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



learn = load_learner('rocks-2.pkl')
  
labels = learn.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "rock classifier"
examples = ["basalt1.jpeg","coal.jpeg","granite.jpeg", "limestone.jpeg","marble.jpeg","quartzite.jpeg","sandstone.jpeg"]
gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(num_top_classes=7),title = title,examples= examples).launch(share=True)