hough-transform | http :

 by   FremyCompany JavaScript Version: Current License: No License

kandi X-RAY | hough-transform Summary

kandi X-RAY | hough-transform Summary

hough-transform is a JavaScript library. hough-transform has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

http://fremycompany.com/BG/2016/Detect-lines-in-an-image-using-JavaScript-353/
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            kandi-support Support

              hough-transform has a low active ecosystem.
              It has 15 star(s) with 3 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              hough-transform has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of hough-transform is current.

            kandi-Quality Quality

              hough-transform has 0 bugs and 0 code smells.

            kandi-Security Security

              hough-transform has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              hough-transform code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              hough-transform does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              hough-transform releases are not available. You will need to build from source code and install.
              hough-transform saves you 5 person hours of effort in developing the same functionality from scratch.
              It has 17 lines of code, 0 functions and 2 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed hough-transform and discovered the below as its top functions. This is intended to give you an instant insight into hough-transform implemented functionality, and help decide if they suit your requirements.
            • Run the final step
            • Runs step step
            • Increments the MD - value of a quadrant .
            Get all kandi verified functions for this library.

            hough-transform Key Features

            No Key Features are available at this moment for hough-transform.

            hough-transform Examples and Code Snippets

            No Code Snippets are available at this moment for hough-transform.

            Community Discussions

            QUESTION

            Multiple template matching with Scikit-image
            Asked 2022-Mar-29 at 11:59

            I want to find the middle of a coin and find the radii. The radii can tell me if the coin is 5 cents of 50 cents. After finding the image, I must be able to detect the middle of the circles so I can give them a color

            I already made a beginning with writing a code for Hough-transform

            Hopefully someone can help me solve this exercise.

            Code for hough transform:

            ...

            ANSWER

            Answered 2022-Mar-29 at 11:59

            You have 2 choices to find matching circles.

            first one: sliding window

            smaller windows is a template that you seek for it in input image, here two images with different radii 19 and 21 respectively. First at all, find edge of template and input image, after that, multiplying cropped part of image with template. each region that is near to template should have higher value.

            Source https://stackoverflow.com/questions/71651920

            QUESTION

            Find rails and their corresponding course using OpenCV in Python
            Asked 2021-Apr-23 at 12:49

            I am working on a detection of LEGO City Rails to obtain if there is a curve and and whats the curve radius or angle.

            As you can see I already cropped the picture. I also used different algorithms for edge detection like canny or just sobel operators.

            Unfortunately the railroad ties make it really hard to detect the curve properly. I already tried hough transform, but this doesn't work well. Also the OpenCV-function cv2.findContours doesn't work very well.

            The following picture shows my current status which uses Canny Edge Detection. The red lines in the picture show the lines generated by the probablistic Hough-Transform. I already removed all horizontal lines and all lines with an angle smaller than 10 degree generated by the hough transform.

            Why doesn't the hough transform detect all lines in this picture?

            Do you guys have any suggestions how I can detect the rails properly?

            Thank you in advance!

            ...

            ANSWER

            Answered 2021-Apr-23 at 12:49
            import cv2
            import numpy as np
            
            def empty(a):
                pass
            
            
            path = 'media/SVIi0.png'
            cv2.namedWindow("TrackBars")
            cv2.resizeWindow("TrackBars",640,240)
            cv2.createTrackbar("Hue Min","TrackBars",11,179,empty)
            cv2.createTrackbar("Hue Max","TrackBars",66,179,empty)
            cv2.createTrackbar("Sat Min","TrackBars",0,255,empty)
            cv2.createTrackbar("Sat Max","TrackBars",255,255,empty)
            cv2.createTrackbar("Val Min","TrackBars",21,255,empty)
            cv2.createTrackbar("Val Max","TrackBars",255,255,empty)
            
            while True:
                img = cv2.imread(path)
                imgHSV = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
                h_min = cv2.getTrackbarPos("Hue Min","TrackBars")
                h_max = cv2.getTrackbarPos("Hue Max", "TrackBars")
                s_min = cv2.getTrackbarPos("Sat Min", "TrackBars")
                s_max = cv2.getTrackbarPos("Sat Max", "TrackBars")
                v_min = cv2.getTrackbarPos("Val Min", "TrackBars")
                v_max = cv2.getTrackbarPos("Val Max", "TrackBars")
                print(h_min,h_max,s_min,s_max,v_min,v_max)
                lower = np.array([h_min,s_min,v_min])
                upper = np.array([h_max,s_max,v_max])
                mask = cv2.inRange(imgHSV,lower,upper)
                imgResult = cv2.bitwise_and(img,img,mask=mask)
            
            
                cv2.imshow("Mask Images", mask)
                cv2.imshow("Original Images", img)
            
                cv2.waitKey(1)
            

            Source https://stackoverflow.com/questions/67225978

            QUESTION

            How can I measure the length of line segments in image mask in MATLAB?
            Asked 2021-Feb-12 at 05:15

            I have a binary image (BW_roi.mat), displayed below. And I wanted to measure the length of every line segment.

            I tried the solution given in this link hough-transform. But it does not work out for me. It just measured the length of some lines as shown below.

            I tried the other code

            ...

            ANSWER

            Answered 2021-Feb-12 at 05:15

            I'd propose using convexhull in combination with the algorithm here to reduce the number of vertices in the detected polygons. Seems to work pretty well. I'll leave it to you to use the adjacency matrix produced by bwboundaries to throw away duplicates.

            Source https://stackoverflow.com/questions/66143757

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install hough-transform

            You can download it from GitHub.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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          • HTTPS

            https://github.com/FremyCompany/hough-transform.git

          • CLI

            gh repo clone FremyCompany/hough-transform

          • sshUrl

            git@github.com:FremyCompany/hough-transform.git

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