metadata

language: en
license: mit
tags:
  - tensorflow
  - image-classification
  - mnist
  - digits
datasets:
  - mnist
metrics:
  - accuracy

Digit Recognition Model

This model is trained to recognize handwritten digits from the MNIST dataset.

Model Description

Model Type: CNN with Attention
Task: Image Classification
Input: 28x28 grayscale images
Output: Digit classification (0-9)

Training

The model was trained on the MNIST dataset using a CNN architecture with attention mechanisms.

Usage

import tensorflow as tf
import numpy as np

# Load the model
model = tf.saved_model.load("path_to_saved_model")

# Prepare input
image = tf.keras.preprocessing.image.load_img("digit.png", target_size=(28, 28))
image = tf.keras.preprocessing.image.img_to_array(image)
image = image.astype('float32') / 255.0
image = np.expand_dims(image, axis=0)

# Make prediction
predictions = model(image)
predicted_digit = tf.argmax(predictions, axis=1).numpy()[0]