mirror of
https://github.com/gsi-upm/senpy
synced 2024-11-21 15:52:28 +00:00
Merge branch '36-estimate-vad'
This commit is contained in:
commit
c9bc485535
@ -84,7 +84,15 @@ deploy:
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only:
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- master
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clean_docker :
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push-github:
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stage: deploy
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script:
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- make -e push-github
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only:
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- master
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- triggers
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clean :
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stage: clean
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script:
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- make -e clean
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1
Makefile
1
Makefile
@ -12,6 +12,7 @@ DEVPORT=5000
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TARNAME=$(NAME)-$(VERSION).tar.gz
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action="test-${PYMAIN}"
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GITHUB_REPO=git@github.com:gsi-upm/senpy.git
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KUBE_CA_PEM_FILE=""
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KUBE_URL=""
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0
senpy/plugins/conversion/emotion/__init__.py
Normal file
0
senpy/plugins/conversion/emotion/__init__.py
Normal file
@ -32,36 +32,58 @@ class CentroidConversion(EmotionConversionPlugin):
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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)
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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."""
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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.onyx__hasEmotionCategory
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if category in self.centroids:
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for dim, value in self.centroids[category].items():
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try:
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res[dim] += value
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except Exception:
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res[dim] = value
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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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dimensions = list(self.centroids.values())[0]
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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(e1, e2):
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return sum((e1[k] - e2.get(k, 0)) for k in 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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emotion = ''
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mindistance = 10000000000000000000000.0
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for state in self.centroids:
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d = distance(self.centroids[state], original)
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if d < mindistance:
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mindistance = d
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emotion = state
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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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@ -1,6 +1,6 @@
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---
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name: Ekman2FSRE
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module: senpy.plugins.conversion.centroids
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module: senpy.plugins.conversion.emotion.centroids
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description: Plugin to convert emotion sets from Ekman to VAD
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version: 0.1
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# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
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@ -1,9 +1,14 @@
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---
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name: Ekman2PAD
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module: senpy.plugins.conversion.centroids
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module: senpy.plugins.conversion.emotion.centroids
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description: Plugin to convert emotion sets from Ekman to VAD
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version: 0.1
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# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
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origin:
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# Point in VAD space with no emotion (aka Neutral)
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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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centroids:
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anger:
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A: 6.95
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@ -11,7 +11,7 @@ def read_version(versionfile=DEFAULT_FILE):
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try:
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with open(versionfile) as f:
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return f.read().strip()
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except IOError:
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except IOError: # pragma: no cover
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logger.error('Running an unknown version of senpy. Be careful!.')
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return '0.0'
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@ -6,8 +6,9 @@ import shutil
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import tempfile
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from unittest import TestCase
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from senpy.models import Results, Entry
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from senpy.models import Results, Entry, EmotionSet, Emotion
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from senpy.plugins import SentimentPlugin, ShelfMixin
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from senpy.plugins.conversion.emotion.centroids import CentroidConversion
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class ShelfDummyPlugin(SentimentPlugin, ShelfMixin):
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@ -152,3 +153,52 @@ class PluginsTest(TestCase):
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}
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})
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assert 'example' in a.extra_params
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def test_conversion_centroids(self):
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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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