Package: data2Insights
Python PackageData2Insights of python packages can be used to integrate the data2insights services with your applications to enhance services with the data2insighs services. You can use this package easily in the popular framworks and libraries(EX:Python,Flask). Form the below installation command you can download the package.Library Installationpip3 install data2insightsPython Text Analytics ModelsThe Text analysis models can take a text as the input and gives the appropriate predicted results for that model.The input text should contain only alphabets (or) combination of both alphabets and special characters (or) combination of both alphabets and digits,then user gets the predicted result for that model .Emotion ModelThe Emotion model of data2insights will take text as the input and returns the type of emotion of the given text as the response object.Method Name :classifiers.emotion(data='provide input text');  # for single text
batchclassifiers.emotion(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.emotion(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Emotion",
"classifications": {
"Prediction_accuracy": "36.04",
"emotion": "Happy",
"given_text": "hi"
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "829",
"query_limit_request": 1,
"status_code": 200
}
Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.emotion(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/emotion/data371.csv",
"msg": "file_processing_completed",
"status_code": 200
}Sentiment ModelThe Sentiment model of data2insights will take text as the input and return the type of sentiment of the given text as the response object.Method Name :classifiers.sentiment(data='provide input text');  # for single text
batchclassifiers.sentiment(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.sentiment(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Sentiment",
"classifications": {
"Prediction_accuracy": "99.59",
"given_text": "hi",
"sentiment": "Neutral"
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "830",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.sentiment(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/sentiment/data372.csv",
"msg": "file_processing_completed",
"status_code": 200}Topic ModelThe Topic model of data2insights will take text as the input and return the type of topic of the given text as the response object.Method Name :classifiers.topic(data='provide input text');  # for single text
batchclassifiers.topic(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.topic(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Topic",
"classifications": {
"Prediction_accuracy": "38.10",
"given_text": "hi",
"topic": "beauty_style"
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "815",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.topic(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/topic/data385.csv",
"msg": "file_processing_completed",
"status_code": 200}Spam ModelThe Spam model of data2insights will take text as the input and return whether the text is spam or not.Method Name :classifiers.spam(data='provide input text');  # for single text
batchclassifiers.spam(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.spam(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Spam",
"classifications": {
"Prediction_accuracy": "80.28",
"given_text": "hi",
"spam": "NotSpam"
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "820",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.spam(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/spam/data386.csv",
"msg": "file_processing_completed",
"status_code": 200}Age ModelThe Age model of data2insights will predict the age of, who wrote the given input text.Method Name :classifiers.age(data='provide input text');  # for single text
batchclassifiers.age(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.age(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Age",
"classifications": {
"Prediction_accuracy": "99.08",
"age": "18_24",
"given_text": "hi"
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "828",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.age(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/age/data388.csv",
"msg": "file_processing_completed",
"status_code": 200}Gender ModelThe Gender model of data2insights will predict the gender of the, who wrote the given input text either Male or Female.Method Name :classifiers.gender(data='provide input text');  # for single text
batchclassifiers.gender(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.gender(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Gender",
"classifications": {
"Prediction_accuracy": "99.87",
"gender": "Female",
"given_text": "hi"
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "817",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.gender(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/gender/data387.csv",
"msg": "file_processing_completed",
"status_code": 200}TweetSentiment ModelTwitter sentiment analysis identifies the opinion of tweet text which has only 280 characters of text as Positive,Neutral,Negative.Method Name :classifiers.tweetsentiment(data='provide input text');  # for single text
batchclassifiers.tweetsentiment(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.tweetsentiment(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Tweet_sentiment",
"classifications": {
"Prediction_accuracy": "55.24",
"given_text": "hi",
"tweetsentiment": "Positive"
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "819",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.tweetsentiment(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/tweetsentiment/data389.csv",
"msg": "file_processing_completed",
"status_code": 200}Entity ModelThe Entity model of data2insights will predict the entities in the given input text(Location,Person, Location, Organisation etc..).Method Name :classifiers.entity(data='provide input text');  # for single text
batchclassifiers.entity(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.entity(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Extraction_id": "Entity",
"content_type": "application-json",
"extractions": {
"entity": [],
"given_text": "hi"
},
"query_limit": "1000",
"query_limit_remaining": "827",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.entity(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/entity/data396.csv",
"msg": "file_processing_completed",
"status_code": 200}TweetEntity ModelThe Twitter Entity Extraction service allows us to identify the entions,Hashtags,Symbols ,Url’s and User_profile_url’s from given twitter tweets.Method Name :classifiers.tweetentity(data='provide input text');  # for single text
batchclassifiers.tweetentity(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.tweetentity(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Extraction_id": "Tweet_entity",
"content_type": "application-json",
"extractions": {
"given_text": "hi",
"tweetentity": {
"Entities": [],
"Hashtags": [],
"symbols": [],
"urls": [],
"user_profiles_url": [],
"users": []
}
},
"query_limit": "1000",
"query_limit_remaining": "818",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.tweetentity(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/tweetentity/data420.csv",
"msg": "file_processing_completed",
"status_code": 200}Keyword ModelThe Keyword model of data2insights will take text as the input and return keywords in the given text.Method Name :classifiers.keyword(data='provide input text');  # for single text
batchclassifiers.keyword(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.keyword(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Extraction_id": "Keyword",
"content_type": "application-json",
"extractions": {
"given_text": "hi",
"keywords": []
},
"query_limit": "1000",
"query_limit_remaining": "826",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.keyword(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/keyword/data397.csv",
"msg": "file_processing_completed",
"status_code": 200}UrlExtraction ModelThe Url Extraction service allows us to identity the full content,title,html page,top image,authors,keyword,summary and publication date from the given url.Method Name :text->classifiers.urlextraction(data='provide input text');  # for single text
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.urlextraction(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Extraction_id": "Url_extraction",
"content_type": "application-json",
"extractions": {
"Response": {
"ALL_IMAGES_URLS": [
"https://i.stack.imgur.com/ziXaw.jpg?s=32&g=1"
],
"AUTHORS": [],
"FULL CONTENT": "I am using requests to get the image from remote URL. Since the images will always be 16x16, I want to convert them to base64 , so that I can embed them later to use in HTML img tag.import requests import base64 response = requests.get(url).content print(response) b = base64.b64encode(response) src = "data:image/png;base64," + bThe output for response is:response = b'GIF89a\x80\x00\x80\x00\xc4\x1f\x00\xff\xff\xff\x00\x00\x00\xff\x00\x00\xff\x88\x88"""\xffff...The HTML part is:But the image is not displayed.",
"HTML_PAGE": "I am usingrequeststo get the image from remote URL. Since the images will always be 16x16, I want to convert them tobase64, so that I can embed them later to use in HTMLimgtag.import requests
import base64
response = requests.get(url).content
print(response)
b = base64.b64encode(response)
src = "data:image/png;base64," + bThe output forresponseis:response = b'GIF89a\x80\x00\x80\x00\xc4\x1f\x00\xff\xff\xff\x00\x00\x00\xff\x00\x00\xff\x88\x88"""\xffff\...The HTML part is:<img src="{{src}}"/>But the image is not displayed.How can I properly base-64 encode theresponse?",
      "KEYWORDS": [
      "url",
      "base64",
      "image",
      "tagimport",
      "src",
      "requests",
      "using",
      "response",
      "python",
      "html",
      "srcsrcbut"
    ],
      "PUBLICATION DATE": null,
      "SUMMARY": "I am using requests to get the image from remote URL.
Since the images will always be 16x16, I want to convert them to base64 , so that I can embed them later to use in HTML img tag.
import requests import base64 response = requests.get(url).content print(response) b = base64.b64encode(response) src = "data:image/png;base64," + bThe output for response is:response = b'GIF89a\x80\x00\x80\x00\xc4\x1f\x00\xff\xff\xff\x00\x00\x00\xff\x00\x00\xff\x88\x88"""\xffff\...
The HTML part is:But the image is not displayed.",
      "TITLE": "Python requests base64 image",
      "TOP_IMAGE": "https://cdn.sstatic.net/Sites/stackoverflow/Img/apple-touch-icon@2.png?v=73d79a89bded"
      },
     "given_url": "https://stackoverflow.com/questions/30280495/python-requests-base64-image"
     },
    "query_limit": "1000",
    "query_limit_remaining": "825",
    "query_limit_request": 1,
    "status_code": 200}Personalitytraits ModelThe Personality Traits model of data2insights will take text as the input and return the Personality Traits of the given text as the response object.Method Name :classifiers.personalitytraits(data='provide input text');  # for single text
batchclassifiers.personalitytraits(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.personalitytraits(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
Classifier_id: 'Topic',
classifications: {
Prediction_accuracy: '85.09',
given_text: 'Welcome to d2i',
topic: 'recreation'
},
content_type: 'application-json',
query_limit: '5000',
query_limit_remaining: '4935',
query_limit_request: 1,
status_code: 200
}
Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.personalitytraits(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/102/personalityTraits/Sample-Spreadsheet-10-rows221.xls",
"msg": "file_processing_completed",
"status_code": 200
}Readability ModelThe Readability model of data2insights will take text as the input and return the type of some metrics of the given text as the response object.Method Name :classifiers.readability(data='provide input text');  # for single text
batchclassifiers.readability(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.readability(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Metrics": {
"document_readability": {
"Automated_Readability_Index": -11.6,
"Coleman_liau_index": -33.81,
"Dalechal": 0.05,
"Flesch_Kindrade_Grade": -3.5,
"Flesch_Reading_Score": 121.22,
"Gunning_Fog": 0.4,
"Linsear_Write": -0.5,
"Smog_index": 0.0
},
"given_text": "hi"
},
"Metrix_id": "Document_readability",
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "824",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.readability(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/readability/data421.csv",
"msg": "file_processing_completed",
"status_code": 200}Similarity ModelThe Similarity model of data2insights will find the similarity between two texts.Method Name :text->classifiers.similarity(data1='provide text',data2='provide text');  # for single text
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.similarity(data1='provide text',data2='provide text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Metrics": {
"Cosine_similarity": 0.0,
"Jaccard_similarity": 0.0,
"given_text1": "hi",
"given_text2": "hello"
},
"Metrix_id": "Document_similarity",
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "823",
"query_limit_request": 1,
"status_code": 200}QandA ModelThe Q&A model of data2insights will find the answer for the given question from the given paragraph.Method Name :classifiers.QA(question='provide question', paragraph='provide paragraph');  # for single text
batchclassifiers.QA(column1='provide question column number',column2='provide paragraph column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.QA(question='provide question', paragraph='provide paragraph')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
content_type: 'application-json',
'q&a': {
Answer: 'welcome to data2insights',
given_paragraph: 'welcome to data2insights',
given_question: 'welcome to d2i?'
},
query_limit: '5000',
query_limit_remaining: '4923',
query_limit_request: 1,
status_code: 200
}
Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.QA(column1='provide question column number',column2='provide paragraph column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/102/QandA/Sample-Spreadsheet-10-rows221.xls",
"msg": "file_processing_completed",
"status_code": 200
}HempTopic ModelThe HempTopic model of data2insights will helps you in identifying topics.Method Name :classifiers.hemptopic(data='provide input text');  # for single text
batchclassifiers.hemptopic(column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.hemptopic(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classification_id": "Hemptopic",
"classifications": {
"Prediction_accuracy": "83.65",
"given_text": "hi",
"hemptopic": "Beauty"
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "814",
"query_limit_request": 1,
"status_code": 200}Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.hemptopic(column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/hemptopic/data502.csv",
"msg": "file_processing_completed",
"status_code": 200
}BertEntity ModelThe BertEntity model of data2insights will helps you to identify the entities.Method Name :classifiers.bertentity(data='provide input text');  # for single text
batchclassifiers.bertentity((column='provide column number',files={'file': open('provide full path of file', 'rb')}); # for batch process
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.bertentity(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Extraction_id": "Bertentity",
"content_type": "application-json",
"extractions": {
"Bertentity": [
{
"bertentity": "O",
"text": "hi"
}
],
"given_text": "hi"
},
"query_limit": "1000",
"query_limit_remaining": "813",
"query_limit_request": 1,
"status_code": 200
}
Example for batch text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.batchclassifiers.bertentity((column='provide column number',files={'file': open('provide full path of file', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Processed_file location": "./outputfiles/3/bertentity/data501.csv",
"msg": "file_processing_completed",
"status_code": 200
}Summarization ModelThe Summarization model of data2insights will helps you summarize the given text.Method Name :text->classifiers.summarization(data='provide input text');  # for single text
Example for single text :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.classifiers.summarization(data='provide input text')Output:#This is exactly the parsed JSON that the Data2Insights API returns!Python Vision Analytics ModelsThe Vision analysis models can take a image as the input and gives the appropriate predicted results for that model.The input image should contain .png (or) .jpeg formats only and it should be either local file or remote file url.Logo ModelThe Logo model of data2insights will predict the 27 types of logos from the given input image.Method Name :visionclassifiers.logo(data='provide image url');visionclassifiers.logoupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.logo(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Logo",
"classifications": {
"Logos": []
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "812",
"query_limit_request": 1,
"status_code": 200}Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.logoupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Logo",
"classifications": {
"Logos": []
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "774",
"query_limit_request": 1,
"status_code": 200
}Bird ModelThe Bird model of data2insights will predict the 27 types of birds from the given input image.Method Name :visionclassifiers.bird(data='provide image url');visionclassifiers.birdupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.bird(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "Bird",
"classifications": {
"Birds": [
{
"Bird": "toucan_bird",
"Coordinates": {
"Bottom": 771.510648727417,
"Left": 53.76867055892944,
"Right": 1191.6043281555176,
"Top": 14.702987670898438
},
"Prediction_accuracy": 99,
"bird": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "794",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.birdupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Bird",
"classifications": {
"Birds": [
{
"Bird": "parrot_bird",
"Coordinates": {
"Bottom": 523.5589575767517,
"Left": 60.50408989191055,
"Right": 711.0763740539551,
"Top": 58.13420504331589
},
"Prediction_accuracy": 92,
"bird": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "772",
"query_limit_request": 1,
"status_code": 200
}Transport ModelThe Transport model of data2insights will predict the vehicle types from the given input image.Method Name :visionclassifiers.transport(data='provide image url');visionclassifiers.transportupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.transport(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Transport",
"classifications": {
"Transports": [
{
"Coordinates": {
"Bottom": 800.0,
"Left": 46.82081937789917,
"Right": 1174.506425857544,
"Top": 8.72507095336914
},
"Prediction_accuracy": 76,
"Transport": "auto",
"transport": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "785",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.transportupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Transport",
"classifications": {
"Transports": [{
"Coordinates": {
"Bottom": 502.32422828674316,
"Left": 41.04209750890732,
"Right": 651.0549342632294,
"Top": 30.10187178850174
},
"Prediction_accuracy": 31,
"Transport": "aeroplane",
"transport": 1
}]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "771",
"query_limit_request": 1,
"status_code": 200}Plant ModelThe Plant model of data2insights will predict the plant types from the given input image.Method Name :visionclassifiers.plant(data='provide image url');visionclassifiers.plantupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.plant(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "Plant",
"classifications": {
"Plants": [
{
"Coordinates": {
"Bottom": 754.0493965148926,
"Left": 9.73820686340332,
"Right": 1200.0,
"Top": 27.520751953125
},
"Plant": "plants_indoor",
"Prediction_accuracy": 58,
"plant": 1
},
{
"Coordinates": {
"Bottom": 800.0,
"Left": 54.79602813720703,
"Right": 1131.5191984176636,
"Top": 10.229825973510742
},
"Plant": "plants_outdoor",
"Prediction_accuracy": 53,
"plant": 2
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "803",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.plantupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Plant",
"classifications": {
"Plants": [
{
"Coordinates": {
"Bottom": 490.9296751022339,
"Left": 0.0,
"Right": 730.0,
"Top": 24.103980362415314
},
"Plant": "plants_indoor",
"Prediction_accuracy": 54,
"plant": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "769",
"query_limit_request": 1,
"status_code": 200}Age ModelThe Age model of data2insights will predict the age of the persons from the given input image.Method Name :visionclassifiers.age(data='provide image url');visionclassifiers.ageupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.age(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Age",
"classifications": {
"Faces": [
{
"Age": "31-55",
"Coordinates": {
"Bottom": 287.21981048583984,
"Left": 505.4616093635559,
"Right": 690.896487236023,
"Top": 18.590307235717773
},
"Face": 1,
"Predicted_accuracy": 51
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "798",
"query_limit_request": 1,
"status_code": 200}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.ageupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "Age",
"classifications": {
"Faces": []
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "761",
"query_limit_request": 1,
"status_code": 200}Gender ModelThe Gender model of data2insights will predict the gender of the persons from the given input image.Method Name :visionclassifiers.gender(data='provide image url');visionclassifiers.genderupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.gender(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Gender",
"classifications": {
"Faces": [
{
"Coordinates": {
"Bottom": 295.8600044250488,
"Left": 507.1301221847534,
"Right": 694.7623014450073,
"Top": 10.44924259185791
},
"Face": 1,
"Gender": "Male",
"Predicted_accuracy": 99
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "777",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.genderupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Gender",
"classifications": {
"Faces": []
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "763",
"query_limit_request": 1,
"status_code": 200}Emotion ModelThe Emotion model of data2insights will predict the emotion of the person from the given input image.Method Name :visionclassifiers.emotion(data='provide image url');visionclassifiers.emotionupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.emotion(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "Emotion",
"classifications": {
"Faces": [
{
"Coordinates": {
"Bottom": 283.68217945098877,
"Left": 519.590413570404,
"Right": 677.3368835449219,
"Top": 43.988871574401855
},
"Emotion": "Neutral",
"Face": 1,
"Predicted_accuracy": 54
},
{
"Coordinates": {
"Bottom": 282.6207637786865,
"Left": 510.5981111526489,
"Right": 689.1172885894775,
"Top": 29.67963218688965
},
"Emotion": "Surprise",
"Face": 2,
"Predicted_accuracy": 37
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "792",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.emotionupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Emotion",
"classifications": {
"Faces": []
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "762",
"query_limit_request": 1,
"status_code": 200}Color ModelThe Color model of data2insights will predict the different color from the given input image.Method Name :visionclassifiers.color(data='provide image url');visionclassifiers.colorupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.color(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Color",
"classifications": {
"Faces": [
{
"Color": "white_people",
"Coordinates": {
"Bottom": 791.8387413024902,
"Left": 224.97146129608154,
"Right": 987.045407295227,
"Top": 47.0322847366333
},
"Face": 1,
"Predicted_accuracy": 99
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "799",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.colorupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Color",
"classifications": {
"Faces": [
{
"Color": "white_people",
"Coordinates": {
"Bottom": 513.8462805747986,
"Left": 38.191078901290894,
"Right": 642.4347186088562,
"Top": 38.06664854288101
},
"Face": 1,
"Predicted_accuracy": 96
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "760",
"query_limit_request": 1,
"status_code": 200}Scene ModelThe Scene model of data2insights will predict the different scenes from the given input image.Method Name :visionclassifiers.scene(data='provide image url');visionclassifiers.sceneupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.scene(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "Scene",
"classifications": {
"Scenes": [
{
"Coordinates": {
"Bottom": 795.6767559051514,
"Left": 211.76365613937378,
"Right": 954.124116897583,
"Top": 36.2668514251709
},
"Prediction_accuracy": 48,
"Scene": "Office_building",
"scene": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "790",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.sceneupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Scene",
"classifications": {
"Scenes": [
{
"Coordinates": {
"Bottom": 795.6767559051514,
"Left": 211.76365613937378,
"Right": 954.124116897583,
"Top": 36.2668514251709
},
"Prediction_accuracy": 48,
"Scene": "Office_building",
"scene": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "790",
"query_limit_request": 1,
"status_code": 200}Weather ModelThe Weather model of data2insights will predict the weather in the given input image.Method Name :visionclassifiers.weather(data='provide image url');visionclassifiers.weatherupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.weather(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Weather",
"classifications": {
"Scenes": [
{
"Coordinates": {
"Bottom": 786.3454818725586,
"Left": 22.405779361724854,
"Right": 1196.6458797454834,
"Top": 62.87107467651367
},
"Prediction_accuracy": 90,
"Weather": "weather_cloudy",
"scene": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "789",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.weatherupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Weather",
"classifications": {
"Scenes": [{
"Coordinates": {
"Bottom": 521.9473385810852,
"Left": 9.529821276664734,
"Right": 723.5642737150192,
"Top": 29.81929510831833
},
"Prediction_accuracy": 99,
"Weather": "weather_snowy",
"scene": 1
}]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "764",
"query_limit_request": 1,
"status_code": 200}Violence ModelThe Violence model of data2insights will predict the violence from the given input image.Method Name :visionclassifiers.violence(data='provide image url');visionclassifiers.violenceupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.violence(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "Violence",
"classifications": {
"Scenes": [
{
"Coordinates": {
"Bottom": 797.3269462585449,
"Left": 111.29786968231201,
"Right": 1200.0,
"Top": 0.0
},
"Prediction_accuracy": 99,
"Violence": "war",
"scene": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "787",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.violenceupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Violence",
"classifications": {
"Scenes": [{
"Coordinates": {
"Bottom": 527.7309834957123,
"Left": 62.09136366844177,
"Right": 730.0,
"Top": 0.0
},
"Prediction_accuracy": 99,
"Violence": "war",
"scene": 1
}, {
"Coordinates": {
"Bottom": 527.7526861429214,
"Left": 13.07406336069107,
"Right": 720.9626841545105,
"Top": 16.71631395816803
},
"Prediction_accuracy": 60,
"Violence": "violence",
"scene": 2
}]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "766",
"query_limit_request": 1,
"status_code": 200}TLO ModelThe Tlo model of data2insights will predict the trees,laks, and oceans from the given input image.Method Name :visionclassifiers.tlo(data='provide image url');visionclassifiers.tloupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.tlo(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "Tlo",
"classifications": {
"Scenes": [
{
"Coordinates": {
"Bottom": 784.9786281585693,
"Left": 15.252542495727539,
"Right": 1200.0,
"Top": 68.20473670959473
},
"Prediction_accuracy": 99,
"Tlo": "lake",
"scene": 1
}
]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "788",
"query_limit_request": 1,
"status_code": 200
}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.tloupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{
"Classifier_id": "Tlo",
"classifications": {
"Scenes": [{
"Coordinates": {
"Bottom": 510.66392064094543,
"Left": 18.766419291496277,
"Right": 719.1625744104385,
"Top": 101.74509018659592
},
"Prediction_accuracy": 99,
"Tlo": "lake",
"scene": 1
}]
},
"content_type": "application-json",
"query_limit": "1000",
"query_limit_remaining": "765",
"query_limit_request": 1,
"status_code": 200}General Objects ModelThe Object model of data2insights will predict the different types of general objects from the given input image.It predicts 545 types of objects.Method Name :visionclassifiers.generalobject(data='provide image url');visionclassifiers.generalobjectupload(files={'file': open('provide image full path', 'rb')});
Example for image URL :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.generalobject(data='provide image url')Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "General_Object",

"classifications": {

	"GeneralObjects": [

		{

			"Class": "Clothing",

			"Coordinates": {

				"Bottom": 781.9650173187256,

				"Left": 326.60393714904785,

				"Right": 913.2122039794922,

				"Top": 258.1010580062866

			},

			"Object": 1,

			"Score": 73

		},

		{

			"Class": "Face",

			"Coordinates": {

				"Bottom": 274.97315406799316,

				"Left": 508.36490392684937,

				"Right": 689.9345397949219,

				"Top": 28.40385138988495

			},

			"Object": 2,

			"Score": 54

		},

		{

			"Class": "Person",

			"Coordinates": {

				"Bottom": 795.4741477966309,

				"Left": 309.1881036758423,

				"Right": 943.9865827560425,

				"Top": 30.157431960105896

			},

			"Object": 3,

			"Score": 42

		},

		{

			"Class": "Man",

			"Coordinates": {

				"Bottom": 794.6691036224365,

				"Left": 319.6103096008301,

				"Right": 909.6429347991943,

				"Top": 29.600465297698975

			},

			"Object": 4,

			"Score": 40

		}

	]

},

"content_type": "application-json",

"status_code": 200,

"query_limit": "10000",

"query_limit_remaining": "9287",

"query_limit_request": 1}
Example for upload local image :from data2Insights import data2insightsUse the API key,account Id and email Id  from your account,credentials = data2insights('provide accountid','provide apikey','provide userid')Pass the input as parameter to the methodcredentials.visionclassifiers.generalobjectupload(files={'file': open('provide image full path', 'rb')})Output:#This is exactly the parsed JSON that the Data2Insights API returns!
{"Classifier_id": "General_Object",

"classifications": {

	"GeneralObjects": [

		{

			"Class": "Clothing",

			"Coordinates": {

				"Bottom": 781.9650173187256,

				"Left": 326.60393714904785,

				"Right": 913.2122039794922,

				"Top": 258.1010580062866

			},

			"Object": 1,

			"Score": 73

		},

		{

			"Class": "Face",

			"Coordinates": {

				"Bottom": 274.97315406799316,

				"Left": 508.36490392684937,

				"Right": 689.9345397949219,

				"Top": 28.40385138988495

			},

			"Object": 2,

			"Score": 54

		},

		{

			"Class": "Person",

			"Coordinates": {

				"Bottom": 795.4741477966309,

				"Left": 309.1881036758423,

				"Right": 943.9865827560425,

				"Top": 30.157431960105896

			},

			"Object": 3,

			"Score": 42

		},

		{

			"Class": "Man",

			"Coordinates": {

				"Bottom": 794.6691036224365,

				"Left": 319.6103096008301,

				"Right": 909.6429347991943,

				"Top": 29.600465297698975

			},

			"Object": 4,

			"Score": 40

		}

	]

},

"content_type": "application-json",

"status_code": 200,

"query_limit": "10000",

"query_limit_remaining": "9287",

"query_limit_request": 1}