https://github.com/shettysach/kannada-handwriting-calculator

A calculator that uses handwritten Kannada digits and operators to calculate the result, using contour detection and CNN model predictions. Made using PyTorch, OpenCV, PIL and CustomTkinter.
https://github.com/shettysach/kannada-handwriting-calculator

basic-arithmetic-operations cnn cnn-classification cnn-keras convo handwriting-calculator handwritten-digit-recognition jupyter-notebook kannada kannada-digit kannada-mnist keras keras-models keras-tensorflow mnis opencv opencv2 pillow tensorflow tensorflow2

Last synced: 18 days ago
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A calculator that uses handwritten Kannada digits and operators to calculate the result, using contour detection and CNN model predictions. Made using PyTorch, OpenCV, PIL and CustomTkinter.

• Host: GitHub
• URL: https://github.com/shettysach/kannada-handwriting-calculator
• Owner: ShettySach
• Created: 2023-10-10T13:39:00.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-07-11T04:58:23.000Z (5 months ago)
• Last Synced: 2024-07-11T22:52:02.071Z (5 months ago)
• Topics: basic-arithmetic-operations, cnn, cnn-classification, cnn-keras, convo, handwriting-calculator, handwritten-digit-recognition, jupyter-notebook, kannada, kannada-digit, kannada-mnist, keras, keras-models, keras-tensorflow, mnis, opencv, opencv2, pillow, tensorflow, tensorflow2
• Language: Jupyter Notebook
• Homepage:
• Size: 1.32 MB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Kannada-Handwriting-Calculator

![Demo](./assets/Demo.gif)

##### Contour boxes (green), predicted classes (blue) and prediction probabilities (red)

![Contours](./assets/Contours.png)

A calculator that uses handwritten ಕನ್ನಡ (Kannada) digits and operators to calculate the result, using contour detection and ConvNet (Convolutional Neural Network) model prediction.

- PyTorch is used to create, train and load the state of the neural network model used for predictions.

- OpenCV and Pillow (PIL) are used to read input from the GUI canvas and to obtain contours for individual digits/operators.

- CustomTKinter is used to provide the GUI.

- The individual digits/operators are detected and their most probable target classes are predicted. The predictions are combined into a string and evaluated to get the result.

- `src/ConvNet.ipynb` consists of processing the data, creating the CNN model architecture and then training the model.

- `src/Main.ipynb` consists of loading the trained model state and using it to make predictions for the calculator app.

### Requirements -

For Linux

```bash

conda create --name  --file requirements.txt

conda activate 

pip install customtkinter

```

For Linux / others

```shell

conda create -c conda-forge -c pytorch --name  --file reqs.txt

conda activate 

pip install customtkinter

```

- python 3.9.18

- pytorch 2.3.1

- opencv 4.10.0

- numpy 2.0.0

- pillow 10.3.0

- customtkinter 5.2.2

- pandas 2.2.2 [ Training only ]

- torchvision 0.18.1 [ Training only ]

### Instructions -

- Clone the repo and run the Jupyter Notebook, `src/Main.ipynb`, or run `src/Main.py`.

- You can use Kannada digits `೦ ೧ ೨ ೩ ೪ ೫ ೬ ೭ ೮ ೯`, operators `+ - × /`, decimal point `.` and parentheses `()`.

- You can also use `××` for exponentiation and `//` for floor division.

- To train the model yourself, download the data, unzip, move it into the `datasets` directory, and then run the Jupyter Notebook `src/ConvNet.ipynb`. 

    > NOTE:

    Depending on your screen resolution, you may need to change canvas size, brush delta/displacement and brush thickness to get more accurate results.

### Data

* [Kannada MNIST dataset](https://www.kaggle.com/competitions/Kannada-MNIST/data)

* [Symbol dateset by Irfan Chahyadi ](https://github.com/irfanchahyadi/Handwriting-Calculator/blob/master/src/dataset/data.pickle)