Exemplo n.º 1
0
    def __init__(self, scene=None, speaker=None):
        self.scene = scene
        if scene is None:
            self.scene = Scene(3)

            # not a very furnished scene, we only have one table
            table = Landmark('table',
                             RectangleRepresentation(rect=BoundingBox([Vec2(5,5), Vec2(6,7)])),
                             None,
                             ObjectClass.TABLE)

            self.scene.add_landmark(table)
            self.table = table

        self.table = self.scene.landmarks['table']

        # there is a person standing at this location
        # he will be our reference
        if speaker is None:
            self.speaker = Speaker(Vec2(5.5, 4.5))
        else:
            self.speaker = speaker

        # NOTE we need to keep around the list of landmarks so that we can
        # access them by id, which is the index of the landmark in this list
        # collect all possible landmarks
        self.landmarks = []
        for scene_lmk in self.scene.landmarks.itervalues():
            self.landmarks.append(scene_lmk)

            # a scene can be represented as a plane, line, etc
            # each representation of a scene has different landmarks
            rs = [scene_lmk.representation]
            rs.extend(scene_lmk.representation.get_alt_representations())

            for r in rs:
                for lmk in r.get_landmarks():
                    self.landmarks.append(lmk)

        # FIXME we are using sentences with 1 or 2 LANDMARK-PHRASEs
        # so we need to restrict the landmarks to 0 or 1 ancestors
        self.landmarks = [l for l in self.landmarks if l.get_ancestor_count() < 2]
Exemplo n.º 2
0
    def __init__(self, scene=None, speaker=None):
        self.scene = scene
        if scene is None:
            self.scene = Scene(3)

            # not a very furnished scene, we only have one table
            table = Landmark('table',
                             RectangleRepresentation(rect=BoundingBox([Vec2(5,5), Vec2(6,7)])),
                             None,
                             ObjectClass.TABLE)

            self.scene.add_landmark(table)
            self.table = table

        self.table = self.scene.landmarks['table']

        # there is a person standing at this location
        # he will be our reference
        if speaker is None:
            self.speaker = Speaker(Vec2(5.5, 4.5))
        else:
            self.speaker = speaker

        # NOTE we need to keep around the list of landmarks so that we can
        # access them by id, which is the index of the landmark in this list
        # collect all possible landmarks
        self.landmarks = []
        for scene_lmk in self.scene.landmarks.itervalues():
            self.landmarks.append(scene_lmk)

            # a scene can be represented as a plane, line, etc
            # each representation of a scene has different landmarks
            rs = [scene_lmk.representation]
            rs.extend(scene_lmk.representation.get_alt_representations())

            for r in rs:
                for lmk in r.get_landmarks():
                    self.landmarks.append(lmk)

        # FIXME we are using sentences with 1 or 2 LANDMARK-PHRASEs
        # so we need to restrict the landmarks to 0 or 1 ancestors
        self.landmarks = [l for l in self.landmarks if l.get_ancestor_count() < 2]
Exemplo n.º 3
0
class ModelScene(object):
    def __init__(self, scene=None, speaker=None):
        self.scene = scene
        if scene is None:
            self.scene = Scene(3)

            # not a very furnished scene, we only have one table
            table = Landmark('table',
                             RectangleRepresentation(rect=BoundingBox([Vec2(5,5), Vec2(6,7)])),
                             None,
                             ObjectClass.TABLE)

            self.scene.add_landmark(table)
            self.table = table

        self.table = self.scene.landmarks['table']

        # there is a person standing at this location
        # he will be our reference
        if speaker is None:
            self.speaker = Speaker(Vec2(5.5, 4.5))
        else:
            self.speaker = speaker

        # NOTE we need to keep around the list of landmarks so that we can
        # access them by id, which is the index of the landmark in this list
        # collect all possible landmarks
        self.landmarks = []
        for scene_lmk in self.scene.landmarks.itervalues():
            self.landmarks.append(scene_lmk)

            # a scene can be represented as a plane, line, etc
            # each representation of a scene has different landmarks
            rs = [scene_lmk.representation]
            rs.extend(scene_lmk.representation.get_alt_representations())

            for r in rs:
                for lmk in r.get_landmarks():
                    self.landmarks.append(lmk)

        # FIXME we are using sentences with 1 or 2 LANDMARK-PHRASEs
        # so we need to restrict the landmarks to 0 or 1 ancestors
        self.landmarks = [l for l in self.landmarks if l.get_ancestor_count() < 2]

    def get_rand_loc(self):
        """returns a random location on the table"""
        bb = self.table.representation.get_geometry()
        xmin, ymin = bb.min_point
        xmax, ymax = bb.max_point
        return random.uniform(xmin, xmax), random.uniform(ymin, ymax)

    def get_landmark_id(self, lmk):
        return self.landmarks.index(lmk)

    def get_landmark_by_id(self, lmk_id):
        return self.landmarks[lmk_id]

    def sample_lmk_rel(self, loc, num_ancestors=None):
        """gets a location and returns a landmark and a relation
        that can be used to describe the given location"""
        landmarks = self.landmarks

        if num_ancestors is not None:
            landmarks = [l for l in landmarks if l.get_ancestor_count() == num_ancestors]

        loc = Landmark(None, PointRepresentation(loc), None, None)
        lmk, lmk_prob, lmk_entropy, head_on = self.speaker.sample_landmark( landmarks, loc )
        rel, rel_prob, rel_entropy = self.speaker.sample_relation(loc, self.table.representation.get_geometry(), head_on, lmk, step=0.5)
        rel = rel(head_on,lmk,loc)

        return (lmk, lmk_prob, lmk_entropy), (rel, rel_prob, rel_entropy)
Exemplo n.º 4
0
class ModelScene(object):
    def __init__(self, scene=None, speaker=None):
        self.scene = scene
        if scene is None:
            self.scene = Scene(3)

            # not a very furnished scene, we only have one table
            table = Landmark('table',
                             RectangleRepresentation(rect=BoundingBox([Vec2(5,5), Vec2(6,7)])),
                             None,
                             ObjectClass.TABLE)

            self.scene.add_landmark(table)
            self.table = table

        self.table = self.scene.landmarks['table']

        # there is a person standing at this location
        # he will be our reference
        if speaker is None:
            self.speaker = Speaker(Vec2(5.5, 4.5))
        else:
            self.speaker = speaker

        # NOTE we need to keep around the list of landmarks so that we can
        # access them by id, which is the index of the landmark in this list
        # collect all possible landmarks
        self.landmarks = []
        for scene_lmk in self.scene.landmarks.itervalues():
            self.landmarks.append(scene_lmk)

            # a scene can be represented as a plane, line, etc
            # each representation of a scene has different landmarks
            rs = [scene_lmk.representation]
            rs.extend(scene_lmk.representation.get_alt_representations())

            for r in rs:
                for lmk in r.get_landmarks():
                    self.landmarks.append(lmk)

        # FIXME we are using sentences with 1 or 2 LANDMARK-PHRASEs
        # so we need to restrict the landmarks to 0 or 1 ancestors
        self.landmarks = [l for l in self.landmarks if l.get_ancestor_count() < 2]

    def get_rand_loc(self):
        """returns a random location on the table"""
        bb = self.table.representation.get_geometry()
        xmin, ymin = bb.min_point
        xmax, ymax = bb.max_point
        return random.uniform(xmin, xmax), random.uniform(ymin, ymax)

    def get_landmark_id(self, lmk):
        return self.landmarks.index(lmk)

    def get_landmark_by_id(self, lmk_id):
        return self.landmarks[lmk_id]

    def sample_lmk_rel(self, loc, num_ancestors=None):
        """gets a location and returns a landmark and a relation
        that can be used to describe the given location"""
        landmarks = self.landmarks

        if num_ancestors is not None:
            landmarks = [l for l in landmarks if l.get_ancestor_count() == num_ancestors]

        loc = Landmark(None, PointRepresentation(loc), None, None)
        lmk, lmk_prob, lmk_entropy, head_on = self.speaker.sample_landmark( landmarks, loc )
        rel, rel_prob, rel_entropy = self.speaker.sample_relation(loc, self.table.representation.get_geometry(), head_on, lmk, step=0.5)
        rel = rel(head_on,lmk,loc)

        return (lmk, lmk_prob, lmk_entropy), (rel, rel_prob, rel_entropy)