import os
import sys
import subprocess

# Install necessary packages if not already installed
required_packages = ["fastai", "gradio"]
for package in required_packages:
    try:
        __import__(package)
    except ImportError:
        subprocess.run([sys.executable, "-m", "pip", "install", package])

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

# Replace 'your_model_path' with the actual path to your model file

learn = load_learner('sphynx.pkl')

# Assuming you have two categories: 'cat' and 'sphinx cat'
categories = ('cat', 'sphinx cat')

def classify_image(im):
    pred, idx, probs = learn.predict(im)
    return dict(zip(categories, map(float, probs)))

# Define the input component
image = gr.Image()

# Define the output component
label_output = gr.Label()

# Create the Gradio interface
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label_output, examples=["Sphynx.jpg", "cat.jpg"])
intf.launch(share=False)