Updates

Author: johnolafenwa

Idris-Elba.jpg

@@ -0,0 +1,34 @@
+using System;
+    using System.IO;
+    using System.Net.Http;
+    using System.Threading.Tasks;
+
+
+    namespace app
+    {
+
+        class App {
+
+        static HttpClient client = new HttpClient();
+
+        public static async Task makeRequest(){
+
+            var request = new MultipartFormDataContent();
+            var image_data = File.OpenRead("image.jpg");
+            request.Add(new StreamContent(image_data),"image",Path.GetFileName("image.jpg"));
+            var output = await client.PostAsync("http://localhost:80/v1/vision/scene",request);
+            var jsonString = await output.Content.ReadAsStringAsync();
+            
+            Console.WriteLine(jsonString);
+
+        }
+
+        static void Main(string[] args){
+
+            makeRequest().Wait();
+
+        }
+
+        }
+    
+    }

backup.rs

@@ -3,8 +3,10 @@
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
+.. _facedetection:
+
 Face Detection
-==============
+================
 
 The face detection API detects faces and returns their coordinates as well as the gender.
 It functions similarly to the face recognition API except that it does not 
@@ -58,12 +60,6 @@ Also note that the recognition API does not return gender predictions.
             var output = await client.PostAsync("http://localhost:80/v1/vision/face",request);
             var jsonString = await output.Content.ReadAsStringAsync();
             Response response = JsonConvert.DeserializeObject<Response>(jsonString);
-            
-            foreach (var user in response.predictions){
-
-                Console.WriteLine(user.gender);
-
-            }
 
             Console.WriteLine(jsonString);
 
@@ -85,7 +81,7 @@ Result ::
     male
     male
     female
-    {'predictions': [{'y_max': 303, 'gender': 'female', 'confidence': 0.99999213, 'x_min': 534, 'x_max': 629, 'y_min': 174}, {'y_max': 275, 'gender': 'male', 'confidence': 0.6611953, 'x_min': 616, 'x_max': 711, 'y_min': 146}, {'y_max': 259, 'gender': 'male', 'confidence': 0.99884146, 'x_min': 729, 'x_max': 811, 'y_min': 147}, {'y_max': 290, 'gender': 'female', 'confidence': 0.99997365, 'x_min': 471, 'x_max': 549, 'y_min': 190}], 'success': True}
+    {'predictions': [{'y_max': 303, 'gender': 'female', 'confidence': 100, 'x_min': 534, 'x_max': 629, 'y_min': 174}, {'y_max': 275, 'gender': 'male', 'confidence': 99, 'x_min': 616, 'x_max': 711, 'y_min': 146}, {'y_max': 259, 'gender': 'male', 'confidence': 98, 'x_min': 729, 'x_max': 811, 'y_min': 147}, {'y_max': 290, 'gender': 'female', 'confidence': 99, 'x_min': 471, 'x_max': 549, 'y_min': 190}], 'success': True}
 
 We can use the coordinates returned to extract the faces from the image
 
@@ -148,7 +144,7 @@ We can use the coordinates returned to extract the faces from the image
                 image.Mutate(x => x
                 .Crop(crop_region)
                 );
-                image.Save(user.gender + i.ToString() + "_.jpg");
+                image.Save(i.ToString() + "_.jpg");
 
             }
 

deepstack_activated.png

@@ -0,0 +1,133 @@
+.. DeepStack documentation master file, created by
+   sphinx-quickstart on Wed Dec 12 17:30:35 2018.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+.. _facematch:
+
+Face Match
+===========
+
+The face detection api compares faces in two different pictures and tells the similarity between them.
+A typical use of this is matching identity documents with pictures of a person.
+
+
+**Example**
+
+Here we shall compare two pictures of obama
+
+.. figure:: test-image6.jpeg
+    :align: center
+
+.. figure:: test-image7.jpg
+    :align: center
+
+::
+
+    using System;
+    using System.IO;
+    using System.Net.Http;
+    using System.Threading.Tasks;
+
+
+    namespace app
+    {
+
+        class App {
+
+        static HttpClient client = new HttpClient();
+
+        public static async Task makeRequest(){
+
+            var request = new MultipartFormDataContent();
+            var image_data1 = File.OpenRead("test-image6.jpeg");
+            var image_data2 = File.OpenRead("test-image7.jpg");
+            request.Add(new StreamContent(image_data1),"image1",Path.GetFileName("test-image6.jpeg"));
+            request.Add(new StreamContent(image_data2),"image2",Path.GetFileName("test-image7.jpg"));
+            var output = await client.PostAsync("http://localhost:80/v1/vision/face/match",request);
+            var jsonString = await output.Content.ReadAsStringAsync();
+            
+            Console.WriteLine(jsonString);
+
+        }
+
+        static void Main(string[] args){
+
+            makeRequest().Wait();
+
+        }
+
+        }
+    
+    }
+
+Result ::
+
+    {'similarity': 0.73975885, 'success': True}
+
+Here we shall compare a picture of Obama with that of Bradley Cooper
+
+.. figure:: test-image6.jpeg
+    :align: center
+
+.. figure:: test-image8.jpg
+    :align: center
+
+::
+
+    using System;
+    using System.IO;
+    using System.Net.Http;
+    using System.Threading.Tasks;
+
+
+    namespace app
+    {
+
+        class App {
+
+        static HttpClient client = new HttpClient();
+
+        public static async Task makeRequest(){
+
+            var request = new MultipartFormDataContent();
+            var image_data1 = File.OpenRead("test-image6.jpeg");
+            var image_data2 = File.OpenRead("test-image8.jpg");
+            request.Add(new StreamContent(image_data1),"image1",Path.GetFileName("test-image6.jpeg"));
+            request.Add(new StreamContent(image_data2),"image2",Path.GetFileName("test-image8.jpg"));
+            var output = await client.PostAsync("http://localhost:80/v1/vision/face/match",request);
+            var jsonString = await output.Content.ReadAsStringAsync();
+            
+            Console.WriteLine(jsonString);
+
+        }
+
+        static void Main(string[] args){
+
+            makeRequest().Wait();
+
+        }
+
+        }
+    
+    }
+
+Result ::
+
+    {{'similarity': 0.4456827, 'success': True}
+
+As seen above, the match for two different pictures of Obama was very high while the match for Obama and Bradley Cooper was very low.
+
+**Performance**
+
+DeepStack offers three modes allowing you to tradeoff speed for peformance. 
+During startup, you can specify performance mode to be , **"High" , "Medium" and "Low"**
+
+The default mode is "Medium"
+
+You can speciy a different mode as seen below ::
+
+    sudo docker run -e MODE=High -e VISION-FACE=True -v localstorage:/datastore \
+    -p 80:5000 deepquestai/deepstack
+
+Note the -**e MODE=High** above

deepstack_pre.png

@@ -153,11 +153,9 @@ We shall test this on the image below.
 
 Result ::
 
-    unknown
     Idris Elba
-    Full Response:  {'predictions': [{'confidence': 0, 'y_min': 233, 'x_max': 1290, 'x_min': 850,
-    'userid': 'unknown', 'y_max': 827}, {'confidence': 0.6676924, 'y_min': 160, 'x_max': 2041, 
-    'x_min': 1577, 'userid': 'Idris Elba', 'y_max': 767}], 'success': True}
+    unknown
+    Full Response:  {'success': True, 'predictions': [{'x_min': 215, 'confidence': 0.76965684, 'x_max': 264, 'y_max': 91, 'y_min': 20, 'userid': 'Idris Elba'}, {'x_min': 115, 'confidence': 0, 'x_max': 162, 'y_max': 97, 'y_min': 31, 'userid': 'unknown'}]}
 
 As you can see above, the first user is unknown since we did not previously register her, however, Idris Elba was detected as we
 registered a picture of his in the previous tutorial.
@@ -254,9 +252,8 @@ Result
 **Setting Minimum Confidence**
 
 DeepStack recognizes faces by computing the similarity between the embedding of a new face and the set of embeddings of previously registered faces.
-By default, the minimum confidence is 0.45. The confidence ranges between 0 and 1.
+By default, the minimum confidence is 0.67. The confidence ranges between 0 and 1.
 If the similarity for a new face falls below the min_confidence, unknown will be returned.
-
 The min_confidence parameter allows you to increase or reduce the minimum confidence.
 
 We lower the confidence allowed below.
@@ -327,17 +324,15 @@ Example ::
 
 Result ::
 
-    Adele
     Idris Elba
-    Full Response:  {'success': True, 'predictions': [{'confidence': 0.44580227, 'y_min': 233,
-    'y_max': 827, 'userid': 'Adele', 'x_max': 1290, 'x_min': 850}, {'confidence': 0.6676924, 
-    'y_min': 160, 'y_max': 767, 'userid': 'Idris Elba', 'x_max': 2041, 'x_min': 1577}]}
+    Adele
+    Full Response:  {'success': True, 'predictions': [{'userid': 'Idris Elba', 'y_min': 154, 'x_min': 1615, 'x_max': 1983, 'confidence': 0.76965684, 'y_max': 682}, {'userid': 'Adele', 'y_min': 237, 'x_min': 869, 'x_max': 1214, 'confidence': 0.6044803, 'y_max': 732}]}
 
 By reducing the allowed confidence, the system detects the first face as Adele. The lower the confidence, the more likely
 for the system to make mistakes. When the confidence level is high, mistakes are extremely rare, however, the system may 
 return unknown always if the confidence is too high.
 
-**For security related processes such as authentication, set the min_confidence at 0.5 or higher**
+**For security related processes such as authentication, set the min_confidence at 0.7 or higher**
 
 Managing Registered Faces
 --------------------------
@@ -423,3 +418,17 @@ Deleting a face ::
 Result ::
 
     {'success': True}
+
+**Performance**
+
+DeepStack offers three modes allowing you to tradeoff speed for peformance. 
+During startup, you can specify performance mode to be , **"High" , "Medium" and "Low"**
+
+The default mode is "Medium"
+
+You can speciy a different mode as seen below ::
+
+    sudo docker run -e MODE=High -e VISION-FACE=True -v localstorage:/datastore \
+    -p 80:5000 deepquestai/deepstack
+
+Note the -**e MODE=High** above 

facedetection.rst

@@ -7,18 +7,14 @@ Getting Started with DeepStack
 ===============================
 
 DeepStack is distributed as a docker image. In this tutorial, we shall 
-go through the complete process of setting up docker and DeepStack and using it
+go through the complete process of using DeepStack
 to build a Face Recognition system.
 
-**Setting Up Docker** 
+Setting Up DeepStack
+---------------------
 
-Docker is a container platform that allows developers to distribute applications
-as self-contained packages that ships every dependency from the
-operating system to the app dependences. It is similar to virtual machines
-but is more lightweight and easier to manage. 
-
-You can learn more about Docker on `Docker's Website <https://docker.io />`_
-Visit  `Docker Getting Started <https://docs.docker.com/get-started />`_ for instructions on setting up and using Docker for the first time.
+Follow instructions on read :ref:`home` to install the CPU Version of DeepStack
+If you have a system with Nvidia GPU, follow instruction on read :ref:`gpuinstall` to install the GPU Version of DeepStack
 
 **Installing DeepStack**
 
@@ -208,3 +204,17 @@ We have just created a face recognition system. You can try with different peopl
 
 The next tutorial is dedicated to the full power of the face recognition api as well as best practices to make the best out of it.
 
+**Performance**
+
+DeepStack offers three modes allowing you to tradeoff speed for peformance. 
+During startup, you can specify performance mode to be , "High","Medium" and "Low"
+
+The default mode is "Medium"
+
+You can speciy a different mode as seen below ::
+
+    sudo docker run -e MODE=High -e VISION-FACE=True -v localstorage:/datastore \
+    -p 80:5000 deepquestai/deepstack
+
+Note the -**e MODE=High** above 
+