userKaran/currencyClassification

1import gradio as gr2import numpy as np3from transformers import pipeline4 5classifier = pipeline("image-classification", model="Chimmi/bhutanese-currency-model")6 7def image_classifier(inp):8    confidence_scores = np.random.rand(8)9    confidence_scores /= np.sum(confidence_scores)10    classes = ['Nu. 1','Nu. 10','Nu. 100','Nu. 1000','Nu. 20','Nu. 5','Nu. 50','Nu. 500']11    result = {classes[i]: confidence_scores[i] for i in range(8)}12    return result13 14# Define description and example images15title = "Bhutanese Currency Classifier"16description = "This model classifies images of Bhutanese currency notes into different denominations."17examples = [ "1.jpg","5.jpg","10.jpg", "20.jpg", "50.jpg", "100.jpg", "500.jpg", "1000.jpg"]18 19demo = gr.Interface(fn=image_classifier, inputs="image", outputs="label")20demo.launch()