%%Leemos la imagen inicial
I = imread('grupo.png');
figure,imshow(I);

%% Detector de personas
peopleDetector = vision.PeopleDetector('ClassificationModel','UprightPeople_128x64');
peopleDetector.WindowStride = [6 6];
peopleDetector.MinSize = [128 64];         %%Tamaņo minimo de las personas
[bboxes, scores] = step(peopleDetector,I);
I_people = insertObjectAnnotation(I,'rectangle',bboxes,scores);
figure, imshow(I_people);

%% Detector de rostros
% Se crea el detector de objetos
faceDetector = vision.CascadeObjectDetector('FrontalFaceCART');            

% Detect faces
bbox = step(faceDetector, I); 

% Draw boxes around detected faces and display results              
shapeInserter = vision.ShapeInserter('BorderColor','Custom','CustomBorderColor',[255 255 0]);       %%Se define el color de la caja
I_faces = step(shapeInserter, I, int32(bbox));
imshow(I_faces);

%% Se numeran los rostros encontrados              
I_faces = insertObjectAnnotation(I,'rectangle',bbox,[1:size(bbox,1)]);
imshow(I_faces);

%% Detect Upper Bodies in the image
% Create a detector object 
bodyDetector = vision.CascadeObjectDetector('UpperBody'); 
bodyDetector.MinSize = [128 128];         %%Tamaņo minimo del cuerpo de la persona
bodyDetector.ScaleFactor = 1.05;

bbox_body = step(bodyDetector, I);

% Draw bounding boxes
I_body = insertObjectAnnotation(I,'rectangle',bbox_body,1:size(bbox_body,1));
figure, imshow(I_body);

%% Remove false detections by looking for face
bbox_face = zeros(size(bbox_body));
for i=1:length(bbox_body)
    Icrop = imcrop(I,bbox_body(i,:));
    bbox = step(faceDetector,Icrop);
    if ~isempty(bbox)
        bbox_face(i,:) = bbox + [bbox_body(i,1:2)-1 0 0];
    end
end
    
I_faces2 = insertObjectAnnotation(I,'rectangle',bbox_face,1:size(bbox_face,1));
figure, imshow(I_faces2);