from fastai.vision.all import *
import gradio as gr
import skimage

learn = load_learner('model.pkl')
labels = learn.dls.vocab

def classify_image(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['grizzly bear.png', 'black bear.png', 'teddy bear.png']

demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title="Image Classifier", description="Upload an image to classify it.")
demo.launch()