In [1]:
import sys
sys.path.append('../../')
from moviegoer.tables import film_id_from_film_directory, load_film_object
from random import choice
In [2]:
film_id = film_id_from_film_directory()
film_id
Out[2]:
'anesthesia_2015'
In [3]:
film_obj = load_film_object(film_id)
film_obj.print_info()
*Film Information* Title, Release Year: Anesthesia (2015) File Runtime: 01:29:38 Film Runtime (No Credits): 1:23:50 *Technical Details* Aspect Ratio: 1.85 Avg. Shot Duration: 13.88 Avg. Brightness: 87 Avg. Contrast: 51 *Dialogue Cadence* Sentences Per Minute: 17 Words Per Sentence 5.55 Questions Per Minute: 2.72 Pct. Questions: 16% *Emotion* Pct. Upset Faces: 57% Laughs Per Minute: 0.13 Profanity Per Minute: 0.87 Words Per Profanity: 109 Exclamations Per Minute: 0.94
In [4]:
print(len(film_obj.scene_objects))
film_obj.display_scenes()
14
*Plot Context*
Context Themes: Counter({'dining': 3})
Establishing Shot Locations: Counter({'building': 1})
Descriptors: ['standing']
Active Actions: Counter({'smoking': 11, 'eating': 3})
Right Wearing: Counter({'knitted hat': 23, 'beanie': 9, 'hat looking at a man': 6, 'hat talking': 2, 'hat': 1, 'hat and gloves': 1, 'hat and mittens': 1})
*Plot Context*
Potential Other Locations: Counter({'hallway': 82})
Descriptors: ['indoors', 'standing']
Active Actions: Counter({'reading': 2})
Left Wearing: Counter({'coat': 29, 'blue coat': 2})
*Plot Context*
*Plot Context*
Potential Other Locations: Counter({'street': 56, 'sidewalk': 5})
Establishing Shot Locations: Counter({'building': 3})
Descriptors: ['outdoors', 'walking']
*Plot Context*
Establishing Shot Locations: Counter({'building': 3})
Named Participants: Counter({'marcia': 1})
Descriptors: ['indoors', 'standing']
Active Actions: Counter({'making': 1})
Left Wearing: Counter({'hat': 49, 'hat and scarf': 20, 'hat and a scarf': 12, 'hat and scarf looking down': 4, 'hat and scarf with a surprised look': 2, 'hat and a coat': 1, 'hat and scarf talking': 1, 'hat and scarf looking at something': 1, 'beanie': 1})
Right Wearing: Counter({'glasses and a knitted hat': 62})
*Plot Context*
Potential Common Locations: Counter({'bathroom': 1})
Establishing Shot Locations: Counter({'building': 3})
Descriptors: ['indoors', 'standing']
Active Actions: Counter({'crossed': 10})
Left Wearing: Counter({'suit': 57})
Right Wearing: Counter({'tan shirt': 18, 'tan shirt is talking to another man': 13})
*Plot Context*
Context Themes: Counter({'intimacy': 11})
Potential Other Locations: Counter({'hallway': 2})
Descriptors: ['indoors', 'standing']
Held Items: Counter({'cell phone': 2, 'control': 1})
Active Actions: Counter({'hugging': 11, 'touching': 1})
Left Wearing: Counter({'purple shirt': 57})
*Plot Context*
Context Themes: Counter({'transit': 395, 'driving': 394})
Potential Common Locations: Counter({'car': 394})
Descriptors: ['sitting']
Active Actions: Counter({'driving': 1})
Left Wearing: Counter({'scarf and a scarf around his neck': 6})
Right Wearing: Counter({'scarf': 1, 'scarf and a scarf around her neck': 1})
*Plot Context*
Context Themes: Counter({'work': 3})
Potential Common Locations: Counter({'office': 3})
Descriptors: ['indoors', 'sitting']
*Plot Context*
Context Themes: Counter({'intimacy': 12})
Descriptors: ['indoors']
Active Actions: Counter({'kissing': 12, 'touching': 1})
*Plot Context*
Named Participants: Counter({'sam': 1})
*Plot Context*
Named Participants: Counter({'joe': 1})
Left Wearing: Counter({'suit': 41})
*Plot Context*
Context Themes: Counter({'dining': 62, 'violence': 1})
Potential Common Locations: Counter({'kitchen': 61})
Potential Other Locations: Counter({'doorway': 65})
Establishing Shot Locations: Counter({'building': 1})
Named Participants: Counter({'hal': 1, 'ella': 1})
Descriptors: ['indoors', 'standing']
Held Items: Counter({'knife': 1})
Active Actions: Counter({'sleeping': 10, 'open': 3, 'covered': 2})
Left Wearing: Counter({'yellow shirt': 16, 'white shirt': 9})
*Plot Context*
Context Themes: Counter({'transit': 9, 'driving': 9})
Potential Common Locations: Counter({'car': 9})
Potential Other Locations: Counter({'street': 39, 'parking lot': 6, 'city': 2})
Establishing Shot Locations: Counter({'building': 9})
Descriptors: ['outdoors', 'standing']
Held Items: Counter({'cell phone': 1})
Left Wearing: Counter({'hat': 31, 'hat and scarf standing': 4, 'hat and scarf': 2})
Right Wearing: Counter({'beanie': 51, 'beanie and a sweater': 4, 'beanie and a backpack': 3, 'beanie and a jacket': 1})
Out[4]:
[None, None, None, None, None, None, None, None, None, None, None, None, None, None]
In [5]:
film_obj.chart_all_dialogue_emotional_indicators()
In [6]:
film_obj.chart_all_dialogue_shape()
In [7]:
film_obj.chart_all_dialogue_question_proportion()
In [8]:
film_obj.display_color_shots()
In [9]:
rand_scene = None
if film_obj.dialogue_objects:
rand_scene = choice(film_obj.dialogue_objects)
rand_scene.display_qna_frames()
In [10]:
if rand_scene:
rand_scene.display_first_p_sentence_frames()
In [11]:
if rand_scene:
rand_scene.display_second_p_address_frames()
In [12]:
film_obj.display_laughs()
Out[12]:
[]
In [13]:
film_obj.display_unintelligible_language()
WOMAN SINGING IN FOREIGN LANGUAGE
In [14]:
film_obj.display_self_intros()
In [15]:
film_obj.display_other_intros()