brnmisson/LandUse

1import gradio as gr2from fastai.vision.all import *3import skimage4 5learn = load_learner('model.pkl')6 7labels = learn.dls.vocab8def predict(img):9    #img = PILImage.create(img)10    pred,pred_idx,probs = learn.predict(img)11    return {labels[i]: float(probs[i]) for i in range(len(labels))}12 13title = "Land Use Classifier"14description = "A  classifier trained as a demo for Gradio and HuggingFace Spaces."15 16examples = ['shrub.jpg', 'forest.jpg', 'crop land.jpg']17 18enable_queue=True19 20gr.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=enable_queue).launch()