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_2901_2944'
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': 138, 'driving': 119})
Potential Common Locations: Counter({'car': 119})
Potential Other Locations: Counter({'street': 10})
Descriptors: ['outdoors', 'sitting', 'rain']
Held Items: Counter({'cell phone': 1})
Active Actions: Counter({'driving': 19, 'covering': 7, 'touching': 5, 'using': 3})
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_2901_2944
Start Frame: 2901~75
End Frame: 2944~00
Scene Time: 00:48:21 - 00:49:04
Scene Runtime: 0:00:43

*Technical Details*
Aspect Ratio: 2.39
Avg. Shot Duration: 14.17
Avg. Brightness: 33
Avg. Contrast: 43

*Dialogue Cadence*
Sentences Per Minute: 24
Words Per Sentence 4.35
Questions Per Minute: 1.39
Pct. Questions: 6%

*Emotion*
Laughs Per Minute: 0.00
Profanity Per Minute: 1.39
Words Per Profanity: 74
Exclamations Per Minute: 2.77
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()