from fastai.vision.all import * from pathlib import Path import gradio as gr import skimage path = Path('export.pkl') learn_inf = load_learner(path) def predict(img): img = PILImage.create(img) pred, pred_idx, probs = learn.predict(img) return {labels[i]:float(probs[i]) for i in range(len(labels))} title = "Pneumonia Classification using Pulmonary X-Ray Images" description = "An app designed to classify and distinguish between x-ray images of bacterial pneumonia, viral pneumonia and pulmonary health. Developed using the FastAI library and the V7 Lab COVID-19 X-Ray Dataset." examples = ['xray_1.png'] enable_queue = True gr.Interface(fn = predict, inputs = gr.inputs.Image(shape = (512, 512)), outputs = gr.outputs.Label(num_top_classes = 3), title = title, description = description, examples = examples, enable_queue = True).launch(share=True)