sanjeevdwivedi · April 20, 2018 02:59
diff --git a/final customvision b/final customvision
 from azure.cognitiveservices.vision.customvision.training import training_api
 from azure.cognitiveservices.vision.customvision.training.models import ImageUrlCreateEntry
 from azure.cognitiveservices.vision.customvision.prediction import prediction_endpoint
 from azure.cognitiveservices.vision.customvision.prediction.prediction_endpoint import models

 from flask import Flask, request, jsonify
 from datetime import datetime

 app = Flask(__name__)

 import os
 import sys
 import json, requests
 import time

 training_key = "5bd2f1fd171c427aa1009ff0304d5802"  # from settings pane on customvision.ai
 prediction_key = "c0bc732ba400470e936aef357942ad9c"

 project_name = "blighthack"
 tagname = ""

 dowhat = "nothing"

 # Check if the project with project_name exists and if not create ir
 project_id = "a5835760-4363-47ef-b052-bbaeb06cd54d"
 trainer = training_api.TrainingApi(training_key)

 def upload_single_image_from_url(image_url, tag_name):
    print('project id is: ' + project_id)
    alltags = trainer.get_tags(project_id)

    tag_id = None
    for i in range(0, len(alltags.tags)):
        if (alltags.tags[i].name == tag_name):
            tagExists = True
            tag_id = alltags.tags[i].id
            break

    if tag_id is not None:
        trainer.create_images_from_urls(project_id, [ImageUrlCreateEntry(image_url, [tag_id])])
    else:
        print('No tag by name: ' + tag_name + " found")

 upload_single_image_from_url('http://www.catster.com/wp-content/uploads/2017/11/A-Siamese-cat.jpg', 'boarded')

 # if training is requested
 def train_ml_model():
    iteration_id = trainer.train_project(project_id)
    while (iteration_id.status == "Training"):
        iteration_id = trainer.get_iteration(project_id, iteration_id.id)
        print("Training status: " + iteration_id.status)
        time.sleep(1)
    print('finished training the model')


 #train_ml_model()

 def predict(image_url):
    if(image_url is None):
        print('image url must be supplied')
        exit(0)
    iterations = trainer.get_iterations(project_id)
    # we are using the first iteration but you can select any iteration as necessary
    iteration_id = iterations[0].id

    host = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.1/Prediction/"
    path = project_id + "/url/?iterationId=" + iteration_id
    predictionUrl = host + path
    print('Prediction URL ' +  predictionUrl)

    headers = {"Prediction-key": prediction_key}
    # this is the URL to the image that you want to get the prediction on
    jsonObj = {"Url": image_url}

    response = requests.post(predictionUrl, headers=headers, json=jsonObj)
    responseJ = json.loads(response.text)
    print(json.dumps(responseJ, indent=4, sort_keys=True))
    predictions = responseJ['Predictions']

    results = []
    for prediction in predictions:
        print ("Tag: " + prediction['Tag'] + " Probability: " + str(prediction['Probability']))
        if prediction['Probability'] > 0.75:
            results.append(prediction['Tag'])

    #return results
    return responseJ

 #predict("https://www.cats.org.uk/uploads/images/featurebox_sidebar_kids/grief-and-loss.jpg")

 @app.route('/')
 def index():
    return "hello, I am your webserver"


 @app.route('/js')
 def js():
    return '''
        <html>
            <head>
                 <script type="text/javascript"
                          src="http://ajax.googleapis.com/ajax/libs/jquery/1.8.2/jquery.min.js"> 
                 </script>
                 <script type="text/javascript">
                    $(document).ready(function () {
                        alert("Your computer is awesome!");
                        console.log("computer is awesome");
                        $('#normalDiv').css('background-color', 'red');
                        $('#colorButton').click(toggleRedColor);
                        // add the code to show/hide text when button gets clicked
                    });

                    var isRedColor = true;
                    function toggleRedColor()
                    {
                        if(isRedColor == true)
                        {
                            $('#normalDiv').css('background-color', 'white');
                            isRedColor = false;
                        }
                        else
                        {
                            $('#normalDiv').css('background-color', 'red');
                            isRedColor = true;
                        }
                    }

                    var isHiddenText = false;
                    function toggleHide()
                    {
                        if(isHiddenText == false)
                        {
                            $('#paranormalDiv').slideUp();
                            isHiddenText = true;
                        }
                        else
                        {
                            $('#paranormalDiv').slideDown();
                            isHiddenText = false;
                        } 
                    }
                  </script>
            </head>
                <body>
                <h3> Welcome to my site </h3>
                    <p>
                        This is a paragraph
                    </p>
                    <div id='normalDiv'>
                        This is a normal div
                    </div>
                    <div id='paranormalDiv'>
                        This is a paranormal div
                    </div>
                    <div>
                        <input type='button' value='Turn Me Red and White' id='colorButton' />
                        <input type='button' value='Show and Hide' id='predictButton' />
                    </div>
            </body>
        </html>
        '''


 @app.route('/predictImageServer', methods=['POST'])
 def predictImageServer():
    print("entering send data")
    print(request)
    note = request.get_json()

    result = predict(note['url'])
    return jsonify(result)


 @app.route('/cs')
 def cs():
    return '''
        <html>
            <head>
                 <style>
                 pre {
                    white-space: pre-wrap;
                }
                 </style>
                 <script type="text/javascript"
                          src="http://ajax.googleapis.com/ajax/libs/jquery/1.8.2/jquery.min.js"> 
                 </script>
                 <script type="text/javascript">
                    $(document).ready(function () {
                        console.log("computer is awesome");
  
                        $('#predictButton').click(getPrediction);
                    });

                     function getPrediction()
                     {
                        $('#predictImage').attr('src', $('#urlTextBox').val());
                        
                        $.ajax({
                            type:"POST",
                            url: "/predictImageServer",
                            data:  JSON.stringify({url: $('#urlTextBox').val() }),
                            success: function (data) {
                                console.log("succeeded"); 
                                console.log(data);
                                $("#resultsDiv").text(JSON.stringify(data));
                                },
                            dataType:"json",
                            contentType: "application/json; charset=utf-8"
                            });
                     }
                  </script>
            </head>
                <body>
                <h3> Welcome to my Machine Learning Site </h3>
                    
                    <div>
                        <input type='text' value='Enter url here' id='urlTextBox' />
                        <input type='button' value='Predict an image' id='predictButton' />
                    </div>
                    <br/>
                    <h3> Results are shown below: </h3>
                    <image src='' id='predictImage'/>
                    <pre id='resultsDiv'>
                    </pre>
            </body>
        </html>
        '''

 if __name__ == '__main__':
    app.run(debug=True, host='0.0.0.0')
	from azure.cognitiveservices.vision.customvision.training import training_api
	from azure.cognitiveservices.vision.customvision.training.models import ImageUrlCreateEntry
	from azure.cognitiveservices.vision.customvision.prediction import prediction_endpoint
	from azure.cognitiveservices.vision.customvision.prediction.prediction_endpoint import models

	from flask import Flask, request, jsonify
	from datetime import datetime

	app = Flask(__name__)

	import os
	import sys
	import json, requests
	import time

	training_key = "5bd2f1fd171c427aa1009ff0304d5802" # from settings pane on customvision.ai
	prediction_key = "c0bc732ba400470e936aef357942ad9c"

	project_name = "blighthack"
	tagname = ""

	dowhat = "nothing"

	# Check if the project with project_name exists and if not create ir
	project_id = "a5835760-4363-47ef-b052-bbaeb06cd54d"
	trainer = training_api.TrainingApi(training_key)

	def upload_single_image_from_url(image_url, tag_name):
	print('project id is: ' + project_id)
	alltags = trainer.get_tags(project_id)

	tag_id = None
	for i in range(0, len(alltags.tags)):
	if (alltags.tags[i].name == tag_name):
	tagExists = True
	tag_id = alltags.tags[i].id
	break

	if tag_id is not None:
	trainer.create_images_from_urls(project_id, [ImageUrlCreateEntry(image_url, [tag_id])])
	else:
	print('No tag by name: ' + tag_name + " found")

	upload_single_image_from_url('http://www.catster.com/wp-content/uploads/2017/11/A-Siamese-cat.jpg', 'boarded')

	# if training is requested
	def train_ml_model():
	iteration_id = trainer.train_project(project_id)
	while (iteration_id.status == "Training"):
	iteration_id = trainer.get_iteration(project_id, iteration_id.id)
	print("Training status: " + iteration_id.status)
	time.sleep(1)
	print('finished training the model')


	#train_ml_model()

	def predict(image_url):
	if(image_url is None):
	print('image url must be supplied')
	exit(0)
	iterations = trainer.get_iterations(project_id)
	# we are using the first iteration but you can select any iteration as necessary
	iteration_id = iterations[0].id

	host = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.1/Prediction/"
	path = project_id + "/url/?iterationId=" + iteration_id
	predictionUrl = host + path
	print('Prediction URL ' + predictionUrl)

	headers = {"Prediction-key": prediction_key}
	# this is the URL to the image that you want to get the prediction on
	jsonObj = {"Url": image_url}

	response = requests.post(predictionUrl, headers=headers, json=jsonObj)
	responseJ = json.loads(response.text)
	print(json.dumps(responseJ, indent=4, sort_keys=True))
	predictions = responseJ['Predictions']

	results = []
	for prediction in predictions:
	print ("Tag: " + prediction['Tag'] + " Probability: " + str(prediction['Probability']))
	if prediction['Probability'] > 0.75:
	results.append(prediction['Tag'])

	#return results
	return responseJ

	#predict("https://www.cats.org.uk/uploads/images/featurebox_sidebar_kids/grief-and-loss.jpg")

	@app.route('/')
	def index():
	return "hello, I am your webserver"


	@app.route('/js')
	def js():
	return '''
	<html>
	<head>
	<script type="text/javascript"
	src="http://ajax.googleapis.com/ajax/libs/jquery/1.8.2/jquery.min.js">
	</script>
	<script type="text/javascript">
	$(document).ready(function () {
	alert("Your computer is awesome!");
	console.log("computer is awesome");
	$('#normalDiv').css('background-color', 'red');
	$('#colorButton').click(toggleRedColor);
	// add the code to show/hide text when button gets clicked
	});

	var isRedColor = true;
	function toggleRedColor()
	{
	if(isRedColor == true)
	{
	$('#normalDiv').css('background-color', 'white');
	isRedColor = false;
	}
	else
	{
	$('#normalDiv').css('background-color', 'red');
	isRedColor = true;
	}
	}

	var isHiddenText = false;
	function toggleHide()
	{
	if(isHiddenText == false)
	{
	$('#paranormalDiv').slideUp();
	isHiddenText = true;
	}
	else
	{
	$('#paranormalDiv').slideDown();
	isHiddenText = false;
	}
	}
	</script>
	</head>
	<body>
	<h3> Welcome to my site </h3>
	<p>
	This is a paragraph
	</p>
	<div id='normalDiv'>
	This is a normal div
	</div>
	<div id='paranormalDiv'>
	This is a paranormal div
	</div>
	<div>
	<input type='button' value='Turn Me Red and White' id='colorButton' />
	<input type='button' value='Show and Hide' id='predictButton' />
	</div>
	</body>
	</html>
	'''


	@app.route('/predictImageServer', methods=['POST'])
	def predictImageServer():
	print("entering send data")
	print(request)
	note = request.get_json()

	result = predict(note['url'])
	return jsonify(result)


	@app.route('/cs')
	def cs():
	return '''
	<html>
	<head>
	<style>
	pre {
	white-space: pre-wrap;
	}
	</style>
	<script type="text/javascript"
	src="http://ajax.googleapis.com/ajax/libs/jquery/1.8.2/jquery.min.js">
	</script>
	<script type="text/javascript">
	$(document).ready(function () {
	console.log("computer is awesome");

	$('#predictButton').click(getPrediction);
	});

	function getPrediction()
	{
	$('#predictImage').attr('src', $('#urlTextBox').val());

	$.ajax({
	type:"POST",
	url: "/predictImageServer",
	data: JSON.stringify({url: $('#urlTextBox').val() }),
	success: function (data) {
	console.log("succeeded");
	console.log(data);
	$("#resultsDiv").text(JSON.stringify(data));
	},
	dataType:"json",
	contentType: "application/json; charset=utf-8"
	});
	}
	</script>
	</head>
	<body>
	<h3> Welcome to my Machine Learning Site </h3>

	<div>
	<input type='text' value='Enter url here' id='urlTextBox' />
	<input type='button' value='Predict an image' id='predictButton' />
	</div>
	<br/>
	<h3> Results are shown below: </h3>
	<image src='' id='predictImage'/>
	<pre id='resultsDiv'>
	</pre>
	</body>
	</html>
	'''

	if __name__ == '__main__':
	app.run(debug=True, host='0.0.0.0')