I am implementing a rightclick context menu on my google v3 map and I need to get the pixel x and y to correctly position the menu. I get the lat and the lng, anyone have a nice solution to get the pixel x and y?
Best Regards
Henkemota
index=x+(y*height)
x = index % width
y = index / height
Correction to the above answer:
index=x+(y*width)
//(not y*height ... because you're taking one full horizontal line of pixels (e.g. 1280px) and multiplying that by the number of lines (y) down the screen at which x is, then adding x to account for x pixels over in the next full line.)
x = index % width
y = index / height
Related
I have created a synthetic image that consists of a circle at the centre of a box with the code below.
%# Create a logical image of a circle with image size specified as follows:
imageSizeY = 400;
imageSizeX = 300;
[ygv, xgv] = meshgrid(1:imageSizeY, 1:imageSizeX);
%# Next create a logical mask for the circle with specified radius and center
centerY = imageSizeY/2;
centerX = imageSizeX/2;
radius = 100;
Img = double( (ygv - centerY).^2 + (xgv - centerX).^2 <= radius.^2 );
%# change image labels from double to numeric
for ii = 1:numel(Img)
if Img(ii) == 0
Img(ii) = 2; %change label from 0 to 2
end
end
%# plot image
RI = imref2d(size(Img),[0 size(Img, 2)],[0 size(Img, 1)]);
figure, imshow(Img, RI, [], 'InitialMagnification','fit');
Now, i need to create a rectangular mask (with label == 3, and row/col dimensions: 1 by imageSizeX) across the image from top to bottom and at known angles with the edges of the circle (see attached figure). Also, how can i make the rectangle thicker than 1 by imageSizeX?. As another option, I would love to try having the rectangle stop at say column 350. Lastly, any ideas how I can improve on the resolution? I mean is it possible to keep the image size the same while increasing/decreasing the resolution.
I have no idea how to go about this. Please i need any help/advice/suggestions that i can get. Many thanks!.
You can use the cos function to find the x coordinate with the correct angle phi.
First notice that the angle between the radius that intersects the vertex of phi has angle with the x-axis given by:
and the x coordinate of that vertex is given by
so the mask simply needs to set that row to 3.
Example:
phi = 45; % Desired angle in degrees
width = 350; % Desired width in pixels
height = 50; % Desired height of bar in pixels
theta = pi-phi*pi/180; % The radius angle
x = centerX + round(radius*cos(theta)); % Find the nearest row
x0 = max(1, x-height); % Find where to start the bar
Img(x0:x,1:width)=3;
The resulting image looks like:
Note that the max function is used to deal with the case where the bar thickness would extend beyond the top of the image.
Regarding resolution, the image resolution is determined by the size of the matrix you create. In your example that is (400,300). If you want higher resolution simply increase those numbers. However, if you would like to link the resolution to a higher DPI (Dots per Inch) so there are more pixels in each physical inch you can use the "Export Setup" window in the figure File menu.
Shown here:
I have background subtracted images as input. The idea is to reduce search areas for person detection by using a smaller search area for the HOG algorithm. The output required is a bounding box around the person and the pixel positions of the box corners.
This is the input image:
This is the required output:
This is what I have tried so far:
x=imread('frame 0080.png');
y=im2bw(x);
s=regionprops(y);
imshow(y);
hold on
for i=1:numel(s)
rectangle('Position',s(i).BoundingBox,'edgecolor','y')
end
This was the output I got:
It looks like you have tried what I have suggested. However, you want the bounding box that encapsulates the entire object. This can easily be done by using the BoundingBox property, then calculating each of the four corners of each rectangle. You can then calculate the minimum spanning bounding box that encapsulates all of the rectangles which ultimately encapsulates the entire object.
I do notice that there is a thin white strip at the bottom of your image, and that will mess up the bounding box calculations. As such, I'm going to cut the last 10 rows of the image before we proceed calculating the minimum spanning bounding box. To calculate the minimum spanning bounding box, all you have to do is take all of the corners for all of the rectangles, then calculate the minimum and maximum x co-ordinates and minimum and maximum y co-ordinates. These will correspond to the top left of the minimum spanning bounding box and the bottom right of the minimum spanning bounding box.
When taking a look at the BoundingBox property using regionprops, each bounding box outputs a 4 element vector:
[x y w h]
x,y denote the top left co-ordinate of your bounding box. x would be the column and y would be the row of the top left corner. w,h denote the width and the height of the bounding box. We would use this and compute top left, top right, bottom left and bottom right of every rectangle that is detected. Once you complete this, stack all of these rectangle co-ordinates into a single 2D matrix, then calculate the minimum and maximum x and y co-ordinates. To calculate the rectangle, simply use the minimum x and y co-ordinates as the top left corner, then calculate the width and height by subtracting the maximum and minimum x and y co-ordinates respectively.
Without further ado, here's the code. Note that I want to extract all of the bounding box co-ordinates in a N x 4 matrix where N denotes the number of bounding boxes that are detected. You would have to use reshape to do this correctly:
% //Read in the image from StackOverflow
x=imread('http://i.stack.imgur.com/mRWId.png');
% //Threshold and remove last 10 rows
y=im2bw(x);
y = y(1:end-10,:);
% //Calculate all bounding boxes
s=regionprops(y, 'BoundingBox');
%// Obtain all of the bounding box co-ordinates
bboxCoords = reshape([s.BoundingBox], 4, []).';
% // Calculate top left corner
topLeftCoords = bboxCoords(:,1:2);
% // Calculate top right corner
topRightCoords = [topLeftCoords(:,1) + bboxCoords(:,3) topLeftCoords(:,2)];
% // Calculate bottom left corner
bottomLeftCoords = [topLeftCoords(:,1) topLeftCoords(:,2) + bboxCoords(:,4)];
% // Calculate bottom right corner
bottomRightCoords = [topLeftCoords(:,1) + bboxCoords(:,3) ...
topLeftCoords(:,2) + bboxCoords(:,4)];
% // Calculating the minimum and maximum X and Y values
finalCoords = [topLeftCoords; topRightCoords; bottomLeftCoords; bottomRightCoords];
minX = min(finalCoords(:,1));
maxX = max(finalCoords(:,1));
minY = min(finalCoords(:,2));
maxY = max(finalCoords(:,2));
% Draw the rectangle on the screen
width = (maxX - minX + 1);
height = (maxY - minY + 1);
rect = [minX minY width height];
% // Show the image
imshow(y);
hold on;
rectangle('Position', rect, 'EdgeColor', 'yellow');
This is the image I get:
I have a video of moving hose in an experiment and I need to detect certain points in that hose and calculate the amplitude of their movements, I am using the code below and I am able to extract the required point using detectSURFFeatures, the function get many unnecessary points so I am using cuba = ref_pts.selectStrongest(5); to choose only five points, the problem is I can not get a function to put a bounding box about this 5 points and get their pixel values through the video, Kindly advice what functions can be used, thanks :)
clear;
clc;
% Image aquisition from Video and converting into gray scale
vidIn = VideoReader('ItaS.mp4');
%% Load reference image, and compute surf features
ref_img = read(vidIn, 1);
ref_img_gray = rgb2gray(ref_img);
ref_pts = detectSURFFeatures(ref_img_gray);
[ref_features, ref_validPts] = extractFeatures(ref_img_gray, ref_pts);
figure; imshow(ref_img);
hold on; plot(ref_pts.selectStrongest(5));
cuba = ref_pts.selectStrongest(5);
stats1 = round(cuba.Location);
If you want to find the bounding box which covers all the five points you selected: stats1 now contains (x, y) coordinates of the selected 5 points. Find min and max for x and y coordinates. min values of x and y gives you the starting point of the rectangle. Width and height of the bounding box is now the difference of max and min in y and x directions.
If you want to extract the part of the original image inside the bounding box: just copy that part to another variable as you want. Consider the following example.
img2 = img1(y:h, x:w, :)
Here, x and y are the x and y coordinates of the top left corner of the bounding box. w and h are the width and height of the bounding box.
def changeRed():
setMediaPath("/Users/addison/Downloads/Cmpt101_Pics/Learjet31A.jpg")
filename1 = "/Users/addison/Downloads/Cmpt101_Pics/Learjet31A.jpg"
source = makePicture(filename1)
halfHeight = getHeight(source)/2
for x in range(0,getWidth(source)):
for y in range(0, halfHeight):
pixel = getPixel(source, x, y)
value = getRed(pixel)
setRed(pixel, value-127.5)
show(source)
Sooo this is my code right now to select the top half of a picture and decresa the redness by 50%. My program also needs to select the bottom half of the picture and increase the redness by 50%, how do i go about doing this?
Pretty much add another for loop within the x in range loop but not in the for y loop you already have. This new for y in range loop should have a range of halfHeight,getHeight(source). Also subtracting -127.5 from red pixels isnt decreasing the red by 50%. Use value/2 instead.
I have background subtracted images as input. The idea is to reduce search areas for person detection by using a smaller search area for the HOG algorithm. The output required is a bounding box around the person and the pixel positions of the box corners.
This is the input image:
This is the required output:
This is what I have tried so far:
x=imread('frame 0080.png');
y=im2bw(x);
s=regionprops(y);
imshow(y);
hold on
for i=1:numel(s)
rectangle('Position',s(i).BoundingBox,'edgecolor','y')
end
This was the output I got:
It looks like you have tried what I have suggested. However, you want the bounding box that encapsulates the entire object. This can easily be done by using the BoundingBox property, then calculating each of the four corners of each rectangle. You can then calculate the minimum spanning bounding box that encapsulates all of the rectangles which ultimately encapsulates the entire object.
I do notice that there is a thin white strip at the bottom of your image, and that will mess up the bounding box calculations. As such, I'm going to cut the last 10 rows of the image before we proceed calculating the minimum spanning bounding box. To calculate the minimum spanning bounding box, all you have to do is take all of the corners for all of the rectangles, then calculate the minimum and maximum x co-ordinates and minimum and maximum y co-ordinates. These will correspond to the top left of the minimum spanning bounding box and the bottom right of the minimum spanning bounding box.
When taking a look at the BoundingBox property using regionprops, each bounding box outputs a 4 element vector:
[x y w h]
x,y denote the top left co-ordinate of your bounding box. x would be the column and y would be the row of the top left corner. w,h denote the width and the height of the bounding box. We would use this and compute top left, top right, bottom left and bottom right of every rectangle that is detected. Once you complete this, stack all of these rectangle co-ordinates into a single 2D matrix, then calculate the minimum and maximum x and y co-ordinates. To calculate the rectangle, simply use the minimum x and y co-ordinates as the top left corner, then calculate the width and height by subtracting the maximum and minimum x and y co-ordinates respectively.
Without further ado, here's the code. Note that I want to extract all of the bounding box co-ordinates in a N x 4 matrix where N denotes the number of bounding boxes that are detected. You would have to use reshape to do this correctly:
% //Read in the image from StackOverflow
x=imread('http://i.stack.imgur.com/mRWId.png');
% //Threshold and remove last 10 rows
y=im2bw(x);
y = y(1:end-10,:);
% //Calculate all bounding boxes
s=regionprops(y, 'BoundingBox');
%// Obtain all of the bounding box co-ordinates
bboxCoords = reshape([s.BoundingBox], 4, []).';
% // Calculate top left corner
topLeftCoords = bboxCoords(:,1:2);
% // Calculate top right corner
topRightCoords = [topLeftCoords(:,1) + bboxCoords(:,3) topLeftCoords(:,2)];
% // Calculate bottom left corner
bottomLeftCoords = [topLeftCoords(:,1) topLeftCoords(:,2) + bboxCoords(:,4)];
% // Calculate bottom right corner
bottomRightCoords = [topLeftCoords(:,1) + bboxCoords(:,3) ...
topLeftCoords(:,2) + bboxCoords(:,4)];
% // Calculating the minimum and maximum X and Y values
finalCoords = [topLeftCoords; topRightCoords; bottomLeftCoords; bottomRightCoords];
minX = min(finalCoords(:,1));
maxX = max(finalCoords(:,1));
minY = min(finalCoords(:,2));
maxY = max(finalCoords(:,2));
% Draw the rectangle on the screen
width = (maxX - minX + 1);
height = (maxY - minY + 1);
rect = [minX minY width height];
% // Show the image
imshow(y);
hold on;
rectangle('Position', rect, 'EdgeColor', 'yellow');
This is the image I get: