cognitive thinking

Get Image Metadata (Part 3)

Anthony Marsiglia — Thu, 29 Mar 2018 20:34:25 GMT

In Continuation of the Get Image Metadata (Part 2), In this post we will build and compile to code we wrote and than we will Test it with a few Images. In the Error List verify that all errors are gone before Building your Code If you don't errors continue to Build and Compile the Code, if for some reason you have errors or when you Try and Build the code an error pops up, Locate the error and step through the blog posting to see where the issue exist. Click on Build | Rebuild Solution and if the Solution builds Successfully you should see “Rebuild All: 1 Succeeded” Now at the Top of Visual Studios Click on the Green Start Now your User Interface should pop up In the UI click on the 3 dots in the little box … Brows for an image and click on Open after you have the image selected you wish to Analyze. Click on the Analyze button Review the Results Repeat test with several images, Try analyzing pictures of Famous Places and Buildings, or even Celebrities I hope you enjoy this Activity

Get Image Metadata (Part 2)

Anthony Marsiglia — Thu, 29 Mar 2018 01:16:09 GMT

Continuing from the “Get Image Metadata (Part 1)” blog posting, we should now have the first part of the code Written which will send the captured image the Microsoft Cognitive Services Vision API. In this next section we will build the Image collection piece with a user friendly UI as well as create a new class. 1st lets create the additional class In the Solution Explorer Right Click on the Project Name in this example its “GetImageMetaData” and select Add Class In the Add new class window , Name the class “AnalysisResults” Click on Add Now you should see a new class added to your code that has the following code within it… In between the braces of

class AnalysisResults { }

Change class AnalysisResults to public class AnalysisResults Than add the following 2 lines of code in-between the 2 Braces of the public class AnalysisResults

public dynamic JsonObj; public string jsonStr;

The code in the class should now look like …

I know its not much to it but lets just continue shall we. now we could create the text boxes manually and define actions to the text boxes for the User Interface , but that will be for another blog. To speed things up we will just add the needed code to set up the interface. In the Solution Explorer Double click on “Form1.Designer.cs” which is under the “Form1.cs” After the brace of

private void InitializeComponent() {

NOTE : remove the existing code after the brace and replace with the following code.

this.label1 = new System.Windows.Forms.Label(); this.txtPicFilename = new System.Windows.Forms.TextBox(); this.cmdBrowse = new System.Windows.Forms.Button(); this.cmdAnalyze = new System.Windows.Forms.Button(); this.label2 = new System.Windows.Forms.Label(); this.txtResults = new System.Windows.Forms.TextBox(); this.txtDescription = new System.Windows.Forms.TextBox(); this.SuspendLayout(); // // label1 // this.label1.AutoSize = true; this.label1.Location = new System.Drawing.Point(23, 23); this.label1.Name = "label1"; this.label1.Size = new System.Drawing.Size(157, 25); this.label1.TabIndex = 0; this.label1.Text = "Picture Filename"; // // txtPicFilename // this.txtPicFilename.Anchor = ((System.Windows.Forms.AnchorStyles)(((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Left) | System.Windows.Forms.AnchorStyles.Right))); this.txtPicFilename.Location = new System.Drawing.Point(28, 52); this.txtPicFilename.Name = "txtPicFilename"; this.txtPicFilename.Size = new System.Drawing.Size(818, 29); this.txtPicFilename.TabIndex = 1; // // cmdBrowse // this.cmdBrowse.Anchor = ((System.Windows.Forms.AnchorStyles)((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Right))); this.cmdBrowse.Location = new System.Drawing.Point(863, 45); this.cmdBrowse.Name = "cmdBrowse"; this.cmdBrowse.Size = new System.Drawing.Size(65, 45); this.cmdBrowse.TabIndex = 2; this.cmdBrowse.Text = "..."; this.cmdBrowse.UseVisualStyleBackColor = true; this.cmdBrowse.Click += new System.EventHandler(this.cmdBrowse_Click); // // cmdAnalyze // this.cmdAnalyze.Anchor = ((System.Windows.Forms.AnchorStyles)((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Right))); this.cmdAnalyze.Location = new System.Drawing.Point(946, 45); this.cmdAnalyze.Name = "cmdAnalyze"; this.cmdAnalyze.Size = new System.Drawing.Size(185, 45); this.cmdAnalyze.TabIndex = 4; this.cmdAnalyze.Text = "Analyze"; this.cmdAnalyze.UseVisualStyleBackColor = true; this.cmdAnalyze.Click += new System.EventHandler(this.cmdAnalyze_Click); // // label2 // this.label2.AutoSize = true; this.label2.Location = new System.Drawing.Point(23, 115); this.label2.Name = "label2"; this.label2.Size = new System.Drawing.Size(76, 25); this.label2.TabIndex = 5; this.label2.Text = "Results"; // // txtResults // this.txtResults.Anchor = ((System.Windows.Forms.AnchorStyles)((((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Bottom) | System.Windows.Forms.AnchorStyles.Left) | System.Windows.Forms.AnchorStyles.Right))); this.txtResults.Location = new System.Drawing.Point(28, 183); this.txtResults.Multiline = true; this.txtResults.Name = "txtResults"; this.txtResults.ScrollBars = System.Windows.Forms.ScrollBars.Vertical; this.txtResults.Size = new System.Drawing.Size(1103, 520); this.txtResults.TabIndex = 6; // // txtDescription // this.txtDescription.Anchor = ((System.Windows.Forms.AnchorStyles)(((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Left) | System.Windows.Forms.AnchorStyles.Right))); this.txtDescription.Location = new System.Drawing.Point(28, 143); this.txtDescription.Name = "txtDescription"; this.txtDescription.ReadOnly = true; this.txtDescription.Size = new System.Drawing.Size(1095, 29); this.txtDescription.TabIndex = 7; // // Form1 // this.AutoScaleDimensions = new System.Drawing.SizeF(11F, 24F); this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font; this.ClientSize = new System.Drawing.Size(1161, 735); this.Controls.Add(this.txtDescription); this.Controls.Add(this.txtResults); this.Controls.Add(this.label2); this.Controls.Add(this.cmdAnalyze); this.Controls.Add(this.cmdBrowse); this.Controls.Add(this.txtPicFilename); this.Controls.Add(this.label1); this.Name = "Form1"; this.Text = "getMetadata v1.0"; this.ResumeLayout(false); this.PerformLayout();

That complete block of code should now look like … after the #endregion

private System.Windows.Forms.Label label1; private System.Windows.Forms.TextBox txtPicFilename; private System.Windows.Forms.Button cmdBrowse; private System.Windows.Forms.Button cmdAnalyze; private System.Windows.Forms.Label label2; private System.Windows.Forms.TextBox txtResults; private System.Windows.Forms.TextBox txtDescription;

That should look like.. so the final code should look like …

namespace GetImageMetaData { partial class Form1 { ///
/// Required designer variable. ///
private System.ComponentModel.IContainer components = null; ///
/// Clean up any resources being used. ///
/// true if managed resources should be disposed; otherwise, false. protected override void Dispose(bool disposing) { if (disposing && (components != null)) { components.Dispose(); } base.Dispose(disposing); } #region Windows Form Designer generated code ///
/// Required method for Designer support - do not modify /// the contents of this method with the code editor. ///
private void InitializeComponent() { this.label1 = new System.Windows.Forms.Label(); this.txtPicFilename = new System.Windows.Forms.TextBox(); this.cmdBrowse = new System.Windows.Forms.Button(); this.cmdAnalyze = new System.Windows.Forms.Button(); this.label2 = new System.Windows.Forms.Label(); this.txtResults = new System.Windows.Forms.TextBox(); this.txtDescription = new System.Windows.Forms.TextBox(); this.SuspendLayout(); // // label1 // this.label1.AutoSize = true; this.label1.Location = new System.Drawing.Point(23, 23); this.label1.Name = "label1"; this.label1.Size = new System.Drawing.Size(157, 25); this.label1.TabIndex = 0; this.label1.Text = "Picture Filename"; // // txtPicFilename // this.txtPicFilename.Anchor = ((System.Windows.Forms.AnchorStyles)(((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Left) | System.Windows.Forms.AnchorStyles.Right))); this.txtPicFilename.Location = new System.Drawing.Point(28, 52); this.txtPicFilename.Name = "txtPicFilename"; this.txtPicFilename.Size = new System.Drawing.Size(818, 29); this.txtPicFilename.TabIndex = 1; // // cmdBrowse // this.cmdBrowse.Anchor = ((System.Windows.Forms.AnchorStyles)((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Right))); this.cmdBrowse.Location = new System.Drawing.Point(863, 45); this.cmdBrowse.Name = "cmdBrowse"; this.cmdBrowse.Size = new System.Drawing.Size(65, 45); this.cmdBrowse.TabIndex = 2; this.cmdBrowse.Text = "..."; this.cmdBrowse.UseVisualStyleBackColor = true; this.cmdBrowse.Click += new System.EventHandler(this.cmdBrowse_Click); // // cmdAnalyze // this.cmdAnalyze.Anchor = ((System.Windows.Forms.AnchorStyles)((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Right))); this.cmdAnalyze.Location = new System.Drawing.Point(946, 45); this.cmdAnalyze.Name = "cmdAnalyze"; this.cmdAnalyze.Size = new System.Drawing.Size(185, 45); this.cmdAnalyze.TabIndex = 4; this.cmdAnalyze.Text = "Analyze"; this.cmdAnalyze.UseVisualStyleBackColor = true; this.cmdAnalyze.Click += new System.EventHandler(this.cmdAnalyze_Click); // // label2 // this.label2.AutoSize = true; this.label2.Location = new System.Drawing.Point(23, 115); this.label2.Name = "label2"; this.label2.Size = new System.Drawing.Size(76, 25); this.label2.TabIndex = 5; this.label2.Text = "Results"; // // txtResults // this.txtResults.Anchor = ((System.Windows.Forms.AnchorStyles)((((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Bottom) | System.Windows.Forms.AnchorStyles.Left) | System.Windows.Forms.AnchorStyles.Right))); this.txtResults.Location = new System.Drawing.Point(28, 183); this.txtResults.Multiline = true; this.txtResults.Name = "txtResults"; this.txtResults.ScrollBars = System.Windows.Forms.ScrollBars.Vertical; this.txtResults.Size = new System.Drawing.Size(1103, 520); this.txtResults.TabIndex = 6; // // txtDescription // this.txtDescription.Anchor = ((System.Windows.Forms.AnchorStyles)(((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Left) | System.Windows.Forms.AnchorStyles.Right))); this.txtDescription.Location = new System.Drawing.Point(28, 143); this.txtDescription.Name = "txtDescription"; this.txtDescription.ReadOnly = true; this.txtDescription.Size = new System.Drawing.Size(1095, 29); this.txtDescription.TabIndex = 7; // // Form1 // this.AutoScaleDimensions = new System.Drawing.SizeF(11F, 24F); this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font; this.ClientSize = new System.Drawing.Size(1161, 735); this.Controls.Add(this.txtDescription); this.Controls.Add(this.txtResults); this.Controls.Add(this.label2); this.Controls.Add(this.cmdAnalyze); this.Controls.Add(this.cmdBrowse); this.Controls.Add(this.txtPicFilename); this.Controls.Add(this.label1); this.Name = "Form1"; this.Text = "getMetadata v1.0"; this.ResumeLayout(false); this.PerformLayout(); } #endregion private System.Windows.Forms.Label label1; private System.Windows.Forms.TextBox txtPicFilename; private System.Windows.Forms.Button cmdBrowse; private System.Windows.Forms.Button cmdAnalyze; private System.Windows.Forms.Label label2; private System.Windows.Forms.TextBox txtResults; private System.Windows.Forms.TextBox txtDescription; } }

Continue to Get Image Metadata (Part 3) Where we will Build Compile and Test

Get Image Metadata (Part 1)

Anthony Marsiglia — Wed, 28 Mar 2018 23:34:53 GMT

Lets build off what we learned of the “ComputerVisionMetaData” Project we built in the post Computer Vision – Analyze (Get Meta Data of Image) , lets first Begin by creating a new Windows Form App Project called “GetImageMetaData” in Visual Studio If you have want to add this project to a Source Control such as TFS or GIT, select the add to Source Control option. If you do not wish to at this time or not sure what this is than I would verify that this option is unchecked and and than click on OK. In a few moments you will be presented with the Project Template that we will begin to build our code on. Within the Solution Explorer Window Click on References Using Visual Studios 2017 my project has automatically been assigned the references in this image, but we need a few more. Right click on either “GetImageMetaData” or “References” and select “Manage NuGet Packages…. you should be presented with the NuGet Package Center Select Newtonsoft.JSON and be sure to Install the latest version. When installation is completed In the Solution Explorer Click on “Form1.cs Expand Form1.cs in the Solution Explorer Now Click on Form 1() and in your main image you should see the default code that was in this template At the Top add the following using statements

using Newtonsoft.Json; using Newtonsoft.Json.Linq; using System.IO; using System.Net.Http;

After you added all the Necessary using statements underneath the lines , just after the brace.

public partial class Form1 : Form {

add the following constants

const string skey = "your vision api key here"; const string uriBase = "https://westus.api.cognitive.microsoft.com/vision/v1.0/"; const string apiMethod = "analyze";

At this point your code should now look like this… Now just after the following block of code... public Form1() { InitializeComponent(); } add the following block of code private void cmdBrowse_Click(object sender, EventArgs e) { var dlg = new OpenFileDialog(); dlg.Filter = "jpg|*.jpg"; var result = dlg.ShowDialog(); if (result == DialogResult.OK) txtPicFilename.Text = dlg.FileName; } after this add the next block of code public static async Task MakeAnalysisRequest(string imageFilePAth) { HttpClient client = new HttpClient(); client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", skey); AnalysisResults results; string requestParameters = "visualFeatures=Categories,Description,Color&language=en"; string uri = uriBase + apiMethod + "?" + requestParameters; HttpResponseMessage response = null; byte[] byteData = GetImageAsByteArray(imageFilePAth); using (ByteArrayContent content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new System.Net.Http.Headers.MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(uri, content); string contentstring = await response.Content.ReadAsStringAsync(); Console.WriteLine("\nResponse:\n"); var jsonObj = JObject.Parse(contentstring); // JsonConvert.DeserializeObject(contentstring); string indentedJson = JsonConvert.SerializeObject(jsonObj, Formatting.Indented); results = new AnalysisResults() { JsonObj = jsonObj, jsonStr = indentedJson }; } return results; } And then finally add the last block of code public static byte[] GetImageAsByteArray(string imageFilePath) { FileStream fileStream = new FileStream(imageFilePath, FileMode.Open, FileAccess.Read); BinaryReader binaryReader = new BinaryReader(fileStream); return binaryReader.ReadBytes((int)fileStream.Length); } Your code should now look like the following... At this time ignore the red squiggly lines Continue to Get Image Metadata (Part 2)

Computer Vision – Generate Thumbnail

Anthony Marsiglia — Wed, 21 Mar 2018 18:48:25 GMT

We will start by Creating a new project just like we did with the Setting up the Project Post this time we will name the project Generate Thumbnail. Once your code looks like the above image add the using statement “using System.Net.Http.Headers;” Enter in your Computer Vision API Key in between the quotes for the variable “skey”. For the const string apiMethod type within the quotes generateThumbnail In the const string fileSource within the quotes add a file path to an image you will be generating the Thumbnail from. At this point your code should look like In the static void Main(string[] args) section between the braces add the following

GenerateThumbnail(fileSource, 80, 80, true); Console.ReadLine();

At this point the code should look like Note: you will see a red squiggly line under GenerateThumbnail, Now lets add the next block of code under the static void Main block of code

public static async void GenerateThumbnail(string fileSource, int width, int height, bool smart) { byte[] thumbnail = await GetThumbnail(fileSource, width, height, smart); string thumbnailFullPath = string.Format("{0}\\thumbnail_{1:yyyy-MMM-dd_hh-mm-ss}.jpg", Path.GetDirectoryName(fileSource), DateTime.Now); using (BinaryWriter bw = new BinaryWriter(new FileStream(thumbnailFullPath, FileMode.OpenOrCreate, FileAccess.Write))) bw.Write(thumbnail); }

Your code should now look like this Now under that the block of code you just added give your self some more space and add the following block of code.

public static async Task GetThumbnail(string fileSource, int width, int height, bool smart) { HttpClient client = new HttpClient(); client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", skey); string requestParameters = $"width={width.ToString()}&height={height.ToString()}&smartCropping={smart.ToString().ToLower()}"; string uri = uriBase + apiMethod + "?" + requestParameters; HttpResponseMessage response = null; byte[] byteData = GetImageAsByteArray(fileSource); using (ByteArrayContent content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(uri, content); return await response.Content.ReadAsByteArrayAsync(); } }

Your code should now look like this Now we just need to add one more small block of code under that last one you added

public static byte[] GetImageAsByteArray(string fileSource) { FileStream fileStream = new FileStream(fileSource, FileMode.Open, FileAccess.Read); BinaryReader binaryReader = new BinaryReader(fileStream); return binaryReader.ReadBytes((int)fileStream.Length); }

Your code should now look like this Now just make sure you entered the key in correctly and that have an image file path set for the const string fileSource Build the code make sure there are no errors and click on Start, Check the location of the file that was set in the fileSource and verify there is a much smaller image there a (“thumbnail”)

Computer Vision API - Methods and Models

Anthony Marsiglia — Wed, 21 Mar 2018 14:40:26 GMT

When working with the Computer Vision API we need to understand what methods we can use for the API. A good resource of information is the Computer Vision Documentation , this Blog will be focused on utilizing the Computer Vision API with C# but there are multiple programing languages that these Cognitive Services APIS can be developed with. An important concept to understand is the API Methods which get passed in with the Endpoint URL. These Methods tell the API that you are contacting what it is you wish to utilize that API for. With the Analyze Image method, you can extract visual features based on image content. You can upload an image or specify an image URL and choose which features to return, including: You can also utilize Domain-Specific Models Such as Celebrities and Landmarks, these 2 models can be used to analyze data (image / video) and identify Places of known interest such as the Empire States Building , The White House, The Leaning Tower of Pisa etc. If an image is sent to the Computer Vision API using the Landmark model, the image is “analyzed” and the API tries to determine where the image takes place. The Celebrity Model is used to identify Known Celebrities, if an image is sent to the Computer Vision API using the Celebrity Model the API would try to identify any people that it recognizes in the image. If you submitted an image with you standing next to Arnold Schwarzenegger, the API would probably be able to determine that you are standing next to Arnold Schwarzenegger but may not be able to identify you specifically and would return a result for you that the API thinks best matches you. Lets take a look at some of these Methods and Models and how we use them First lets look at the Endpoint URL for the Computer Vision API

Log into your Azure Portal
Look for the Computer Vision API you set up under Cognitive Services
- If you have not done this already Follow this guide to do so.
Looking at Your Computer Vision API you should see something like this

The Endpoint URL which I believe is the same for everyone but I would double check should look like the following https://westus.api.cognitive.microsoft.com/vision/v1.0 When working with a method like analyze the Endpoint URL is appended with the name of the Method like this https://westus.api.cognitive.microsoft.com/vision/v1.0/analyze When working with a Model such as Landmark the Endpoint URL is appended with the Model and the Method and looks like this https://westus.api.cognitive.microsoft.com/vision/v1.0/models/landmarks Some other examples of Methods are: generateThumbnail https://westus.api.cognitive.microsoft.com/vision/v1.0/generateThumbnail ocr https://westus.api.cognitive.microsoft.com/vision/v1.0/ocr recognizeText https://westus.api.cognitive.microsoft.com/vision/v1.0/recognizeText Using the Celebrity Model would look like this https://westus.api.cognitive.microsoft.com/vision/v1.0/models/celebrities

Computer Vision - Analyze (Get Meta Data of Image)

Anthony Marsiglia — Tue, 20 Mar 2018 23:23:29 GMT

The first project we will compose, will be built off the Starter Project we created in Setting up the Project post. This Base project should look like the following. Now lets add the following inbetween the 2 braces within the “static void Main(string[] args) section

string imageFilePath = fileSource; MakeAnalysisRequest(imageFilePath); Console.ReadLine();

Your code should now look like the this At this point you should see some red squiggly lines under MakeAnalysisRequest, this is normal behavior as we have not defined what this is. Now just after the block of code we just added give your self some space one or two lines In this space add this next block of code.

public static async void MakeAnalysisRequest(string imageFilePAth) { HttpClient client = new HttpClient(); client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", skey); string requestParameters = "visualFeatures=Categories,Description,Color&language=en"; string uri = uriBase + apiMethod + "?" + requestParameters; //string uri = uriBase + "?" + requestParameters; HttpResponseMessage response = null; byte[] byteData = GetImageAsByteArray(imageFilePAth); using (ByteArrayContent content = new ByteArrayContent(byteData)) { content.Headers.ContentType = new System.Net.Http.Headers.MediaTypeHeaderValue("application/octet-stream"); response = await client.PostAsync(uri, content); string contentstring = await response.Content.ReadAsStringAsync(); Console.WriteLine("\nResponse:\n"); Console.WriteLine(contentstring); //Console.WriteLine(contentstring); //Console.WriteLine(JsonPrettyPrint(contentstring)); } }

Your program should now look like the following 2 images together. Now you should notice that the “MakeAnalysisRequest” is no longer marked with a red squiggly line. But within the new section you just added you will see a new red squiggly line, which is under GetImageAsByteArray Under that last block of code you just added, give your self some space and insert the following block of code.

public static byte[] GetImageAsByteArray(string imageFilePath) { FileStream fileStream = new FileStream(imageFilePath, FileMode.Open, FileAccess.Read); BinaryReader binaryReader = new BinaryReader(fileStream); return binaryReader.ReadBytes((int)fileStream.Length); }

The red squiggly line should now be gone and the code should look like this. Click “Build Solution” and verify there are no issues, but WAIT your not done just yet, Open up your Azure Portal and Get your Vision API Key and paste it in between the quotes of the skey in the Variable. Verify that the Endpoint matches the Endpoint for your Vision API, if it doesn't replace the uriBase variable we predefined earlier with the Endpoint that you have. Now for the apiMethod in between the quotes type “analyze”. for your fileSource leave the @ symbol and add the full path and name of an image you would like to submit to the Cognitive Services Vision API. this block of code should look something like this ok now click on Build again and verify there are no errors. When your ready to test click on the Green Start Arrow In a moment you should see a console window pop up, this process may take a second, so if its blank like this, do not close this window. After a moment or 2 you should get some metadata back about the image you submitted, but if you get this message than you need to check and re enter your subscription key after you fix the subscription key lets click on start again

Setting up the Project

Anthony Marsiglia — Tue, 20 Mar 2018 00:41:17 GMT

In Visual Studios click on File | New | Project In the New Project window Select Visual C# | Console App (.Net Framework) For Name , you can leave as Default or name it something that reflects the Project you are going to write. unless you wish to change the location for this project leave the default value and verify Create directory for solution is checked. You can select the Add to Source Control if your Visual Studios is connected to TFS or GIT Hub. Once you click on Ok the initial Project will setup and Load. At first you should only see the following bit of code which includes 5 using statements. Notice the namespace in this particular project says “ComputerVisionMetaData” , What ever you put as the Name of the project will show up here. Add the following using statements using System.IO; using System.Net.Http; Your Code should now look like Now lets add some Variables which we will use throughout our projects. Just under Class Program and the 1st Brace add the following:

const string skey = " ";

const string uriBase = "https://westus.api.cognitive.microsoft.com/vision/v1.0/";

const string apiMethod = " ";

const string fileSource = @"C:\Users\Pictures\"; // Source Location of Test Image

The Code should now look like The Variable skey will be the Key you get from Managed Keys within the API you are going to access with this project. In more complex projects you will have multiple variables set depending on how many different Cognitive Services API’s you need to access. For Review at this point your code should look something like the above image, Snippet of code will be used for a few of the projects that we will walk through in this blog. We added a few Constant Variables which will be used as well.

SKEY
- Is the variable that will be used to pass in the Key associated with the Specific Cognitive Services API this project will be working with.
uriBase
- Is the variable that will be used to pass in the Endpoint of the API that you are going to access with this project.
apiMethod
- Is the Method which gets appended to the uriBase, that when get put together with the rest of the "requestParameters" to form the Request URL. For more information on understanding and building the Request URL please visit the Vision API Reference.
fileSource
- Is going to be used to define the path of the file (image, video, etc) that we are going to submit to the Cognitive Services API.

In the Next Post we will continue to build out the initial project which will get used several times on this Blog Site.

Preparing to build / write your 1st Program utilizing Cognitive Services

Anthony Marsiglia — Mon, 19 Mar 2018 23:47:41 GMT

When your ready to build your first program be sure you have the following information 1. The Endpoint address 2. Access Key, which you get by clicking on the Show Access Keys … which is under the Manage Keys section. You should also read up on the Cognitive Services API Methods which can be found for the following: Computer Vision API Face API Text Analytics Once you are ready Open up Visual Studios and lets begin.

Where to Begin

Anthony Marsiglia — Mon, 19 Mar 2018 22:16:47 GMT

Before we begin you should first become familiar with "what cognitive services" is / are. I would start by reviewing the following blogs Try Cognitive Services What is Cognitive Services? Following the Getting started section of the "What is Cognitive Services" site you will than get to the section "Create a Cognitive Services APIs account in the Azure portal" Familiarize yourself with the Azure Portal Page and when your ready set up your first few Cognitive Services API's I would at least start with the following Computer Vision API Face API Text Analytics API We can always add more later as you need them. You do not need to be a Developer to start with Cognitive Services, so take your time and start thinking about how these Cognitive Services API's can help you. Start with something small and build from there. I hope this site is helpful, please feel free to leave Comments and Feedback.