Module vipy.data.charades

Classes

class Charades (datadir, annodir)

Charades, provide paths such that datadir contains the contents of 'http://ai2-website.s3.amazonaws.com/data/Charades_v1.zip' and annodir contains 'http://ai2-website.s3.amazonaws.com/data/Charades.zip'.
These are license restructed and must be downloaded by the user

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class Charades(object):
    def __init__(self, datadir, annodir):
        """Charades, provide paths such that datadir contains the contents of 'http://ai2-website.s3.amazonaws.com/data/Charades_v1.zip' and annodir contains 'http://ai2-website.s3.amazonaws.com/data/Charades.zip'.  
        These are license restructed and must be downloaded by the user"""
        self.datadir = datadir
        self.annodir = annodir
        if not self._isdownloaded():
            raise ValueError('Not downloaded')
            
    def __repr__(self):
        return str('<vipy.data.charades: datadir="%s", annotations="%s">' % (self.datadir, self.annodir))

    def _isdownloaded(self):
        return os.path.exists(os.path.join(self.annodir, 'Charades_v1_train.csv')) and os.path.exists(os.path.join(self.datadir, 'ZZXQF.mp4'))
    
    def _dataset(self, csvfile):
        csv = readcsv(csvfile)

        d_index_to_category = self.categories()
        d_videoid_to_video = {}
        for row in csv[1:]:            
            videoid = row[0]
            actions = row[-2]
            sceneloc = row[2]
            if videoid not in d_videoid_to_video:
                v = Scene(filename=os.path.join(self.datadir, '%s.mp4' % videoid), category=sceneloc)
                fps = v.probe()['streams'][0]['avg_frame_rate']
                fps = float(fps.split('/')[0]) / float(fps.split('/')[1])
                v.framerate(fps)  # FIXME: better handling of time based clips to avoid ffprobe
                d_videoid_to_video[videoid] = v                
            assert d_videoid_to_video[videoid].category() == sceneloc
            
            if len(actions) > 0:
                for a in actions.split(';'):
                    (category, startsec, endsec) = a.split(' ')
                    try:
                        d_videoid_to_video[videoid].add(Activity(category=d_index_to_category[category], startframe=float(startsec)*fps, endframe=float(endsec)*fps, attributes={'csvfile':row}))
                    except KeyboardInterrupt:
                        raise
                    except Exception as e:
                        print('[vipy.data.charades]: SKIPPING invalid activity row="%s" with error "%s"' % (str(row),str(e)))
                        
        return list(d_videoid_to_video.values())

    def categories(self):
        return {x.split(' ', 1)[0]:x.split(' ', 1)[1].strip() for x in readlist(os.path.join(self.annodir, 'Charades_v1_classes.txt'))}

    def trainset(self):
        return self._dataset(os.path.join(self.annodir, 'Charades_v1_train.csv'))

    def testset(self):
        return self._dataset(os.path.join(self.annodir, 'Charades_v1_test.csv'))

    def review(self, outfile=None, mindim=1024, n=25):
        """Generate a standalone HTML file containing quicklooks for each annotated activity in the train set"""
        from vipy.batch import Batch
        import vipy.visualize
        
        T = self.trainset()
        quicklist = Batch(T).map(lambda v: [(c.load().quicklook(n=n), c.activitylist(), str(c.flush().print())) for c in v.mindim(512).activityclip()]).result()
        quicklooks = [imq for q in quicklist for (imq, activitylist, description) in q]  # for HTML display purposes
        provenance = [{'clip':str(description), 'activity':str(a), 'category':a.category(), 'train.csv':a.attributes['csvfile']} for q in quicklist for (imq, activitylist, description) in q for a in activitylist]
        (quicklooks, provenance) = zip(*sorted([(q,p) for (q,p) in zip(quicklooks, provenance)], key=lambda x: x[1]['category']))  # sorted in category order
        return vipy.visualize.tohtml(quicklooks, provenance, title='Charades trainset quicklooks', outfile=outfile, mindim=mindim)

Methods

def categories(self)

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def categories(self):
    return {x.split(' ', 1)[0]:x.split(' ', 1)[1].strip() for x in readlist(os.path.join(self.annodir, 'Charades_v1_classes.txt'))}

def review(self, outfile=None, mindim=1024, n=25)

Generate a standalone HTML file containing quicklooks for each annotated activity in the train set

Expand source code Browse git

def review(self, outfile=None, mindim=1024, n=25):
    """Generate a standalone HTML file containing quicklooks for each annotated activity in the train set"""
    from vipy.batch import Batch
    import vipy.visualize
    
    T = self.trainset()
    quicklist = Batch(T).map(lambda v: [(c.load().quicklook(n=n), c.activitylist(), str(c.flush().print())) for c in v.mindim(512).activityclip()]).result()
    quicklooks = [imq for q in quicklist for (imq, activitylist, description) in q]  # for HTML display purposes
    provenance = [{'clip':str(description), 'activity':str(a), 'category':a.category(), 'train.csv':a.attributes['csvfile']} for q in quicklist for (imq, activitylist, description) in q for a in activitylist]
    (quicklooks, provenance) = zip(*sorted([(q,p) for (q,p) in zip(quicklooks, provenance)], key=lambda x: x[1]['category']))  # sorted in category order
    return vipy.visualize.tohtml(quicklooks, provenance, title='Charades trainset quicklooks', outfile=outfile, mindim=mindim)

def testset(self)

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def testset(self):
    return self._dataset(os.path.join(self.annodir, 'Charades_v1_test.csv'))

def trainset(self)

Expand source code Browse git

def trainset(self):
    return self._dataset(os.path.join(self.annodir, 'Charades_v1_train.csv'))