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HandwrittenDigitsRecognizer\nHandwritten digits recognizer by using a neural network.  \nShort video about it: [YouTube Shorts](https://youtube.com/shorts/ZE2NT-mdVBc?si=nZa1vGP0JAuYuont)\n\n# How to use\n* Download the MNIST training images from [here](http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz)\n* Download the MNIST training labels from [here](http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz)\n* Compile the neural network file: `javac NeuralNetwork.java`\n* Compile the JavaFX file: `javac --module-path $FX_PATH --add-modules javafx.controls HandRecognizer.java` were `$FX_PATH` contains the path of your lib folder in the javafx installation directory.\n* (optional) Train the model: `java NeuralNetwork.java`\n* Run the JavaFX application: `java --module-path $FX_PATH --add-modules javafx.controls HandRecognizer`\n\n# Instructions\n* Draw a number on the left (left mouse button) and the network will tell you what number it is and the confidence.\n* Use the `DELETE` key to clear the canvas\n* Use the digits from `0` to `9` to train the network while using it (for example if it recognizes some digits wrongly)\n* Use the `L` key to load a random image of the database\n\nAll the training data is saved in the file `training.txt`\n\n# Screenshot\n![Screenshot from 2024-06-16 10-48-39](https://github.com/OrangoMango/HandwrittenDigitsRecognizer/assets/61402409/4866073f-8b18-4dd2-bc1c-e757dcd15a07)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Forangomango%2Fhandwrittendigitsrecognizer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Forangomango%2Fhandwrittendigitsrecognizer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Forangomango%2Fhandwrittendigitsrecognizer/lists"}