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_3491_3543'
In [3]:
film_obj = load_film_object(film_id)
scene_obj = film_obj.scene_object(scene_id)
scene_obj.print_context_clues()

*Plot Context*
Establishing Shot Locations: Counter({'train': 9})
Named Participants: Counter({'detective melville': 1})
Descriptors: ['indoors', 'standing']
Held Items: Counter({'cell phone': 4, 'hand': 3})
Active Actions: Counter({'sleeping': 9, 'crossed': 2})
Left Wearing: Counter({'suit': 58})
Right Wearing: Counter({'white dress': 14, 'bathrobe': 2})
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_3491_3543
Start Frame: 3491~25
End Frame: 3543~25
Scene Time: 00:58:11 - 00:59:03
Scene Runtime: 0:00:53

*Technical Details*
Aspect Ratio: 1.78
Avg. Shot Duration: 16.08
Avg. Brightness: 41
Avg. Contrast: 35

*Dialogue Cadence*
Sentences Per Minute: 17
Words Per Sentence 6.93
Questions Per Minute: 3.40
Pct. Questions: 20%

*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()