In [1]:
import sys
sys.path.append('../../../../')
import os
from moviegoer.tables import load_film_object, film_id_and_scene_id_from_scene_directory
In [2]:
film_id, scene_id = film_id_and_scene_id_from_scene_directory()
scene_id
Out[2]:
't_3444_3476'
In [3]:
film_obj = load_film_object(film_id)
scene_obj = film_obj.scene_object(scene_id)
scene_obj.print_context_clues()

*Plot Context*
Context Themes: Counter({'dining': 67, 'transit': 13, 'driving': 13})
Potential Common Locations: Counter({'restaurant': 67, 'car': 13})
Potential Other Locations: Counter({'sidewalk': 40})
Establishing Shot Locations: Counter({'building': 3, 'plane': 1})
Named Participants: Counter({'robbie': 2})
Descriptors: ['indoors', 'standing']
Active Actions: Counter({'parked': 48, 'sit': 1})
In [4]:
scene_obj.display_anchor_shots()
In [5]:
scene_obj.display_scene_frames_large()
In [6]:
scene_obj.print_info()

*Scene Information*
Scene ID: t_3444_3476
Start Frame: 3444~75
End Frame: 3476~25
Scene Time: 00:57:24 - 00:57:56
Scene Runtime: 0:00:32

*Technical Details*
Aspect Ratio: 2.39
Avg. Shot Duration: 12.70
Avg. Brightness: 136
Avg. Contrast: 61

*Dialogue Cadence*
Sentences Per Minute: 39
Words Per Sentence 5.57
Questions Per Minute: 7.38
Pct. Questions: 19%

*Emotion*
Laughs Per Minute: 0.00
Profanity Per Minute: 0.00
Words Per Profanity: 0
Exclamations Per Minute: 1.85
In [7]:
scene_obj.display_cutaway_shots()
In [8]:
scene_obj.display_qna_frames()
In [9]:
scene_obj.display_first_p_sentence_frames()
In [10]:
scene_obj.display_second_p_address_frames()
In [11]:
scene_obj.display_exclamations()
In [12]:
scene_obj.display_laughs()
Out[12]:
[]
In [13]:
scene_obj.display_unintelligible_language()
In [14]:
scene_obj.display_long_take_shots()
Out[14]:
[]
In [15]:
scene_obj.display_color_shots()