Primer vistazo al computer vision | 4Sessions Feb17
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Primer vistazo al COMPUTER VISION #FourSessions Toni Recio
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Transcript of Primer vistazo al computer vision | 4Sessions Feb17
Primer vistazo al COMPUTER VISION#FourSessions
Toni Recio
Agenda
Computer Vision
Las diferentes aproximaciones
Benchmarking de API’s en la nube
OpenCV
Consumir clasificador
Detectar vs Identificar
Crear un clasificador
Computer
Vision
2 cámaras de foto biológicas
Captura de foto cada 200ms
En 3 años un niño ha visto cientos
de millones de “fotografías”
Pattern
Recognition
Machine
LearningDeep
Learning
Applied
AI
Strong
AI
Applied
AI
Strong
AI
Applied
AI
Strong
AI
Applied
AI
Strong
AI
Applied
AI
Strong
AI
Applied
AI
Strong
AI
FUTUROLOGÍA
FUTUROLOGÍA
FUTUROLOGÍA
PRESENTOLOGÍA
Las diferentes
aproximaciones
Benchmarking
API’s en la nube
Vision > Computer Vision
Vision > Computer Vision
a cat sitting
in front of a
computer
keyboard
Vision > Computer Vision
Vision > Computer Vision
Vision > Computer Vision
Vision > Computer Vision
Vision > Computer Vision
Vision > Face
Vision > Face
Vision > Face
Vision > Face
Vision > Face
Vision > Face
Vision > Face
Vision > Emotion
Vision > Emotion
Vision > Emotion
Vision > Video
Vision > Video
Vision > Video
Vision > Video
https://www.microsoft.com/cognitive-services/en-US/subscriptions
var visionClient = new VisionServiceClient("CLAVE_EXTRAIDA_DEL _PORTAL_DE_MCS");
using (Stream imageFileStream = File.OpenRead("C:\\CODE\\ComputerVisionSamples\\ComputerVision.Wpf\\Images\\catkeyboard.png"))
{var features = new VisualFeature[] { VisualFeature.Adult,VisualFeature.Categories,VisualFeature.Color,VisualFeature.Description,VisualFeature.Faces,VisualFeature.ImageType,VisualFeature.Tags };var result = await visionClient.AnalyzeImageAsync(imageFileStream, features);
}
https://console.cloud.google.com
https://console.cloud.google.com
public static GoogleCredential CreateCredentials(string path){
GoogleCredential credential;using (var stream = new FileStream(path, FileMode.Open,
FileAccess.Read)){
var c = GoogleCredential.FromStream(stream);credential = c.CreateScoped(VisionService.Scope.CloudPlatform);
}
return credential;}
public static VisionService CreateService(string applicationName,IConfigurableHttpClientInitializer credentials)
{var service = new VisionService(new BaseClientService.Initializer(){
ApplicationName = applicationName,HttpClientInitializer = credentials
});
return service;}
public static IList<AnnotateImageResponse> DetectLabels(VisionService vision, string imagePath)
{// Convert image to Base64 encoded for JSON ASCII text based request byte[] imageArray = System.IO.File.ReadAllBytes(imagePath);string imageContent = Convert.ToBase64String(imageArray);// Post label detection request to the Vision APIvar responses = vision.Images.Annotate(
new BatchAnnotateImagesRequest(){
Requests = new[] {new AnnotateImageRequest() {
Features = new [] {new Feature() {Type = "LABEL_DETECTION"},new Feature() {Type = "TEXT_DETECTION"},new Feature() {Type = "FACE_DETECTION"},new Feature() {Type = "LANDMARK_DETECTION"},new Feature() {Type = "LOGO_DETECTION"},new Feature() {Type = "SAFE_SEARCH_DETECTION"},new Feature() {Type = "IMAGE_PROPERTIES"}
},Image = new Image() { Content = imageContent }
}}}).Execute();
return responses.Responses;}
var credentails = CreateCredentials("c:\\archivos\\credenciales.json");var service = CreateService("TEST", credentails);var result = DetectLabels(service, "C:\\archivos\\playoffs2016.jpg");
Open CV
http://opencv.org/
https://github.com/opencv/opencv/tree/master/data
http://www.emgu.com/wiki/index.php/Main_Page
long detectionTime;Mat image = new Mat("C:\\archivos\\playoffs2016.jpg", LoadImageType.Color); List<System.Drawing.Rectangle> faces = new List<System.Drawing.Rectangle>();using (CascadeClassifier cascadeCla =
new CascadeClassifier("Classifiers\\haarcascade_frontalface_default.xml")){
Rectangle[] faces = cascadeCla.DetectMultiScale(image,1.1,8);
}
long detectionTime;Mat image = new Mat("C:\\archivos\\playoffs2016.jpg", LoadImageType.Color); List<System.Drawing.Rectangle> faces = new List<System.Drawing.Rectangle>();using (CascadeClassifier cascadeCla =
new CascadeClassifier("Classifiers\\haarcascade_frontalface_default.xml")){
Rectangle[] faces = cascadeCla.DetectMultiScale(image,1.1,8);
}
Detectar
Vs
Identificar
María
1 2 3 4 5
1 2 3 4 5
Image<Gray, Byte>[] trainingImages = new Image<Gray, Byte>[5];trainingImages[0] = new Image<Gray, byte>("C:\\Images\\alex.png");trainingImages[1] = new Image<Gray, byte>("C:\\Images\\arturo.png");trainingImages[2] = new Image<Gray, byte>("C:\\Images\\lauree.png");trainingImages[3] = new Image<Gray, byte>("C:\\Images\\javier.png");trainingImages[4] = new Image<Gray, byte>("C:\\maria.png");
Image<Gray, Byte>[] trainingImages = new Image<Gray, Byte>[5];trainingImages[0] = new Image<Gray, byte>("C:\\Images\\alex.png");trainingImages[1] = new Image<Gray, byte>("C:\\Images\\arturo.png");trainingImages[2] = new Image<Gray, byte>("C:\\Images\\lauree.png");trainingImages[3] = new Image<Gray, byte>("C:\\Images\\javier.png");trainingImages[4] = new Image<Gray, byte>("C:\\maria.png");
int[] labels = new int[] { 1, 2, 3, 4, 5 };
Image<Gray, Byte>[] trainingImages = new Image<Gray, Byte>[5];trainingImages[0] = new Image<Gray, byte>("C:\\Images\\alex.png");trainingImages[1] = new Image<Gray, byte>("C:\\Images\\arturo.png");trainingImages[2] = new Image<Gray, byte>("C:\\Images\\lauree.png");trainingImages[3] = new Image<Gray, byte>("C:\\Images\\javier.png");trainingImages[4] = new Image<Gray, byte>("C:\\maria.png");
int[] labels = new int[] { 1, 2, 3, 4, 5 };
var recognizer = new LBPHFaceRecognizer(1, 8, 8, 8, 100);recognizer.Train(trainingImages, labels);
Image<Gray, Byte>[] trainingImages = new Image<Gray, Byte>[5];trainingImages[0] = new Image<Gray, byte>("C:\\Images\\alex.png");trainingImages[1] = new Image<Gray, byte>("C:\\Images\\arturo.png");trainingImages[2] = new Image<Gray, byte>("C:\\Images\\lauree.png");trainingImages[3] = new Image<Gray, byte>("C:\\Images\\javier.png");trainingImages[4] = new Image<Gray, byte>("C:\\maria.png");
int[] labels = new int[] { 1, 2, 3, 4, 5 };
var recognizer = new LBPHFaceRecognizer(1, 8, 8, 8, 100);recognizer.Train(trainingImages, labels);
Image<Gray, Byte> testImage = new Image<Gray, Byte>("C:\\Images\\test.png");
Image<Gray, Byte>[] trainingImages = new Image<Gray, Byte>[5];trainingImages[0] = new Image<Gray, byte>("C:\\Images\\alex.png");trainingImages[1] = new Image<Gray, byte>("C:\\Images\\arturo.png");trainingImages[2] = new Image<Gray, byte>("C:\\Images\\lauree.png");trainingImages[3] = new Image<Gray, byte>("C:\\Images\\javier.png");trainingImages[4] = new Image<Gray, byte>("C:\\maria.png");
int[] labels = new int[] { 1, 2, 3, 4, 5 };
var recognizer = new LBPHFaceRecognizer(1, 8, 8, 8, 100);recognizer.Train(trainingImages, labels);
Image<Gray, Byte> testImage = new Image<Gray, Byte>("C:\\Images\\test.png");
var label = recognizer.Predict(testImage);
Image<Gray, Byte>[] trainingImages = new Image<Gray, Byte>[5];trainingImages[0] = new Image<Gray, byte>("C:\\Images\\alex.png");trainingImages[1] = new Image<Gray, byte>("C:\\Images\\arturo.png");trainingImages[2] = new Image<Gray, byte>("C:\\Images\\lauree.png");trainingImages[3] = new Image<Gray, byte>("C:\\Images\\javier.png");trainingImages[4] = new Image<Gray, byte>("C:\\maria.png");
int[] labels = new int[] { 1, 2, 3, 4, 5 };
var recognizer = new LBPHFaceRecognizer(1, 8, 8, 8, 100);recognizer.Train(trainingImages, labels);
Image<Gray, Byte> testImage = new Image<Gray, Byte>("C:\\Images\\test.png");
var label = recognizer.Predict(testImage);
Crear un
clasificador
http://acodigo.blogspot.com.es/2015/12/entrenar-opencv-en-deteccion-de-objetos.html
http://www-cvr.ai.uiuc.edu/ponce_grp/data/
https://github.com/TutorProgramacion/opencv-
traincascade/blob/master/image_dataset/images.rar
pos/pos-532.pgm 1 0 0 100 40
pos/pos-166.pgm 1 0 0 100 40
pos/pos-76.pgm 1 0 0 100 40
pos/pos-193.pgm 1 0 0 100 40
pos/pos-0.pgm 1 0 0 100 40
pos/pos-84.pgm 1 0 0 100 40
pos/pos-333.pgm 1 0 0 100 40
pos/pos-15.pgm 1 0 0 100 40
pos/pos-371.pgm 1 0 0 100 40
pos/pos-44.pgm 1 0 0 100 40
pos/pos-172.pgm 1 0 0 100 40
…
cars.info
neg/neg-225.pgm
neg/neg-310.pgm
neg/neg-24.pgm
neg/neg-119.pgm
neg/neg-198.pgm
neg/neg-155.pgm
neg/neg-31.pgm
neg/neg-441.pgm
neg/neg-56.pgm
neg/neg-455.pgm
neg/neg-144.pgm
…
neg.info
cd C:\opencv\build\x86\vc11\bin
opencv_createsamples -info cars.info -num 550 -w 48 -h 24 -vec cars.vec
c:\opencv\build\x64\vc12\bin>opencv_traincascade.exe -data data -vec cars.vec
-bg neg.info -numPos 500 -numNeg 500 -numStages 10 -w 48 -h 24 -featureType LBP
c:\opencv\build\x64\vc12\bin>opencv_traincascade.exe -data data -vec cars.vec
-bg neg.info -numPos 500 -numNeg 500 -numStages 10 -w 48 -h 24 -featureType LBP
Un vistazo
atrás
GRACIAS
http://www.freepik.com/free-vector/abstract-blue-background-with-
triangles_710166.htm#term=glacial&page=1&position=0
http://www.freepik.com/free-vector/computers-and-school-
elements_719102.htm#term=learning&page=1&position=37
http://www.freepik.com/free-vector/colorful-brain-
icons_764996.htm#term=brain&page=1&position=1
http://www.freepik.com/free-vector/five-senses-
icons_837465.htm#term=senses&page=1&position=0
http://www.freepik.com/free-vector/analog-camera-
icon_791929.htm#term=camera&page=1&position=1
http://www.freepik.com/free-vector/photos-and-
cameras_804428.htm#term=picture&page=1&position=0
http://www.freepik.com/free-vector/magnifying-glass-data-
analysis_761448.htm#term=information&page=1&position=4
http://www.freepik.com/free-vector/educational-future-
concept_776917.htm#term=future&page=1&position=3
http://www.freepik.com/free-vector/global-education-
background_780891.htm#term=logic&page=1&position=0
http://www.freepik.com/free-vector/cartoon-scientist-with-chemical-
elements_848470.htm#term=scientist&page=1&position=9
http://www.freepik.com/free-vector/colorful-information-
buttons_807853.htm#term=information&page=1&position=5
