Instructions to use nithin1729s/kannadaLettersClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use nithin1729s/kannadaLettersClassification with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://nithin1729s/kannadaLettersClassification") - Notebooks
- Google Colab
- Kaggle
Kannada Alphabet Recognition using CNN
Usage & Full Project
This repository only contains the trained model file (full_model.h5).
To use this model in a complete application—including a web interface where users can draw Kannada letters and get real-time predictions—please visit the full project repository:
GitHub Repository: https://github.com/Nithin1729S/Kannada-CNN
The GitHub repo includes:
- Training code and dataset preprocessing
- Model architecture and evaluation
- A FastAPI backend for serving the model
- A Next.js (TypeScript) frontend with canvas drawing
- Complete setup instructions to run locally
📽️ Demo:
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