Template-Matching | Searching the location of a template or a target image | Computer Vision library

I'm trying to move space-delimited tokens from one attribute to another in XSLT-2.0. For example, given

I'm new to OpenCV, I am getting Assertion failed error when I run a template matching code. The error message is given below

So I'm trying to create a program that can see what number an image is and print the integer in the console. (I'm using python 3)

For example that the program recognizes that the following image (an actual image the program has to check) is number 2:

I've tried to just compare it with an other image with the 2 in it with cv2.matchTemplate() but each time the blue pixels rgb values are a little bit different for each image and the image could be a bit larger or smaller. for example the following image:

It also has to recognize it apart from al the other blue number images (0-9), for example the following one:

I've tried mulitple match template codes, and make a folder with number 0-9 images as templates, but each time almost every single number is recognized in the number that needs to be recognized. for example number 5 gets recognized in an image that is number 2. And if its doesnt recognize all of them, it recognizes the wrong one(s).

The ones I've tried:

• Answer from this question
• Both codes from this tutorial
• And the one from this tutorial

but like I said before it comes with those problems.

I've also tried to see how much percentage blue is in each image, but those numbers were to close to tell the numbers appart by seeing how much blue was in them.

Does anyone have a solution? Am I being stupid for using cv2.matchTemplate() and is there a much simpler option? (I don't mind using a library for it, because this is part of a bigger piece of code, but I prefer to code it, instead of libraries)

I have done multi-scale template matching in real-time from looking at this article. When the template appears in the frame, it detects it and drawing a bounding box around it which means it works fine. But when there is no template in the frame also, it detects somewhere and drawing the bounding box. I'll mention the code and the error that I recognized.

I was able to do template matching from pictures from this and I applied the same to real-time which means I looped through the frames. But it does not seem to be matching the template with frames, And I realized that found(bookkeeping variable) is always None.

I'm trying to use the match_template method from the scikit-image library to check if a template exists inside an image and get its X and Y positions. I'm using the scikit-image template matching example.

My code looks like this:

I am doing a project where I need to detect musical elements from stave lines, and I am in the point where I know what duration an note element has (quarter, octet, etc) and I what to detect the center of the note-head so that I can found out what note it is (C, D, etc) based on its location on the stave lines.

The problem that I have is that I don't know exactly where to start. I was thinking about some template-matching using full and empty ovals as a template and the element Mat as a source.

Does anyone has any better and optimal solutions?

Examples of element Mats from where I want to find the note-head:

or or

Project on GitHub if anyone is interested https://github.com/AmbroziePaval/OMR

I have two surfaces, a large one

and a smaller one

I'm trying to adapt a template matching tutorial to these surfaces by treating them as grey-scale images.

I need to update the tutorial to scale independently in x and y, I've done this but adding an additional loop. My code is:

I am new to computer vision but I am trying to code an android app which does the following:

Get the live camera preview and try to detect one logo in that (i have the logo in my resources). In real-time. Draw a rect around the logo if found. If there is no match, dont draw the rectangle.

I already tried a couple of things including template-matching and feature detection using ORB.

Why that didnt work:

Template-matching: Issues with scaling and rotation. I tried a multi scale variant of it but a) the performance was really bad and b) the rectangle was of course always shown trying to search for the image. There was no way to actually confirm in the code if the logo was found or not.

ORB feature detection: Also pretty slow (5-6 fps) but it worked ok-ish. The other problem was that also i never could be sure if the logo was in the picture or not. ORB found random matches even if the logo was not in the picture.

Like I said, I am very new to this. I would appreciate the help on what would be the best way to achieve:

• Confirm if a picture A (around 200x200 pixels) is in ROI of camera picture (around 600x600 pixels).

• This shouldnt take longer than 50ms per frame. I dont know if thats even possible though. So if a correct way to do this would take a bit longer than that, I would just do the work in a seperate thread and only analyze like every fifth camera frame or so.

Would appreciate any hints or code examples on how to achieve that. Thank you!