320 lines
12 KiB
Python
Executable File
320 lines
12 KiB
Python
Executable File
from google.cloud import translate_v2 as Translate
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from google.cloud import translate
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from MNF.settings import BasePath
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# from .script_writing import default_script
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from .translation_variables import code_script
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from .script_detector import script_cat
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from statistics import mode
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from collections import Counter
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# import textract
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from tqdm import tqdm
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import sys
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import re
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import os
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from .script_reading import getRefined, getSlugAndNonSlug, getSpeakers, getScenes
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import requests
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import uuid
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import json
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import boto3
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from collections import Counter
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basePath = BasePath()
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# -> Google Translation API Credentials
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os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = rf"{basePath}/MNF/json_keys/authentication.json"
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translate_client = Translate.Client()
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client = translate.TranslationServiceClient()
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# -> For Detecting language of any text
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def language_detector(text):
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lang_detected = []
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print(text,"sentence recieved")
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#primary language detector
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result = translate_client.detect_language(text)
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print("length re:",len(result['language']))
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if len(result['language']) > 3:
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#print((str(result['language']).split("-"))[0])
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return (str(result['language']).split("-"))[0]
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#lang_detected.append((str(result['language']).split("-"))[0])
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else:
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#lang_detected.append(result['language'])
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return result['language']
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# takes too long to use this
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#secondary translation_detection
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try:
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subscription_key = "83ce6233419541929f7ab0d3035fca58"
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location = "eastus"
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headers = {
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'Ocp-Apim-Subscription-Key': subscription_key,
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'Ocp-Apim-Subscription-Region': location,
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'Content-type': 'application/json',
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'X-ClientTraceId': str(uuid.uuid4())
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}
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params = {'api-version': '3.0'}
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body = [{'text': text}]
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request = requests.post("https://api.cognitive.microsofttranslator.com/detect?api-version=3.0", params=params,
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headers=headers, json=body)
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response = request.json()
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lang_detected.append(str(response[0]['language']))
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except:
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print("azure is not working ")
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pass
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#tertiary translation_detection
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try:
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aws_json_path = basePath + "/MNF/json_keys"
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with open(rf"{aws_json_path}/keys_aws.json") as f:
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keys1 = json.load(f)
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session = boto3.Session(aws_access_key_id=keys1["aws_access_key_id"],
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aws_secret_access_key=keys1["aws_secret_access_key"],
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region_name=keys1["region_name"])
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detect_aws = session.client(service_name='comprehend', region_name='us-east-2', use_ssl=True)
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pred_3 = (detect_aws.detect_dominant_language(Text=text))['Languages'][0]["LanguageCode"]
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lang_detected.append(str(pred_3))
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except:
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print("aws is not working ")
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pass
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most_common_lang = Counter(lang_detected)
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sorted_values = sorted(most_common_lang.values(), reverse=True) # Sort the values
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sorted_dict = {}
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for i in sorted_values:
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for k in most_common_lang.keys():
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if most_common_lang[k] == i:
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sorted_dict[k] = most_common_lang[k]
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sources = list(sorted_dict.keys())
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return sources[0]
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# -> For Detecting Script of any text
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def script_det(text):
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punctuations = '''!()-[]{};:'"\,<>./?@#$%^&*_~'''
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no_punct = ""
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for char in text:
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if char not in punctuations:
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no_punct = char
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break
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script = script_cat(no_punct)[0]
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return script
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'''
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A. Language of Highest number of full dialogues,
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B. Numbers of dialogues in action line language,
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C. Number of dialogues in other languages)
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'''
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# -> For Detecting presence of different languages in dialogues (whole sentences)
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def A_B_C(dialogue_language, non_dial_src_lang):
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print("line 316:dialogue_language", dialogue_language)
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dict1 = dict(Counter(dialogue_language))
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print("line 319:dict1", dict1)
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sorted_values = sorted(dict1.values(), reverse=True) # Sort the values
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print("line 321:sorted_values:", sorted_values)
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sorted_dict = {}
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for i in sorted_values:
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for k in dict1.keys():
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if dict1[k] == i:
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sorted_dict[k] = dict1[k]
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sources = list(sorted_dict.keys())
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print("line 328: sources: ", sources)
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A = sources[0]
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print("Most Prominent Dialogue Language", A)
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if len(sources) == 1:
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B = 0
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C = 0
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elif non_dial_src_lang not in sources:
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B = 0
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C = sum(sorted_values[1:])
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else:
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if A == non_dial_src_lang:
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B = 0
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else:
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B = sorted_values[sources.index(non_dial_src_lang)]
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C = sum(sorted_values[1:]) - B
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return A, B, C
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# -> Detection of Different Lanugages and Scripts in Script
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def dial_each_word_lang1(non_dial_src_lang, dial):
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for word in dial.split():
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if language_detector(word) == non_dial_src_lang:
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return "True"
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return "False"
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# -> Detection of Different Lanugages and Scripts in Script
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def dial_each_word_lang2(non_dial_src_lang, A, dial):
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for word in dial.split():
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if (language_detector(word) != non_dial_src_lang) or (language_detector(word) != A):
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return "True"
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return "False"
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# -> Detection of words in lines with different languages
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def word_with_actionline_other_lang(scenes, A, non_dial_src_lang):
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dials_with_actionline_langs = 0
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dials_with_other_langs = 0
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sceneno = 0
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actionline_lang_output = "False"
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other_lang_output = "False"
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ignore_actionline_match = "False"
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if A == non_dial_src_lang:
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ignore_actionline_match = "True"
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for scene in tqdm(scenes[:]):
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sceneno += 1
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for i, line in enumerate(scene):
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if i == 0:
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continue
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if isinstance(line, str):
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continue
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else:
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[speaker] = line.keys()
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if speaker == 'Transition':
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continue
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dial_src_lang = language_detector(line[speaker][2])
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if actionline_lang_output == "False" or other_lang_output == "False":
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print(
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"Still Searching if Words of other langs are present or not...")
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if dial_src_lang == A:
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if actionline_lang_output != "True" and not ignore_actionline_match:
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output = dial_each_word_lang1(
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non_dial_src_lang, line[speaker][2])
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if output == "True":
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dials_with_actionline_langs += 1
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if dials_with_actionline_langs > 5:
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actionline_lang_output = "True"
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if other_lang_output != "True":
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output = dial_each_word_lang2(
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non_dial_src_lang, A, line[speaker][2])
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if output == "True":
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dials_with_other_langs += 1
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if dials_with_other_langs > 5:
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other_lang_output = "True"
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else:
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print("Found Presence of other Langs in Words")
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return actionline_lang_output, other_lang_output
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return actionline_lang_output, other_lang_output
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# -> Detection of Different Lanugages and Scripts in Script
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def getInputs(filename1):
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print("Detecting Languages and Scripts present in Script")
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text = textract.process(filename1, encoding="utf8", errors='ignore')
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filename = rf"{basePath}/conversion/translation/file_lines.txt"
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f = open(filename, 'wb')
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f.write(text)
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f.close()
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with open(rf"{basePath}/conversion/translation/file_lines.txt") as file:
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li = file.readlines()
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print("line", li)
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total_line = len(li)
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print("total_lines,", total_line)
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txt_file_200 = "".join((li)[:200])
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filename = rf"{basePath}/conversion/translation/file_lines_200.txt"
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f = open(filename, 'wb')
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f.write(txt_file_200)
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f.close()
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print("txt_file_200", txt_file_200)
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exit()
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refined, total_scenes = getRefined(filename1)
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sluglines, without_slug = getSlugAndNonSlug(refined)
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characters = getSpeakers(without_slug)
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scenes, actionline, parenthetical_lis, speakers, dialogues = getScenes(
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refined, total_scenes, characters)
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print("line 520:scenes: ", scenes)
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language_of_all_dialogues = []
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script_of_all_dialogues = []
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count = 0
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length = len(scenes)
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if (length > 5):
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length = 5
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scenes = scenes[:length]
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for scene in tqdm(scenes[:length]):
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for i, line in enumerate(scene):
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if i == 0:
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continue
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if isinstance(line, str):
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if count == 0:
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non_dial_src_lang = language_detector(line)
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non_dial_src_script = script_det(line)
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count += 1
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print("Non Dialogue/Actionline Language:", non_dial_src_lang)
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print("Non Dialogue/Actionline Script:", non_dial_src_script)
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else:
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[speaker] = line.keys()
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if speaker == 'Transition':
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continue
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dial_src_lang = language_detector(line[speaker][2])
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language_of_all_dialogues.append(dial_src_lang)
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script_of_all_dialogues.append(script_det(line[speaker][2]))
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# -> For Detecting presence of different languages in dialogues (whole sentences)
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A, B, C = A_B_C(language_of_all_dialogues, non_dial_src_lang)
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totaldials = len(language_of_all_dialogues)
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dial_src_script = mode(script_of_all_dialogues)
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dial_src_lang = A
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one_step_process = "Yes" if dial_src_script == code_script[A] else "Can_not_say"
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# word_lang_with_actionline = word_with_actionline(scenes, A, non_dial_src_lang)
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# word_lang_with_other = word_with_other(scenes, A, non_dial_src_lang)
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# -> For Detecting presence of different languages in dialogues (words)
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word_lang_with_actionline, word_lang_with_other = word_with_actionline_other_lang(
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scenes, A, non_dial_src_lang)
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print("A = {} B = {} C = {}".format(A, B, C))
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print("dial_language", A)
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print("dial_src_script", dial_src_script)
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if round(B / totaldials, 2) > 0.15:
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print("UI option3 - yes")
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UI_option3 = "Yes"
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else:
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print("UI option3 - no")
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UI_option3 = "No"
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if round(C / totaldials, 2) > 0.20:
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print("UI option4 - yes")
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UI_option4 = "Yes"
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else:
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print("UI option4 - no")
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UI_option4 = "No"
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if word_lang_with_actionline == "True":
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print("UI option5 - Yes")
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UI_option5 = "Yes"
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else:
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print("UI_option5 - NO")
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UI_option5 = "No"
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print("checking other lang", word_lang_with_other)
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if word_lang_with_other == "True":
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print("UI option6 - Yes")
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UI_option6 = "Yes"
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else:
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print("UI option6 - No")
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UI_option6 = "No"
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print("*******************------------Detection------------***********************")
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print(UI_option3, UI_option4, UI_option5, UI_option6, non_dial_src_script)
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return [non_dial_src_lang, dial_src_lang, dial_src_script, non_dial_src_script, UI_option3, UI_option4, UI_option5,
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UI_option6]
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