Question

未定义的功能＆＃39; imageSet＆＃39;对于＆＃39; char＆＃39;。

类型的输入参数

构建错误（第3行） buildingScene = imageSet（buildingDir）;

% Load images.
buildingDir = fullfile(toolboxdir('vision'), 'visiondata', 'building');
buildingScene = imageSet(buildingDir);
% Display images to be stitched
montage(buildingScene.ImageLocation)
% Read the first image from the image set.
I = read(buildingScene, 1);
% Initialize features for I(1)
grayImage = rgb2gray(I);
points = detectSURFFeatures(grayImage);
[features, points] = extractFeatures(grayImage, points);

% Initialize all the transforms to the identity matrix. Note that the
% projective transform is used here because the building images are fairly
% close to the camera. Had the scene been captured from a further distance,
% an affine transform would suffice.
tforms(buildingScene.Count) = projective2d(eye(3));

% Iterate over remaining image pairs
for n = 2:buildingScene.Count

    % Store points and features for I(n-1).
    pointsPrevious = points;
    featuresPrevious = features;

    % Read I(n).
    I = read(buildingScene, n);

    % Detect and extract SURF features for I(n).
    grayImage = rgb2gray(I);
    points = detectSURFFeatures(grayImage);
    [features, points] = extractFeatures(grayImage, points);

    % Find correspondences between I(n) and I(n-1).
    indexPairs = matchFeatures(features, featuresPrevious, 'Unique', true);

    matchedPoints = points(indexPairs(:,1), :);
    matchedPointsPrev = pointsPrevious(indexPairs(:,2), :);

    % Estimate the transformation between I(n) and I(n-1).
    tforms(n) = estimateGeometricTransform(matchedPoints, matchedPointsPrev,...
        'projective', 'Confidence', 99.9, 'MaxNumTrials', 2000);

    % Compute T(1) * ... * T(n-1) * T(n)
    tforms(n).T = tforms(n-1).T * tforms(n).T;
end
avgXLim = mean(xlim, 2);

[~, idx] = sort(avgXLim);

centerIdx = floor((numel(tforms)+1)/2);

centerImageIdx = idx(centerIdx);
Tinv = invert(tforms(centerImageIdx));

for i = 1:numel(tforms)
    tforms(i).T = Tinv.T * tforms(i).T;
end
for i = 1:numel(tforms)
    [xlim(i,:), ylim(i,:)] = outputLimits(tforms(i), [1 imageSize(2)], [1 imageSize(1)]);
end

% Find the minimum and maximum output limits
xMin = min([1; xlim(:)]);
xMax = max([imageSize(2); xlim(:)]);

yMin = min([1; ylim(:)]);
yMax = max([imageSize(1); ylim(:)]);

% Width and height of panorama.
width  = round(xMax - xMin);
height = round(yMax - yMin);

% Initialize the "empty" panorama.
panorama = zeros([height width 3], 'like', I);
Step 4 - Create the Panorama

Use imwarp to map images into the panorama and use vision.AlphaBlender to overlay the images together.

blender = vision.AlphaBlender('Operation', 'Binary mask', ...
    'MaskSource', 'Input port');

% Create a 2-D spatial reference object defining the size of the panorama.
xLimits = [xMin xMax];
yLimits = [yMin yMax];
panoramaView = imref2d([height width], xLimits, yLimits);

% Create the panorama.
for i = 1:buildingScene.Count

    I = read(buildingScene, i);

    % Transform I into the panorama.
    warpedImage = imwarp(I, tforms(i), 'OutputView', panoramaView);

    % Create an mask for the overlay operation.
    warpedMask = imwarp(ones(size(I(:,:,1))), tforms(i), 'OutputView', panoramaView);

    % Clean up edge artifacts in the mask and convert to a binary image.
    warpedMask = warpedMask >= 1;

    % Overlay the warpedImage onto the panorama.
    panorama = step(blender, panorama, warpedImage, warpedMask);
end

figure
imshow(panorama)

Answer 1

imageSet需要MATLAB R2014b或更高版本的计算机视觉工具箱。请参阅计算机视觉工具箱中的发行说明：http://www.mathworks.com/help/vision/release-notes.html#R2014b

如果你有R2014a或更低，imageSet不附带你的发行版。您唯一的选择是升级MATLAB发行版。对不起，如果这不是您想听到的内容！

我想制作全景图像，但它显示错误信息未定义的功能＆＃39; imageSet＆＃39;对于＆＃39; char＆＃39;类型的输入参数

1 个答案: