mirror of
https://github.com/gsi-upm/senpy
synced 2025-10-24 04:08:19 +00:00
Refactored conversion and postprocessing
This commit is contained in:
J. Fernando Sánchez
0
senpy/plugins/postprocessing/__init__.py
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0
senpy/plugins/postprocessing/__init__.py
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0
senpy/plugins/postprocessing/emotion/__init__.py
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0
senpy/plugins/postprocessing/emotion/__init__.py
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158
senpy/plugins/postprocessing/emotion/centroids.py
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158
senpy/plugins/postprocessing/emotion/centroids.py
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@@ -0,0 +1,158 @@
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from senpy.plugins import EmotionConversionPlugin
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from senpy.models import EmotionSet, Emotion, Error
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import logging
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logger = logging.getLogger(__name__)
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class CentroidConversion(EmotionConversionPlugin):
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'''
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This plugin converts emotion annotations from a dimensional model to a
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categorical one, and vice versa. The centroids used in the conversion
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are configurable and appear in the semantic description of the plugin.
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'''
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def __init__(self, info, *args, **kwargs):
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if 'centroids' not in info:
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raise Error('Centroid conversion plugins should provide '
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'the centroids in their senpy file')
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if 'onyx:doesConversion' not in info:
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if 'centroids_direction' not in info:
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raise Error('Please, provide centroids direction')
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cf, ct = info['centroids_direction']
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info['onyx:doesConversion'] = [{
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'onyx:conversionFrom': cf,
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'onyx:conversionTo': ct
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}, {
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'onyx:conversionFrom': ct,
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'onyx:conversionTo': cf
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}]
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if 'aliases' in info:
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aliases = info['aliases']
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ncentroids = {}
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for k1, v1 in info['centroids'].items():
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nv1 = {}
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for k2, v2 in v1.items():
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nv1[aliases.get(k2, k2)] = v2
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ncentroids[aliases.get(k1, k1)] = nv1
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info['centroids'] = ncentroids
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super(CentroidConversion, self).__init__(info, *args, **kwargs)
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self.dimensions = set()
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for c in self.centroids.values():
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self.dimensions.update(c.keys())
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self.neutralPoints = self.get("neutralPoints", dict())
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if not self.neutralPoints:
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for i in self.dimensions:
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self.neutralPoints[i] = self.get("neutralValue", 0)
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def _forward_conversion(self, original):
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"""Sum the VAD value of all categories found weighted by intensity.
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Intensities are scaled by onyx:maxIntensityValue if it is present, else maxIntensityValue
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is assumed to be one. Emotion entries that do not have onxy:hasEmotionIntensity specified
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are assumed to have maxIntensityValue. Emotion entries that do not have
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onyx:hasEmotionCategory specified are ignored."""
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res = Emotion()
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maxIntensity = float(original.get("onyx:maxIntensityValue", 1))
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for e in original.onyx__hasEmotion:
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category = e.get("onyx:hasEmotionCategory", None)
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if not category:
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continue
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intensity = e.get("onyx:hasEmotionIntensity", maxIntensity) / maxIntensity
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if not intensity:
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continue
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centroid = self.centroids.get(category, None)
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if centroid:
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for dim, value in centroid.items():
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neutral = self.neutralPoints[dim]
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if dim not in res:
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res[dim] = 0
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res[dim] += (value - neutral) * intensity + neutral
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return res
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def _backwards_conversion(self, original):
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"""Find the closest category"""
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centroids = self.centroids
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neutralPoints = self.neutralPoints
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dimensions = self.dimensions
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def distance_k(centroid, original, k):
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# k component of the distance between the value and a given centroid
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return (centroid.get(k, neutralPoints[k]) - original.get(k, neutralPoints[k]))**2
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def distance(centroid):
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return sum(distance_k(centroid, original, k) for k in dimensions)
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emotion = min(centroids, key=lambda x: distance(centroids[x]))
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result = Emotion(onyx__hasEmotionCategory=emotion)
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result.onyx__algorithmConfidence = distance(centroids[emotion])
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return result
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def convert(self, emotionSet, fromModel, toModel, params):
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cf, ct = self.centroids_direction
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logger.debug(
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'{}\n{}\n{}\n{}'.format(emotionSet, fromModel, toModel, params))
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e = EmotionSet()
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if fromModel == cf and toModel == ct:
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e.onyx__hasEmotion.append(self._forward_conversion(emotionSet))
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elif fromModel == ct and toModel == cf:
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for i in emotionSet.onyx__hasEmotion:
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e.onyx__hasEmotion.append(self._backwards_conversion(i))
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else:
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raise Error('EMOTION MODEL NOT KNOWN')
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yield e
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def test(self, info=None):
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if not info:
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info = {
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"name": "CentroidTest",
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"description": "Centroid test",
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"version": 0,
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"centroids": {
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"c1": {"V1": 0.5,
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"V2": 0.5},
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"c2": {"V1": -0.5,
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"V2": 0.5},
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"c3": {"V1": -0.5,
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"V2": -0.5},
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"c4": {"V1": 0.5,
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"V2": -0.5}},
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"aliases": {
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"V1": "X-dimension",
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"V2": "Y-dimension"
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},
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"centroids_direction": ["emoml:big6", "emoml:fsre-dimensions"]
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}
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c = CentroidConversion(info)
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es1 = EmotionSet()
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e1 = Emotion()
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e1.onyx__hasEmotionCategory = "c1"
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es1.onyx__hasEmotion.append(e1)
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res = c._forward_conversion(es1)
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assert res["X-dimension"] == 0.5
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assert res["Y-dimension"] == 0.5
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e2 = Emotion()
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e2.onyx__hasEmotionCategory = "c2"
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es1.onyx__hasEmotion.append(e2)
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res = c._forward_conversion(es1)
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assert res["X-dimension"] == 0
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assert res["Y-dimension"] == 1
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e = Emotion()
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e["X-dimension"] = -0.2
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e["Y-dimension"] = -0.3
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res = c._backwards_conversion(e)
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assert res["onyx:hasEmotionCategory"] == "c3"
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e = Emotion()
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e["X-dimension"] = -0.2
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e["Y-dimension"] = 0.3
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res = c._backwards_conversion(e)
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assert res["onyx:hasEmotionCategory"] == "c2"
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52
senpy/plugins/postprocessing/emotion/ekman2fsre.senpy
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52
senpy/plugins/postprocessing/emotion/ekman2fsre.senpy
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@@ -0,0 +1,52 @@
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---
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name: Ekman2FSRE
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module: senpy.plugins.postprocessing.emotion.centroids
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description: Plugin to convert emotion sets from Ekman to VAD
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version: 0.2
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# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
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neutralValue: 5.0
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centroids:
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anger:
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A: 6.95
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D: 5.1
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V: 2.7
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S: 5.0
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disgust:
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A: 5.3
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D: 8.05
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V: 2.7
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S: 5.0
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fear:
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A: 6.5
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D: 3.6
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V: 3.2
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S: 5.0
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happiness:
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A: 7.22
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D: 6.28
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V: 8.6
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S: 5.0
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sadness:
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A: 5.21
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D: 2.82
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V: 2.21
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S: 5.0
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surprise:
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A: 5.0
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D: 5.0
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V: 5.0
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S: 10.0
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centroids_direction:
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- emoml:big6
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- emoml:fsre-dimensions
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aliases: # These are aliases for any key in the centroid, to avoid repeating a long name several times
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A: emoml:fsre-dimensions_arousal
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V: emoml:fsre-dimensions_valence
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D: emoml:fsre-dimensions_potency
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S: emoml:fsre-dimensions_unpredictability
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anger: emoml:big6anger
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disgust: emoml:big6disgust
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fear: emoml:big6fear
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happiness: emoml:big6happiness
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sadness: emoml:big6sadness
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surprise: emoml:big6surprise
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40
senpy/plugins/postprocessing/emotion/ekman2vad.senpy
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40
senpy/plugins/postprocessing/emotion/ekman2vad.senpy
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@@ -0,0 +1,40 @@
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---
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name: Ekman2PAD
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module: senpy.plugins.postprocessing.emotion.centroids
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description: Plugin to convert emotion sets from Ekman to VAD
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version: 0.2
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# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
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neutralValue: 5.0
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centroids:
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anger:
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A: 6.95
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D: 5.1
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V: 2.7
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disgust:
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A: 5.3
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D: 8.05
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V: 2.7
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fear:
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A: 6.5
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D: 3.6
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V: 3.2
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happiness:
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A: 7.22
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D: 6.28
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V: 8.6
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sadness:
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A: 5.21
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D: 2.82
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V: 2.21
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centroids_direction:
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- emoml:big6
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- emoml:pad
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aliases: # These are aliases for any key in the centroid, to avoid repeating a long name several times
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A: emoml:pad-dimensions:arousal
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V: emoml:pad-dimensions:pleasure
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D: emoml:pad-dimensions:dominance
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anger: emoml:big6anger
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disgust: emoml:big6disgust
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fear: emoml:big6fear
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happiness: emoml:big6happiness
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sadness: emoml:big6sadness
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196
senpy/plugins/postprocessing/emotion/maxEmotion_plugin.py
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196
senpy/plugins/postprocessing/emotion/maxEmotion_plugin.py
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@@ -0,0 +1,196 @@
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from senpy import PostProcessing, easy_test
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class MaxEmotion(PostProcessing):
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'''Plugin to extract the emotion with highest value from an EmotionSet'''
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author = '@dsuarezsouto'
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version = '0.1'
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def process_entry(self, entry, params):
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if len(entry.emotions) < 1:
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yield entry
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return
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set_emotions = entry.emotions[0]['onyx:hasEmotion']
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# If there is only one emotion, do not modify it
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if len(set_emotions) < 2:
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yield entry
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return
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max_emotion = set_emotions[0]
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# Extract max emotion from the set emotions (emotion with highest intensity)
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for tmp_emotion in set_emotions:
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if tmp_emotion['onyx:hasEmotionIntensity'] > max_emotion[
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'onyx:hasEmotionIntensity']:
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max_emotion = tmp_emotion
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if max_emotion['onyx:hasEmotionIntensity'] == 0:
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max_emotion['onyx:hasEmotionCategory'] = "neutral"
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max_emotion['onyx:hasEmotionIntensity'] = 1.0
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entry.emotions[0]['onyx:hasEmotion'] = [max_emotion]
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entry.emotions[0]['prov:wasGeneratedBy'] = "maxSentiment"
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yield entry
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def check(self, request, plugins):
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return 'maxemotion' in request.parameters and self not in plugins
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# Test Cases:
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# 1 Normal Situation.
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# 2 Case to return a Neutral Emotion.
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test_cases = [
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{
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"name":
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"If there are several emotions within an emotion set, reduce it to one.",
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"entry": {
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"@type":
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"entry",
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"emotions": [
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{
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"@id":
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"Emotions0",
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"@type":
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"emotionSet",
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"onyx:hasEmotion": [
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "anger",
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"onyx:hasEmotionIntensity": 0
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},
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "joy",
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"onyx:hasEmotionIntensity": 0.3333333333333333
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},
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "negative-fear",
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"onyx:hasEmotionIntensity": 0
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},
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "sadness",
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"onyx:hasEmotionIntensity": 0
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},
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "disgust",
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"onyx:hasEmotionIntensity": 0
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}
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]
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}
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],
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"nif:isString":
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"Test"
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},
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'expected': {
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"@type":
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"entry",
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"emotions": [
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{
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"@id":
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"Emotions0",
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"@type":
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"emotionSet",
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"onyx:hasEmotion": [
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "joy",
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"onyx:hasEmotionIntensity": 0.3333333333333333
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}
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],
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"prov:wasGeneratedBy":
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'maxSentiment'
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}
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],
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"nif:isString":
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"Test"
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}
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},
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{
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"name":
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"If the maximum emotion has an intensity of 0, return a neutral emotion.",
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"entry": {
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"@type":
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"entry",
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"emotions": [{
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"@id":
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"Emotions0",
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"@type":
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"emotionSet",
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"onyx:hasEmotion": [
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "anger",
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"onyx:hasEmotionIntensity": 0
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},
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "joy",
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"onyx:hasEmotionIntensity": 0
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},
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{
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"@id":
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"_:Emotion_1538121033.74",
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"@type":
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"emotion",
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"onyx:hasEmotionCategory":
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"negative-fear",
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"onyx:hasEmotionIntensity":
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0
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},
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory":
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"sadness",
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"onyx:hasEmotionIntensity": 0
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},
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{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory":
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"disgust",
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"onyx:hasEmotionIntensity": 0
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}]
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}],
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"nif:isString":
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"Test"
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},
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'expected': {
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"@type":
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"entry",
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"emotions": [{
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"@id":
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"Emotions0",
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"@type":
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"emotionSet",
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"onyx:hasEmotion": [{
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"@id": "_:Emotion_1538121033.74",
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"@type": "emotion",
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"onyx:hasEmotionCategory": "neutral",
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"onyx:hasEmotionIntensity": 1
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}],
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"prov:wasGeneratedBy":
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'maxSentiment'
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}],
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"nif:isString":
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"Test"
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}
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}
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]
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if __name__ == '__main__':
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easy_test()
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