import gradio as gr
import timm
import numpy as np
from operator import itemgetter
from fastai.vision.all import *


learn = load_learner("./plants_10_epochs.pkl")

categories = learn.dls.vocab
def classify_image(img):
    pred, idx, probs = learn.predict(img)
    dict_all = dict(zip(categories, map(float,probs)))
    n = 5
    dict_n = dict(sorted(dict_all.items(), key=itemgetter(1), reverse=True)[:n])
    return dict_n

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
intf = gr.Interface(fn=classify_image,inputs=image,outputs=label)
intf.launch()