import gradio as gr from fastai.vision.all import * import skimage learn = load_learner('export 1.pkl') labels = learn.dls.vocab def predict(img): img = PILImage.create(img) pred,pred_idx,probs = learn.predict(img) prediction = str(pred) return prediction title = "Lung cancer detection with Deep Transfer Learning(ResNet152 model)" description = "

As a radiologist or oncologist, it is crucial to know what is wrong with a lung CT image.
Upload the breast X-ray image to know what is wrong with a patients breast with or without inplant

" article="

Web app is built and managed by Mr.

" examples = ['img 1.png', 'img 2.png'] enable_queue=True #interpretation='default' gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,enable_queue=enable_queue).launch()