How to measure the performance (precision and recall ) for following model and does it need to have groundTruth?

7 次查看（过去 30 天）
yasmin ismail
yasmin ismail 2023-9-26
评论： yasmin ismail 2023-10-2
I have 3 questions for classical computer vision detection model for crack detection.
I attached the original image (input ) and the output thus,
1- How many image I need to calculate the peformance of this model(Precision, recall,....) if I want o reach accuracy above 90%?
2-Does this type of model need to have the groundTruth or the original image is the groundTruth?
3-Does this type of model needs to train (80% for traing and 20% for testing) and how to do it, or traingnig only for machine learning and deep learning model ?
% Program to compute the mean width of a blob in an image.
clearvars;
close all;
clc;
fontSize = 15;
% Read in original image, with white lightning on black background.
baseFileName = 'Original image.jpg';
fullFileName = fullfile(pwd, baseFileName);
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)
if numberOfColorChannels > 1
% It's not really gray scale like we expected - it's color.
% Use weighted sum of ALL channels to create a gray scale image.
% grayImage = rgb2gray(rgbImage);
% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
% which in a typical snapshot will be the least noisy channel.
grayImage = grayImage(:, :, 2); % Take green channel.
else
grayImage = grayImage; % It's already gray scale.
end
% Now it's gray scale with range of 0 to 255.
subplot(2, 3, 1);
imshow(grayImage, [])
impixelinfo; % Let user mouse around and see values in the status line at the lower right.
title('Original Image', 'FontSize', fontSize);
% Binarize the image.
% mask = imbinarize(grayImage);
lowThreshold = 0;
highThreshold = 160;
% Interactively and visually set a threshold on a gray scale image.
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image?s_tid=srchtitle
[lowThreshold, highThreshold] = threshold(lowThreshold, highThreshold, grayImage);
mask = grayImage >= lowThreshold & grayImage <= highThreshold;
% Fill holes.
mask = imfill(mask, 'holes');
% Take largest blob only.
mask = bwareafilt(mask, 1);
subplot(2, 3, 2);
imshow(mask)
impixelinfo; % Let user mouse around and see values in the status line at the lower right.
title('Mask', 'FontSize', fontSize)
% Compute the skeleton
skelImage = bwskel(mask);
subplot(2, 3, 3);
imshow(skelImage)
impixelinfo; % Let user mouse around and see values in the status line at the lower right.
title('Thinned', 'FontSize', fontSize)

请先登录，再回答此问题。

回答（1 个）

Pratham Shah
Pratham Shah 2023-9-28
Yes, You need to have a ground truth in order to obtain accuracy, precision and recall. If you have ground truth you can calculate all those parameters.
  5 个评论
显示 3更早的评论
Pratham Shah
Pratham Shah 2023-10-1
You can use Image Segmenter application of MATLAB or LableImg to mark background and foreground(Cracks). With that image you can compute accuracy of your algorithm.
yasmin ismail
yasmin ismail 2023-10-2
@Pratham Shah thanks I used Imgae segmeneter and I got the result as shown in attached file (crack) which is groundTruth, now how can I apply IoU to compare between the GrndTruth and model out put ? I attached the outPut Too

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 Image Category Classification 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by