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]:
'd_0168_0193'
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({'work': 17})
Potential Common Locations: Counter({'office': 11, 'cubicle': 6})
Descriptors: ['indoors', 'sitting']
Held Items: Counter({'magazine': 1, 'book': 1})
Active Actions: Counter({'hanging': 5, 'reading': 1, 'setting': 1, 'using': 1})
Left Wearing: Counter({'headset': 5})
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: d_0168_0193
Start Frame: 0168~00
End Frame: 0193~50
Scene Time: 00:02:48 - 00:03:13
Scene Runtime: 0:00:26

*Technical Details*
Aspect Ratio: 2.39
Avg. Shot Duration: 11.44
Avg. Brightness: 72
Avg. Contrast: 52

*Dialogue Cadence*
Sentences Per Minute: 29
Words Per Sentence 3.77
Questions Per Minute: 4.53
Pct. Questions: 15%

*Emotion*
Laughs Per Minute: 0.00
Profanity Per Minute: 0.00
Words Per Profanity: 0
Exclamations Per Minute: 0.00
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()