 16:10:34 +08:00
Remove ner
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@@ -9,7 +9,6 @@ from indicoio.text.sentiment import political, posneg
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from indicoio.text.sentiment import posneg as sentiment
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from indicoio.text.lang import language
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from indicoio.text.classification import classification
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from indicoio.text.ner import named_entities
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from indicoio.images.fer import fer
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from indicoio.images.features import facial_features
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from indicoio.images.features import image_features
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@@ -23,4 +22,3 @@ fer = partial(fer, config.api_root)
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facial_features = partial(facial_features, config.api_root)
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image_features = partial(image_features, config.api_root)
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classification = partial(classification, config.api_root)
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named_entities = partial(named_entities, config.api_root)
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@@ -7,7 +7,6 @@ from indicoio.text.sentiment import political, posneg
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from indicoio.text.sentiment import posneg as sentiment
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from indicoio.text.lang import language
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from indicoio.text.classification import classification
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from indicoio.text.ner import named_entities
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from indicoio.images.fer import fer
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from indicoio.images.features import facial_features
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from indicoio.images.features import image_features
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@@ -21,4 +20,3 @@ fer = partial(fer, config.local_api_root)
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facial_features = partial(facial_features, config.local_api_root)
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image_features = partial(image_features, config.local_api_root)
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classification = partial(classification, config.local_api_root)
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named_entities = partial(named_entities, config.local_api_root)
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@@ -1,23 +0,0 @@
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from indicoio.utils import api_handler
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def named_entities(api_root, text):
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"""
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Given input text, returns a mapping from named entities to
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named entity categories.
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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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>>> text = 'On Monday, president Barack Obama will be...'
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>>> indicoio.named_entities(text)
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>>> "{'Monday': 'Time', 'Barack Obama': 'Person'}"
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:param text: The text to be analyzed.
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:type text: str or unicode
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:rtype: Dictionary of named entity, category pairs
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"""
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return api_handler(text, api_root + "ner")
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@@ -26,12 +26,6 @@ class FullAPIRun(unittest.TestCase):
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results = classification(text)
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self.assertTrue(categories < set(results.keys()))
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def test_named_entity_recognition(self):
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categories = set(['arts'])
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text = "On Monday, president Barack Obama will be..."
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results = named_entities(text)
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self.assertTrue('named entity' in set(results.keys()))
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def test_political(self):
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political_set = set(['Libertarian', 'Liberal', 'Conservative', 'Green'])
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test_string = "Guns don't kill people, people kill people."
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@@ -4,8 +4,7 @@ import os
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import numpy as np
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import skimage.io
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from indicoio import political, sentiment, fer, facial_features, language, image_features, \
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classification, named_entities
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from indicoio import political, sentiment, fer, facial_features, language, image_features, classification
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DIR = os.path.dirname(os.path.realpath(__file__))
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@@ -29,12 +28,6 @@ class FullAPIRun(unittest.TestCase):
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results = classification(text)
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self.assertTrue(categories < set(results.keys()))
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def test_named_entity_recognition(self):
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categories = set(['arts'])
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text = "On Monday, president Barack Obama will be..."
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results = named_entities(text)
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self.assertTrue('named entity' in set(results.keys()))
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def test_political(self):
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political_set = set(['Libertarian', 'Liberal', 'Conservative', 'Green'])
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test_string = "Guns don't kill people, people kill people."
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