app.py

import numpy as np
from sklearn import svm
from sklearn.metrics import accuracy_score
from tensorflow import keras
import gradio as gr


(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()


x_train = x_train.reshape(-1, 28*28) / 255.0
x_test = x_test.reshape(-1, 28*28) / 255.0


clf = svm.SVC()


clf.fit(x_train, y_train)


y_pred = clf.predict(x_test)


accuracy = accuracy_score(y_test, y_pred)
print(f"Accuracy: {accuracy}")



def classify_digit(image):

    image = image.reshape(1, 28*28) / 255.0


    pred = clf.predict(image)


    return int(pred[0])



interface = gr.Interface(
    fn=classify_digit,
    inputs=gr.Sketchpad(invert_colors=True),
    outputs=gr.Text(),
    title="MNIST Digit Classifier",
    description="Draw a digit on the sketchpad and click 'Submit' to classify it , Draw in centre for better accuracy",
    theme="default"
)


interface.launch()