import gradio as gr
from fastai.vision.all import *
import skimage
from PIL import Image
from timm import *

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

def classify_image(img):
    img = Image.fromarray(img)
    pred, idx, probs = learn.predict(img)
    return dict(zip(labels, map(float, probs)))


iface = gr.Interface(fn=classify_image, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3), interpretation="default", title="Watches classifier")
iface.launch()