import gradio as gr
from huggingface_hub import hf_hub_download
import subprocess

# Needed helper function for pickling
def label_func(o): return o[0].isupper()

# Download model requirements
requirements_hash = hf_hub_download(repo_id="muellerzr/fastai-pets-resnet-34", filename="requirements.txt")
subprocess.call(['pip', 'install', '-r', requirements_hash ])

# After installing, import Learner
from fastai.learner import load_learner

# Download and load model
learner_hash = hf_hub_download(repo_id="muellerzr/fastai-pets-resnet-34", filename="model.pkl")
learn = load_learner(learner_hash)

# Predict
def predict(img):
    clas, idx, probs = learn.predict(img)
    return "Dog" if clas == "False" else "Cat"

iface = gr.Interface(fn=predict, inputs="image", outputs="label")
iface.launch()