import gradio as gr from fastai.vision.all import * import skimage learn = load_learner('export.pkl') examples = [['Images/PKG - Breast-Metastases-MSKCC/Breast-Metastases-MSKCC/HobI16-053768896760.jpeg'], ['Images/PKG - CPTAC-BRCA/BRCA/01BR001-4ffefc66-d0ba-4a36-b4fa-35bd91.jpeg']] labels = learn.dls.vocab 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 = "Breast Cancer classification" description = "Demo for breast cancer classification using histopathology images." article="

Notebook

" interpretation='default' enable_queue=True gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=6),title=title,description=description,article=article,examples=examples , interpretation=interpretation,enable_queue=enable_queue).launch()