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_2552_2643'
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({'transit': 548, 'driving': 546})
Potential Common Locations: Counter({'car': 546})
Establishing Shot Locations: Counter({'boat': 27, 'train': 3, 'building': 2})
Named Participants: Counter({'kate': 1})
Descriptors: ['sitting']
Active Actions: Counter({'driving': 2, 'drops': 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: d_2552_2643
Start Frame: 2552~00
End Frame: 2643~00
Scene Time: 00:42:32 - 00:44:03
Scene Runtime: 0:01:32

*Technical Details*
Aspect Ratio: 1.84
Avg. Shot Duration: 17.38
Avg. Brightness: 109
Avg. Contrast: 45

*Dialogue Cadence*
Sentences Per Minute: 19
Words Per Sentence 6.00
Questions Per Minute: 2.61
Pct. Questions: 14%

*Emotion*
Laughs Per Minute: 0.65
Profanity Per Minute: 0.00
Words Per Profanity: 0
Exclamations Per Minute: 0.00
In [7]:
scene_obj.display_cutaway_shots()
Out[7]:
[]
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()