gesture-recognition | Handwriting and gesture recognition with line integrals | Computer Vision library

 by   justinmeiners JavaScript Version: Current License: No License

kandi X-RAY | gesture-recognition Summary

kandi X-RAY | gesture-recognition Summary

gesture-recognition is a JavaScript library typically used in Artificial Intelligence, Computer Vision applications. gesture-recognition has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Handwriting and gesture recognition with line integrals.
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              gesture-recognition has a low active ecosystem.
              It has 13 star(s) with 1 fork(s). There are 1 watchers for this library.
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              It had no major release in the last 6 months.
              gesture-recognition has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of gesture-recognition is current.

            kandi-Quality Quality

              gesture-recognition has no bugs reported.

            kandi-Security Security

              gesture-recognition has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

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

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              gesture-recognition releases are not available. You will need to build from source code and install.

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            gesture-recognition Key Features

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            gesture-recognition Examples and Code Snippets

            No Code Snippets are available at this moment for gesture-recognition.

            Community Discussions

            QUESTION

            Getting the "ValueError: Shapes (64, 4) and (64, 10) are incompatible" when trying to fit my model
            Asked 2021-May-02 at 05:38

            I am trying to write my own neural network to detect certain hand gesture, following the code found from https://www.kaggle.com/benenharrington/hand-gesture-recognition-database-with-cnn/execution.

            ...

            ANSWER

            Answered 2021-May-02 at 05:38

            The problem here is the output labels, you didn't specify what data you used but its due to the number of labels for the output

            Its a simple fix if you change from 10 to 4

            Source https://stackoverflow.com/questions/67352985

            QUESTION

            Languages to develop applications for Xbox 360 kinect
            Asked 2021-Feb-03 at 13:26

            I know this sounds stupid and I'm propably very late to the party but here's the thing I want to program an gesture recogniction application (in the likes of this Hand detection or this actual finger detection) for the Xbox 360 Kinect. SDK (version 1.8) is found, installed and works, preliminary research is done - I only forgot to look in which language to write the code. The link from the SDK to the documentation would be the first thing to do but is a dead end, unfortunately.
            From the provided examples it seems either to be C++ or C# although some old posts also claim Java. My question is: Is there a documentation not tied to the SDK and which pitfall are there in regard to developing in this specific case under C++/C#/Java? A post from 2011 barely covers the beginning.

            Addendum: On further looking I was prompted for the Samples site from the developer toolkit - which can be reached, yet all listed and linked examples are dead ends too.

            Addendum: For reference I userd this instruction - ultimately proving futile.

            Found an version of NiTE here

            ...

            ANSWER

            Answered 2021-Jan-19 at 22:29

            I've provided this answer in the past.

            Personally I've used the Xbox360 sensor with OpenNI the most (because it's cross platform). Also the NITE middleware on alongside OpenNI provides some basic hand detection and even gesture detection (swipes, circle gesture, "button" push, etc.).

            While OpenNI is opensource, NITE isn't so you'd be limited to what they provide.

            The links you've shared use OpenCV. You can install OpenNI and compile OpenCV from source with OpenNI support. Alternatively, you can manually wrap the OpenNI frame data into an OpenCV cv::Mat and carry on with the OpenCV operations from there.

            Here's a basic example that uses OpenNI to get the depth data and passes that to OpenCV:

            Source https://stackoverflow.com/questions/65778896

            QUESTION

            I am getting a 100% accuracy on all my machine learning models. What is wrong with my model
            Asked 2020-Feb-25 at 20:57

            I am working on a dataset that is a collection of 5 Hand made letters. I've uploaded the DB on Kaggle and if anyone wants to give it a look, please do.

            https://www.kaggle.com/shayanriyaz/gesture-recognition

            Currently, I've trained and tested several models but I keep getting 100% accuracy.

            Here's my code.

            ...

            ANSWER

            Answered 2020-Feb-25 at 20:57

            There is nothing wrong with your model, it's just a trivial problem for the models to solve. These letters look nothing alike when you consider all of the features you have. If you had chosen all of the letters, or ones that all looked the same, you might see some error.

            Rerun the model using only index_pitch and index_roll. You will still get like 95% AUC. At least by doing that you can guess that the only loss comes from B,D, and K, which by looking at an image of what those look like are the only 3 that could remotely be confused if you only looked at the index finger. This turns out to be the case.

            It's just a problem that given your data set is actually solvable

            Source https://stackoverflow.com/questions/60401653

            QUESTION

            How to know if I need to reverse the thresholding TYPE after findContour
            Asked 2019-Jul-10 at 12:37

            I'm working with OpenCV on hand detection. But I'm struggling when trying to contours of the threshed image. findContour will always try to find white area as contour.

            So basically it works in most cases but sometimes my threshed image looks like this :

            _, threshed = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY|cv2.THRESH_OTSU)

            So to make it works I just need to change the threshold type cv2.THRESH_BINARY_INV.

            _, threshed = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV|cv2.THRESH_OTSU)

            And it works well.

            My question is how can I determine when the threshold need to be reversed ? Does I Need to always found contours on both threshed images, and compare the result (I this case How ?) ? or there is a way to allays knows if contours are not totally missed.

            EDIT : There is a way to be 100% sure contour looks like a hand ?

            EDIT 2 : So I forgot to mention that I'm trying to detect fingertips and defects using this method so I need defects, which with the first threshed image I can't find them, because it reversed. See blue point on the First contour image.

            Thanks.

            ...

            ANSWER

            Answered 2019-Jul-10 at 12:37

            You can write a utility method to detect the most dominant color along the border and then decide the logic, as if you want to invert the image or not, so the flow may look like:

            1. Use OSTU binarization method.
            2. Pass the thresholded image to utility method get_most_dominant_border_color and get the dominant color.
            3. If the border color is WHITE, then you should invert the image using cv2.bitwise_not, else keep it that way only.

            The get_most_dominant_border_color could be defined as:

            Source https://stackoverflow.com/questions/56967542

            QUESTION

            Hand recognition script for OpenCV+Python not working
            Asked 2018-Dec-07 at 03:02

            I'm trying to get the following script to work. I found it from this website but I keep getting the error :

            contours, hierarchy = cv2.findContours(thresh1,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) ValueError: too many values to unpack (expected 2)

            I have little experience in Python and OpenCV so if anyone here can help that would be much appreciated! I'm running Mac OS X 10.13.4, OpenCV 3.4.1, Python 3.6.5 and

            Here is the script I'm trying to get work :

            ...

            ANSWER

            Answered 2018-Dec-07 at 03:02

            The function cv2.fincContours has changed since OpenCV 3.x , and back in OpenCV 4.x . Try this:

            Source https://stackoverflow.com/questions/50850937

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

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