face-video-analysis.py

import math
import pandas as pd

shots = pd.read_csv('shots.csv')
faces = pd.read_csv('face_result.csv')

significant_scenes = []
for idx, row in shots.iterrows():
    frames = list(range(
                 int(round(row['begin'])),
                 int(round(row['end'])) + 1
             ))
    joy, sorrow, anger, surprise = 0, 0, 0, 0
    for frame in frames:
        frame_png = '{}.png'.format(frame)
        face = faces.loc[faces['n_frame'] == frame_png]
        joy += int(face['joy'])
        sorrow += int(face['sorrow'])
        anger += int(face['anger'])
        surprise += int(face['surprise'])
    frames_faces = {
        'frames': [round(frame / 60.0, 2) for frame in frames],
        'joy': joy,
        'sorrow': sorrow,
        'anger': anger,
        'surprise': surprise,
        'total_emotions': joy + sorrow + anger + surprise
    }

    if (joy + sorrow + anger + surprise) != 0:
        significant_scenes.append(frames_faces)

significant_scenes = sorted(significant_scenes, key=lambda k: k['total_emotions'], reverse=True)

for scene in significant_scenes[:10]:
    emotions = ['joy', 'sorrow', 'anger', 'surprise']
    begin = scene['frames'][0]
    end = scene['frames'][-1]

    detected_emotions = []
    for emotion in emotions:
        if scene[emotion] != 0:
            detected_emotions.append({emotion: scene[emotion]})
    (begin_sec, begin_min) = math.modf(begin)
    url = 'https://youtu.be/exYXWI3tIsQ?t={}m{}s'.format(int(begin_min), int(begin_sec * 100))
    report = '{} '.format(url)
    for detected_emotion in detected_emotions:
        for key, value in detected_emotion.iteritems():
            report = report + key + ': ' + str(value) + ' '

    print(report)