app.py

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

learn = load_learner('export.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 = "Assault Rifles Classifier"
description = "By now classifier is trained to distinguish the following rifles: AK-47, AR-15, FAMAS, FN SCAR, M16, M4 Carabine"
examples = "examples"
interpretation='default'
enable_queue=True

gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=6),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()